Health services administration

The Research Enterprise Funding Australia's basic biomedical research of 1993 and 1994 The meshing of two databases of scientific publications -- the Wellcome Trust's Research Outputs Database, and the Research Evaluation and Policy Project's database of Australian publications -- allows a detailed analysis of the funding agencies providing external (as opposed to intramural) support for Australia's basic biomedical research. This analysis shows the success Australian researchers are having in attracting funding from overseas, and the high citation rates achieved by publications with external funding. Linda Butler MJA 1999; 171: 629-633 Introduction - Characteristics of basic biomedical research funding - Comparison of funded and unfunded publications - The impact of funded research - Conclusions - References - Authors' details - - More articles on Economics

Linda Butler

Research Reliability of sentinel node status in predicting axillary lymph node involvement in breast cancer James Kollias, P Grantley Gill, Barry E Chatterton, Vivian E Hall, Melissa A Bochner, Brendon J Coventry and Gelareh Farshid MJA 1999; 171: 461-465 For editorial comment, see Ung & Wetzig Abstract - Introduction - Methods - Results - Discussion - References - Authors' details - - More articles on Oncology Abstract Objectives: To assess the reliability of determining sentinel node status in staging regional lymph nodes in breast cancer. Design and setting: Prospective validation study in a major public teaching hospital, comparing histological sentinel node status with that of remaining axillary nodes. Patients: 117 women who underwent sentinel node biopsy and axillary dissection for primary breast cancer between 1995 and 1998. Main outcome measures: Intraoperative success rate in sentinel node identification; false negative rate; predictive value of negative sentinel node status; overall accuracy of sentinel node status. Results: The sentinel node was identified at operation in 95 patients (81.2%). Tumour involvement of the sentinel node was demonstrated in 29 of 31 women (93.5%; 95% CI, 79%-99%). Sixty-four of the 66 women in whom the sentinel node was negative for tumour showed no further involvement of remaining axillary nodes (standard haematoxylin-eosin histological assessment), giving a predictive value of negative sentinel node status of 97% (95% CI, 89%-100%). The overall accuracy in 95 women in whom sentinel node status was compared with axillary node status was 97.9%. Conclusions: Histopathological examination of the sentinel node is an accurate method of assessing axillary lymph node status in primary breast cancer and is likely to be incorporated into future surgical management of women with primary breast cancer. Introduction Axillary lymph node status is the most important prognostic indicator in early breast cancer, and the detection of nodal metastases is a key factor in recommending adjuvant systemic therapy after surgery.1,2 Surgical removal and histopathological assessment of these nodes remains the only accurate way of determining their involvement with tumour. Axillary dissection also reduces the risk of regional recurrence of breast cancer in the axilla,3 as the risk is inversely related to the number of axillary nodes removed.4However, axillary lymph node dissection is not without morbidity: seroma formation, wound infection, damage to nerves, and reduced shoulder mobility. Of particular importance is lymphoedema, which occurs in 15% and 30% of women.5-8 As a consequence, other, less invasive methods of assessing axillary node status have been investigated (eg, mammography, ultrasound and colour doppler imaging, magnetic resonance imaging [MRI] and positron emission tomography [PET] scanning), but have yet to achieve the accuracy of surgical staging. Axillary node sampling -- removal of a small number of Level 1 nodes (those below the lower border of the pectoralis minor muscle) -- is associated with fewer complications, and has been proposed as an alternative to complete axillary dissection for staging of the axilla.9,10 However, its efficacy has been questioned.11 With the advent of population-based mammographic screening programs, there has been a dramatic decrease in tumour size and lymph node involvement in women diagnosed with early breast cancer.12,13 Thus, an increasing proportion of women will undergo axillary dissection only to find that their lymph glands are free of disease. Ideally, there should be a method of providing accurate assessment of axillary lymph node status without the need for axillary dissection. The sentinel lymph node (the first draining node within a lymph node basin) is the first to receive lymphatic drainage from a tumour site. Selective biopsy of this node allows the detection of metastases in clinically normal nodes with a low false negative rate, and has been used in patients with operable breast cancer by several groups.14-19 Their findings indicate that the status of the sentinel node(s) can accurately predict that of the fully dissected axilla. We report our experience of lymphoscintigraphy, intraoperative sentinel node mapping and sentinel node biopsy in 117 women with primary operable breast cancer. Our aims were: To assess the success rate of lymphoscintigraphy and intraoperative lymph node mapping in identifying the sentinel node; and To assess the accuracy of sentinel node biopsy in staging the axillary nodes. Methods Patients A consecutive series of 117 women treated for primary breast cancer at the Royal Adelaide Hospital Breast Unit between June 1995 and August 1998 entered a prospective evaluation of the technique of sentinel lymph node biopsy in breast cancer. Ethical approval for the study was provided by the Human Ethics Committee of the Royal Adelaide Hospital. All women gave written informed consent to participate in the study. Eligibility criteria were: Operable primary breast cancer (tumour, < 5 cm in diameter), detected clinically and by imaging, and confirmed by cytology, core biopsy or open biopsy; Clinically impalpable axillary lymph nodes; and The usual surgical indications for axillary dissection (ie, invasive, operable cancer). Patients were excluded if their condition did not fulfil these criteria; if they were pregnant or currently breastfeeding; if there was a high clinical suspicion or preoperative verification of axillary nodal involvement; or if they had metastatic breast carcinoma or a preoperative diagnosis of ductal carcinoma-in-situ. The women's ages ranged from 31 to 82 years (median, 60 years). Their clinical characteristics are summarised in Table 1. During the period of study, no eligible women refused entry to the study. Isotope injection technique The radiopharmaceutical used was 99mTc-labelled antimony sulfide colloid ("Lymph-Flo", Royal Adelaide Hospital Radiopharmacy). The colloid underwent filtration through a 0.2-µ sterile filter, ensuring more than 80% of the filtered particles were smaller than 20 nm. A 32-mm, 25-gauge needle was used to inject 40 MBq of tracer to four sites surrounding the palpable margin of the breast lesion. If the lesion was not palpable, ultrasound localisation was performed, and the injection was given in a similar manner under ultrasound guidance. In the initial stages of the study, 0.5 mL of tracer was injected in each of 82 patients. For the remaining 35 women, the injected volume was increased to 4 mL in four divided doses. In these latter women, the injection site was lightly massaged, and they were instructed to move their arms to encourage lymphatic movement. All radioisotope injections were given on the morning of the day of surgery. Lymphoscintigraphy and lymph node mapping After injection, serial anterior and appropriate lateral images were obtained with a large-field-of-view gamma camera (GE XRT, General Electric) at about 15-minute intervals until the initial draining node (or nodes) was visualised (Figure 1). The surface projection of the sentinel node was then marked on the skin with a radioactive marker. Orthogonal projections were made by the established technique of "triangulation"; the marks were joined by a straight line to indicate the base of a right-angled triangle with the node at the apex. Body outline was marked with a radioactive marker, or a transmission image was performed by holding a "flood" source behind the patient. The intraoperative probe (RMD CTC 4 with audible guidance system, Gammasonics, Melbourne) was calibrated in the Nuclear Medicine Department to the counts detected at the skin surface. Surgical technique After completion of lymphoscintigraphy and sentinel node mapping, the patient and hand-held gamma probe were transferred to the operating theatre. In 66 patients, 1-2 mL of 2.5% Patent Blue V dye (Guerbet Laboratories, France; distributed by Fauldings Australia, Adelaide) was injected into the breast parenchyma or subdermal fat overlying the tumour to facilitate intraoperative identification of the sentinel node. Blue dye alone was used in 19 patients before a gamma probe was available. At operation, a 2-cm transverse axillary incision was made in accordance with the planned axillary lymph node dissection, but taking into account the preoperative skin markings indicating the location of the sentinel node at lymphoscintigraphy. An attempt was made to identify the node in vivo before commencement of axillary dissection. The node was identified by its blue colour (if dye was used) and/or by the hand-held gamma probe (in a sterile sheath). The probe enabled detection of individual nodes with radioactivity levels significantly greater than those of the axillary fat (Figure 2). Sometimes more than one sentinel node was identified. If both dye and radioisotope were used for lymphatic mapping, the blue node corresponded to the most radioactive node. Once the sentinel node was removed, its activity was reassessed ex vivo and it was sent for histological examination separately from the main axillary nodal specimen. The axillary fat was then examined with the gamma probe in vivo to exclude any residual activity suggesting further sentinel nodes. The axillary skin incision was then lengthened and a level I and II axillary lymph node dissection was performed. The resected axillary tissue was examined ex vivo using the probe to identify any further radioactive or blue lymph nodes not identified during in-vivo examination. Histopathological examination All specimens were examined by duty histopathologists at the Institute of Medical and Veterinary Science. The histological tumour features were classified according to tumour size and grade,20 and presence or absence of vascular invasion.21 Generally, sentinel nodes were submitted in their entirety for histological evaluation. Those larger than 1.5 cm were sliced before paraffin embedding. Each node was placed in an individual cassette. At least one section of each node was stained with haematoxylin-eosin (H&E) and examined with light microscopy. Immunohistochemical analysis (antikeratin antibody CAM 5.2, Becton Dickinson) was performed in H&E-stained sections suspected of having metastatic tumour deposits. The axillary fat was fixed in formalin and the nodes were later isolated from the fat after clearance in Carnoy's solution. Each node was placed in an individual cassette and larger nodes were sliced before being embedded in paraffin. At least one H&E-stained section of each node was examined. Statistical analysis A false negative sentinel node was defined as an excised sentinel lymph node which contained no microscopically detectable tumour, but which was associated with at least one tumour-positive node in the remaining resected axillary tissue. The false negative rate and the predictive value of negative sentinel node status were calculated together with 95% confidence intervals. The kappa (κ) statistic for paired data was used to assess the level of agreement between sentinel node status and axillary node status.22 A score of -1 indicates perfect disagreement and + 1 indicates perfect agreement. The corresponding z and P values were calculated. Univariate analysis was used to assess clinical and histological factors that predicted intraoperative sentinel node localisation. Fisher's exact and χ2 tests were used for other analyses between groups. Results Lymphoscintigraphy The sentinel node was identified on preoperative lymphoscintigraphy in 74 of 117 women (63.2%). One sentinel node was identified in 52 women, two were identified in 20 women, and in two further women three and four sentinel nodes were identified, respectively. The sentinel node was identified outside the lower axilla in nine patients (Table 2). A significant increase in sentinel node identification at lymphoscintigraphy was noted after the injection of larger isotope volumes into the breast (77% v 57%; χ2 = 4.15; P = 0.04), while rates of intraoperative detection of the sentinel node also increased (91% v 76%; χ2 = 3.4; P = 0.06). Intraoperative sentinel node identification The sentinel node was identified in 95 patients (81.2%) at operation. In 66 women, one sentinel node was identified, two were identified in 20 women, three in eight women, and in one four sentinel nodes were identified. The sentinel node was identified in 35 of the 51 women in whom radioisotope alone was used (68.6%), compared with 18 of 19 women in whom blue dye alone was used (94.7%) and 42 of 47 women in whom both isotope and blue dye were used (89.4%) (χ2 = 9.6; P = 0.008). Of the clinical and histological factors assessed for predicting intraoperative sentinel node identification, only a positive preoperative lymphoscintigram was significant (χ2 = 28.7; P < 0.001) (Table 3). Predictive value of sentinel node(s) In 95 patients in whom the sentinel node was identified, 31 had metastatic tumour involvement of axillary nodes (32.6%). Tumour involvement of the sentinel node was demonstrated in 29 of these 31 women (93.5%; 95% CI, 79%-99%), giving a false negative rate of 6.5%. The sentinel node was the only positive node in 13 of 31 women (41.9%). Of 66 women with a negative sentinel node, 64 had no tumour involvement in the remainder of the axillary nodes (by standard H&E histological assessment), giving a predictive value of negative sentinel node status of 97% (95% CI, 89%-100%). The overall accuracy in 95 patients in whom sentinel node status was compared with axillary node status was 97.9% (κ, 0.95; z = 9.3; P < 0.001) (Table 4). Of the 22 women in whom the sentinel node was not identified at operation, six had nodal metastases on histological examination of the dissected axillary nodes. Discussion The concept of the sentinel lymph node is based on the premise that the first lymph node to receive lymphatic drainage from a tumour site should be the first site of lymphatic spread; that "skip metastases" do not occur; and that the absence of tumour metastases in the sentinel node implies the absence of lymph node metastases in the entire lymphatic basin. This concept was first described in penile carcinoma in 197723 and was later studied in patients with cutaneous melanoma.24 Previous detailed pathological studies of axillary nodes in women with breast cancer have demonstrated a skip metastasis rate of less than 5%.25,26Our results confirm that the status of the sentinel lymph node(s) predicts the overall axillary lymph node status with a high degree of accuracy, and can thus be used to limit the morbidity associated with axillary surgery. More importantly, the predictive value of a tumour-free sentinel node was 97%. As such, women identified with a sentinel node free of metastatic tumour can be reassured that further axillary lymph node involvement is highly unlikely. Other studies of sentinel node biopsy in breast cancer (using blue dye and radioactive isotope techniques) have shown sentinel node status to accurately determine axillary lymph node status in more than 95% of women.14-19 We still need to deal with the problem that 3% of patients exhibited tumour-positive axillary nodes when the biopsied sentinel node was negative. The optimal method of pathological assessment of the sentinel node remains unresolved and was not addressed in our study. This issue was discussed at the Adelaide Workshop on Sentinel Node Biopsy in Breast Cancer27 and is the subject of further studies by one of us (G F). Giuliano et al28 have found that immunohistochemical studies of sentinel nodes showed micrometastases in an additional 11% of women whose sentinel node was tumour negative on light microscopy. However, similar assessment of two women with false negative results in our study did not reveal metastases. The implications of micrometastases detected by sensitive immunohistochemical and polymerase chain reaction (PCR) techniques for multidisciplinary care are unknown. They are currently being investigated in trials in the United States (Merrick Ross, Associate Professor of Surgical Oncology, M D Anderson Hospital, Texas, USA, personal communication). Until the answers to this question are available, a large UK trial (ALMANAC) is assessing sentinel node status by conventional microscopy (R Mansell, Professor of Surgery, Cardiff University, UK, personal communication), as this is the current method on which treatment planning is based. These uncertainties emphasise the need for Australian studies to incorporate detailed protocols for pathology assessment of the sentinel node. The prognostic implications of a false negative sentinel node are uncertain, but should be compared with the considerable physical morbidity associated with axillary dissection in lymph node negative women. There is a definite error rate in routine pathological assessment of axillary dissection specimens which may underestimate metastatic disease by 11%-30%,27,29 while unselective sampling of the axilla fails to remove involved nodes in many women.11 The false negative rate must ultimately be minimised by maximal detection of the sentinel node by scintigraphy, careful operative technique and optimal pathological assessment, which requires an experienced multidisciplinary team. The concomitant intraoperative use of both blue dye and radionuclide methods for lymphatic mapping was particularly useful for sentinel node biopsy. Preoperative lymphoscintigraphy permits identification of the sentinel node and subsequent planning of the site of skin incision. Several radiolabelled colloids are currently in use around the world, but the recent workshop in Adelaide27 identified antimony colloids as having excellent properties for lymphoscintigraphy. This is the only agent available for this purpose in Australia and is able to visualise sentinel nodes in the internal mammary chain as well as in the axillary node group. The blue dye technique facilitated visualisation of the sentinel node at the time of surgery and was supplemented by the use of an intraoperative gamma probe. In all patients in whom both blue dye and radionuclide were used, the blue node corresponded to the "hot" node previously identified on lymphoscintigraphy and identified intraoperatively with the hand-held gamma probe. Furthermore, the identification of a sentinel node at preoperative lymphoscintigraphy was the only factor significantly associated with the intraoperative identification of the sentinel node. Lymphoscintigraphy also demonstrates the number and location of potential sentinel nodes requiring biopsy. The initial rate of preoperative identification of the sentinel node by lymphoscintigraphy in our series was lower than that in published reports. However, this was overcome by increasing the volume of the isotope injection and presumably increasing tissue oncotic pressure, lymphatic uptake and drainage. The importance of isotope volume in achieving successful scintigraphic identification of the sentinel node has also been suggested by others.30 Sentinel lymph node mapping and biopsy are likely to be incorporated into clinical practice, provided they can be successfully performed in most patients, and it can be shown that women with negative sentinel nodes who undergo no further treatment to the axilla are not adversely compromised in terms of disease-free and overall survival. This will be best established by randomised controlled studies comparing sentinel node biopsy with standard axillary surgical management. In addition, these studies should address the implied assumption of lower short and long term morbidity associated with this procedure, the optimal methods of pathological assessment, and allow analysis and comparison with clinicopathological variables in predicting sentinel node status. Studies are currently being undertaken in Europe, the United Kingdom and the United States and it is hoped that Australian women can soon participate in similar trials in Australia. References Carter CL, Allen C, Henson DE. Relation of tumour size, lymph nodes status and survival in 24,740 breast cancer cases. Cancer 1989; 63: 181-187. Fisher ER, Anderson S, Redmond C, Fisher B. Pathologic findings from the National Surgical Adjuvant Breast Project Protocol B-06: 10 year pathological and clinical prognostic discriminants. Cancer 1993; 71: 2507-2514. Fisher D, Woolmark N, Bauer M, et al. The accuracy of clinical nodes staging and of limited axillary dissection as a determinant of histological nodal status in carcinoma of the breast. Surg Gynecol Obstet 1991; 152: 765-772. Axellsson CK, Mouridsen HT, Zedeler K. Axillary dissection of Level I and II lymph nodes is important in breast cancer classification: The Danish Breast Cancer Cooperative Group (DBCG). Eur J Cancer 1992; 28: 1415-1418. Kissin MW, Querci-Della-Rovere G, Easton D, Westbury G. Risk of lymphoedema following the treatment of breast cancer. Br J Surg 1986; 73: 580-584. Aitken RJ, Gayes MN, Rodger A, et al. Arm morbidity within a trial of mastectomy and either node sample with selective radiotherapy or axillary clearance. Br J Surg 1989; 76: 568-571. Larson D, Weinstein M, Goldburg I, et al. Oedema of the arm as a function of the extent of axillary surgery in patients with Stage 1-2 carcinoma of the breast treated with primary radiotherapy. Int J Radiat Oncol Biol Phys 1986; 12: 1575-1582. Liljegren G, Holmburg L. Arm morbidity after sector resection and axillary dissection with or without postoperative radiotherapy in breast cancer. Stage 1: Results from a randomised trial. Uppsala Orebro Breast Cancer Study Group. Eur J Cancer 1997; 33: 193-199. Steel RJC, Forrest APM, Gibson T, et al. The efficacy of lower axillary sampling in obtaining lymph node status in breast cancer: a controlled randomised trial. Br J Surg 1985; 72: 368-369. Dixon JM, Dillon P, Anderson TJ, Chetty U. Axillary node sampling in breast cancer: an assessment of its efficacy. Breast 1998; 7: 206-208. Kissin MW, Thompson PH, Price AB, et al. The inadequacy of axillary sampling in breast cancer. Lancet 1982; 1: 1210-1212. Tabar L, Fagerberg G, Duffy SW, et al. Update of the Swedish two-county program of mammographic screening for breast cancer. Radiol Clin North Am 1992; 30: 187-210. Cady B, Stone MD, Schuler JG, et al. The new era in breast cancer: invasion, size and lymph node involvement dramatically decreased as a result of mammographic screening. Arch Surg 1996; 131: 301-308. Giuliano AE, Kirgan DM, Guenther JM, Morton DL. Lymphatic mapping and sentinel lymphadenectomy in breast cancer. Ann Surg 1994; 220: 391-401. Albertini JJ, Lyman GH, Cox C, et al. Lymphatic mapping and sentinel node biopsy in the patient with breast cancer. JAMA 1996; 276: 1818-1822. Veronesi U, Paganelli G, Galimberti V, et al. Sentinel node biopsy to avoid axillary dissection in breast cancer with clinically negative lymph nodes. Lancet 1997; 349: 1864-1867. Borgstein PJ, Pijpers R, Comans EF, et al. Sentinel lymph node biopsy in breast cancer: guidelines and pitfalls of lymphoscintigraphy and gamma probe detection. J Am Coll Surg 1998; 186: 275-283. Cox CE, Pendas S, Cox JM, et al. Guidelines for sentinel node biopsy and lymphatic mapping of patients with breast cancer. Ann Surg 1998; 227: 645-653. O'Hea BJ, Hill ADK, El-Shirbiny AM, et al. Sentinel lymph node biopsy in breast cancer: initial experience at Memorial Sloan-Kettering Cancer Center. J Am Coll Surg 1998; 186: 423-427. Elston CW, Ellis IO. Pathological prognostic factors in breast cancer. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology 1991; 19: 403-410. Pinder SE, Ellis IO, Galea M, et al. Pathological prognostic factors in breast cancer. Vascular invasion: relationship with recurrence and survival in a large study with long-term follow-up. Histopathology 1994; 24: 41-47. Fliess JL. Statistical methods for rates and proportions. 2nd edition. New York, NY: John Wiley and Sons, 1981. Cabanas RM. An approach for the treatment of penile carcinoma. Cancer 1977; 39: 456-466. Morton DL, Wen D-R, Wong JH, et al. Technical details of intraoperative lymphatic mapping for early stage melanoma. Arch Surg 1992; 127: 392-399. Berg JW. The significance of axillary node levels in the study of breast cancer. Cancer 1955; 8: 776-778. Veronesi U, Rilke F, Luimi A, et al. Distribution of axillary node metastases by level of invasion: an analysis of 539 cases. Cancer 1987; 59: 682-687. Kollias J, Gill PG, Chatterton B, et al. Sentinel node biopsy in breast cancer: recommendations for surgeons, pathologists, nuclear physicians and radiologists in Australia and New Zealand. Aust N Z J Surg 1999. In press. Giuliano AE, Dale PS, Turner RR, et al. Improved axillary staging of breast cancer with sentinel lymphadenectomy. Ann Surg 1995; 222: 387-399. Hainsworth PJ, Tjandra JJ, Stillwell RG, et al. Detection and significance of occult metastases in node negative breast cancer. Br J Surg 1993; 80: 459-463. Krag DN, Ashikaga T, Harlow SH, Weaver DL. Development of sentinel node targeting technique in breast cancer patients. Breast J 1998; 4: 67-74. (Received 22 Apr, accepted 9 Sep, 1999) Authors' details Royal Adelaide Hospital and Women's Health Centre, Adelaide, SA. James Kollias, MB BS, FRACS, Staff Surgeon, Breast-Endocrine and Surgical Oncology Unit. P Grantley Gill, FRACS, MD, Head, Breast-Endocrine and Surgical Oncology Unit; and Associate Professor, University of Adelaide. Barry E Chatterton, MB BS, FRACP, Director, Department of Nuclear Medicine. Vivian E Hall, MB BS, FRACR, Radiologist, Department of Radiology. Melissa A Bochner, MB BS, FRACS, Senior Registrar, Breast-Endocrine and Surgical Oncology Unit. Brendon J Coventry, FRACS, PhD, Senior Surgeon, Breast-Endocrine and Surgical Oncology Unit; and Senior Lecturer, University of Adelaide. Department of Tissue Pathology, Institute of Medical and Veterinary Science, Adelaide, SA. Gelareh Farshid, MB BS, FRCPA, Senior Lecturer, University of Adelaide. Reprints will not be available from the authors. Correspondence: Associate Professor P G Gill, Breast-Endocrine Surgical Oncology Unit, Royal Adelaide Hospital, North Terrace, Adelaide, SA 5000. cbatesbrownswordATmedicine.adelaide.edu.au Back to textBack to textBack to textBack to text 3: Clinical and histological features predicting success in sentinel node identification at operationVariableNo. of womenSentinel node identified (%)χ2 (P)Age (years)< 503330 (91%)2.84> 508465 (77%)(0.09)Tumour site (quadrant)Upper/outer86 69 (80%)0.2Lower/inner31 26 (84%)(0.66)Tumour detectionScreening56 42 (75%)2.7Symptomatic61 53 (87%)(0.1)Previous core biopsyYes1210 (83%)0.04No10585 (79%)(0.84)Previous open biopsyYes11089 (81%)0.1No76 (86%)(0.75)Scintiscan resultPositive74 71 (96%)28.7Negative43 24 (56%)(< 0.001)OperationMastectomy31 24 (77%)1.23Wide local excision5547 (85%)(0.54)Localised wide local excision3124 (77%)Tumour size*< 2cm79 64 (81%)0.03≥ 2cm36 29 (81%)(0.95)Tumour grade*12721 (78%)2.425346 (87%)(0.31)33526 (74%)Lymphatic/vascular invasionNegative101 83 (82%)0.44Positive16 12 (75%)(0.5)Lymph node statusNegative80 64 (80%)0.2Positive37 31 (84%)(0.6) * Excludes two cases of ductal carcinoma-in-situ, diagnosed after excision. 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James Kollias · Barry E Chatterton · Vivian E Hall · Melissa A Bochner · Brendon J Coventry · Gelareh Farshid

Editorial Nurses in Australia: their role today and tomorrow The old stereotypes are long gone and the new nurse is developing swiftly MJA 1996; 164: 520-521 May 12 is International Nurses' Day, in tribute to nurses and the role they play in delivering health care. In Australia, the nature of this role has changed significantly over the past three decades. The momentum for this change has come in response to forces from both within and without the profession: the women's movement of the 1970s dramatically altered expectations of work for this once almost totally female workforce;1 in the 1980s, tertiary education was introduced; and in the 1990s, nursing has not escaped the impact of deregulation of the labour market, multiskilling and the drive towards greater efficiency and productivity in the face of economic pressures. Impact of tertiary education Newly qualified nurses are now the product of a liberal education, quite different from the hospital-based education of the past. Indeed, all nurses have embraced the tertiary opportunities that the transfer of nurse education has provided. The demand for places to convert certificate or diploma qualifications to degrees remains strong in the 34 universities with faculties or schools of nursing in Australia.2 So, too, does the demand for places for graduate diplomas and higher degrees; about half the schools of nursing offer doctoral programs3 and the number of nurses who have gained doctorates is increasing. This has in turn led to the creation of more chairs of clinical nursing (18 as of March 1996, with more pending [Professor S McKinley, Secretary to the Australian Professors of Clinical Nursing Association, personal communication]). As well as providing education, universities have promoted and stimulated research that is contributing to the developing knowledge base for nursing practice. This work, together with hospital-based research and that of newly established nursing research centres, is crucial to the evolution of the nurse's role and to the provision of evidence-based care unique to nursing. In fact, increased scientific knowledge and resulting new technologies and treatment methods are increasing the complexity of nursing practice. And in the constant interplay between education and research, education to maintain and develop new practical skills has become a critical necessity. Other influences Influences apart from those of education and research have led to further developments in the role of nurses. At times, blurred boundaries with the roles of other health workers have resulted, with accompanying dilemmas. For example, economic forces have led to the increasing employment of less skilled workers who have taken on some of the work of nurses, mostly outside the regulatory framework that governs nurses -- grave questions about accountability and duty of care need to be answered. For example, to whom and for what are personal care attendants, with no knowledge of drugs, accountable in administering prescribed medications without supervision? Indeed, the general decline in resources and the restructuring of service delivery systems will continue to impact on the role of nurses. Advancing technology is also associated with yet-to-be-resolved legal and ethical dilemmas in the role of nurses (as for all health practitioners) -- dilemmas, such as euthanasia and assisted suicide, that are no longer remote but immediate and omnipresent. Expanding roles The expansion of the nurse's role is challenging the existing statutory limitations on nursing practice. For example, nurses in intensive care units are at the cutting edge of technological innovation and often undertake activities once thought to be the sole province of medical practitioners.4 Nurses in remote areas have long been expected to act outside the boundaries of the nurse's role and have articulated the case for an expanded role (e.g., the right to prescribe some medications or to order pathological tests).5,6 Further, nurses in women's health services in most States and Territories find the absence of such rights (including also the right to refer clients to specialist services) prevents delivery of optimal patient care.7 A review of existing nursing roles with new and expanded boundaries is almost complete in New South Wales.8 The Nurse Practitioner Review, sponsored by the New South Wales Health Department, started in November 1993 and has included 10 pilot projects to evaluate three models of nursing roles with expanded responsibilities: Nurse Practitioner Remote Area, Nurse Practitioner General Practice and Nurse Practitioner Area and District Health. Within the context of each practice, extra responsibilities include ordering diagnostic procedures, prescribing and receiving or making referrals. The scope that the nurse practitioner role offers for advanced practice in nursing is a major attraction for nurses. And, given the developments in their preparation and the growth of nursing knowledge, it is a role that nurses are ready to fulfil. Within the wider context of all health care professions, nurses wish to work collaboratively, as team members, and to be consulted about their views on people's health care needs. They wish to be acknowledged for the contribution they make to patient recovery and to maintaining people's health and for the care and support they give to the dying; nurses are arguably the health professionals most intimate with people's lives and they recognise their resulting position of privilege and trust. And, in the challenging climate of change continually impacting on so many aspects of the nursing role, at least one aspect will persist: nurses will continue to support the values of caring and comfort that have always underpinned their practice. Elizabeth C Percival Executive Director, Royal College of Nursing, Canberra, ACT Helen M Hamilton Project Officer, Royal College of Nursing, Canberra, ACT Beaumont M. The professional role of a national nursing organisation. In: Gray G, Pratt R, editors. Issues in Australian nursing 2. Melbourne: Churchill Livingstone, 1989; 247-261. Report of the national review of nurse education in the higher education sector: 1994 and beyond. Canberra: AGPS, 1994: 143. Royal College of Nursing, Australia. Directory of higher education nursing courses. Sydney: New Hobson Press, 1996. Bucknall T, Thomas S. Clinical decision making in critical care. Aust J Adv Nurs 1995; 13 (2): 10-17. Kreger A. Remote area nursing practice: a quest for education. Report to the Council of Remote Area Nurses Inc. CRANA, 1991: 57-60. Buckley P, Gray G. Across the spinifex: registered nurses working in rural and remote South Australia. Adelaide: School of Nursing, Flinders University, 1993: 143. New South Wales Health Department. Role and function of nurse practitioners in New South Wales. Discussion paper. Sydney: NSW Health, 1992: 7, 13-17. (NSW State Health Publication No. [NB] 93-120.) New South Wales Health Department. Nurse Practitioner Review Stage 2. Vol 2. Sydney: NSW Health, 1993. A1/1-A5/1-20. (NSW State Health Publication No. [NB] 93-120.) ©MJA 1999 © 1999 Medical Journal of Australia.

Elizabeth C Percival · Helen M Hamilton

Healthcare Hepatitis C: an economic evaluation of extended treatment with interferon Alan Shiell, Sue Brown and Geoff C Farrell MJA 1999; 171: 189-193 Abstract - Introduction - Methods - Results - Discussion - References - Authors' details Abstract Objectives: To re-evaluate the cost effectiveness of treating hepatitis C virus (HCV) infection with interferon alfa (IFα) in Australia, taking into account changes in clinical practice. Design: A decision-analytic method (Markov model) was used to simulate the costs and effects of 6 months and 12 months of treatment with IFα versus no treatment (conventional management). Both costs and effects were modelled over 30 years. Data sources: Published meta-analysis of the effectiveness of treatment, professional judgement about treatment protocols, scheduled medical fees, diagnosis-related costs for hospital admission, and a literature search for quality-of-life weights. Patients: A hypothetical cohort of 1000 patients with chronic HCV infection aged 40 years at the start of treatment. Main outcome measures: Incremental costs per life-year gained and per quality-adjusted life-year (QALY) gained. Results: Compared with no treatment, IFα treatment for 6 months results in an extra 94.2 life-years or 320.1 QALYs at an extra cost of $1.8 million (after discounting at 3%) in a cohort of 1000 patients. Discounted cost per life-year gained is $19 110, which is about a quarter of the cost reported in 1994. The discounted cost per QALY gained is $5625. Extended treatment for another 6 months results in an additional 89.0 life-years saved or 170.8 QALYs gained at an incremental discounted cost of $15 835 per life-year gained and $8250 per QALY gained. Conclusions: The cost effectiveness of IFα treatment for HCV infection has improved as a result of better patient selection, cost reductions and enhanced effectiveness of extended treatment. The results are sensitive to assumptions made about quality of life and the discount rate. Introduction Infection with the hepatitis C virus (HCV) is an important public health problem in Australia. It is estimated that there are at least 100 000 people carrying the virus and that up to 10 000 new cases are diagnosed each year.1 As many as 85% of those with acute HCV infection will develop chronic infection, and, of these, a significant proportion will develop cirrhosis and hepatocellular carcinoma (HCC). The only approved treatment for chronic HCV infection, interferon alfa (IFα), is expensive, has significant adverse effects and is effective in only 10%-35% of patients. The cost effectiveness of treatment is uncertain. Decision-analytic techniques have been used to simulate the expected costs and effects of treatment, and several economic evaluations of IFα have been published.2-7 The only Australian study (published in 1994)3 estimated the cost per life-year gained by treatment with IFα to be $33 000 in patients with cirrhosis at the start of treatment and $71 000 for patients without cirrhosis. These figures are substantially higher than those reported elsewhere, reflecting a more cautious view of the long term effectiveness of IFα and the exclusion of the broader benefits of therapy, such as its assumed effects on employment and production capacity. The impact that IFα has on the natural history of HCV infection is now better known. Treatment is discontinued in patients who fail to show a response after 12 weeks, with no reduction in effectiveness but with substantial cost savings. Further, several studies have shown benefits of extended treatment over 12 months rather than 6 months, and this has become the recommended treatment period in most countries including Australia. The effect that this has on cost effectiveness is not clear, as both costs and benefits are likely to increase. Our aim is to update our previous estimate of the cost effectiveness of IFα in the treatment of chronic HCV infection.3 Under section 100 of the Health Act 1953 (Cwlth) (Highly Specialised Drugs Program), subsidised treatment is restricted to patients with no signs of cirrhosis at start of treatment and we have restricted our analysis to such patients. Methods The costs and effects of IFα treatment were simulated by a decision-analytic method (the Markov model) in a hypothetical cohort of 1000 patients with chronic HCV infection aged 40 years at start of treatment (the mean age at diagnosis is 42 years). Both costs and effects were modelled over 30 years. The cost effectiveness of treatment with IFα over 6 months versus no treatment (ie, conventional management only) was re-evaluated, incorporating changes in clinical practice, treatment costs and the price of IFα. The incremental costs and effects of moving from 6 months to 12 months' treatment were then estimated. The software used was Microsoft Excel 97. The assumptions and methods for the decision analytic technique are shown in the Box. Results The net cost of 6 months' treatment with IFα for chronic HCV infection (ie, the cost of treatment minus the cost of conventional management of the disease) was estimated to be $1800 per patient after discounting at 3%. Treatment with IFα results in an extra 94.2 discounted life-years saved or 320.1 additional (discounted) QALYs (Table 2). The incremental cost per life-year saved was $19 110, which is about a quarter of the cost reported in our previous study.3 The incremental cost per QALY gained was $5625. Extending treatment from 6 to 12 months results in an additional 89.0 discounted life-years gained or 170.8 discounted QALYs at incremental costs of $15 835 per life-year gained and $8250 per QALY gained. Average cost per unit of outcome increases as the duration of the model is reduced. As duration of the model acts as a proxy for age at the start of treatment, this finding suggests that treatment is less cost effective in older age groups. The sensitivity analysis (Table 3) suggests that the results for 6 months' treatment are robust with respect to assumptions made about rates of disease progression, the long term effectiveness of IFα, the price of IFα and the exclusion of patients not responding after 12 weeks. The most important variables are the choice of discount rate and the adjustment for quality of life (Table 3). Relatively minor adjustments to the quality-of-life weight for treatment have a large effect on cost per QALY gained. In the extreme, the adverse effects of treatment offset any gains in quality of life brought about by disease resolution. The effect of 12 months' treatment over 6 months' treatment is also sensitive to changes in the discount rate and the duration of the model and, in addition, is more sensitive to assumptions made about disease progression and treatment effectiveness. Discussion Our results suggest that the cost per life-year gained from 6 months' treatment with IFα is lower than when it was first evaluated in an Australian context in 1994.3 This change is attributable to three main factors: a reduction in the cost of treating people with IFα; a reduction in the price of IFα itself; and cessation of treatment at 12 weeks in those who fail to show a reduction in serum alanine aminotransferase levels. The latter has been clinical policy in Australia since IFα was first listed for public subsidy in 1994, but our initial evaluation preceded this.3Quality adjustment of the outcomes also has a substantial effect on the cost-effectiveness ratios, suggesting that the major impact of IFα treatment is on improving quality of life rather than increasing life expectancy through the prevention of cirrhosis. There is also the relief offered to those in whom the infection is resolved. However, the sensitivity of the results to changing assumptions about the effect of the disease and its treatment on quality of life reinforces the need for further research into the subjective impact of HCV infection. Only one other study has considered the cost effectiveness of 12 months' versus 6 months' therapy.7 Consistent with our results, it concluded that treatment over 12 months may be cost effective, except in patients older than 60 years of age. The cost-effectiveness ratios reported here compare favourably with many other public health interventions, such as screening for breast and cervical cancer.20,21 However, there are problems in comparing the results of economic evaluations, particularly when different methods have been used.22 Furthermore, if the benefits of extended treatment with IFα are to be realised within a limited healthcare budget, then some other program or activity must be dropped or reduced in scale to accommodate the increase in expenditure. Thus, before drawing conclusions about cost effectiveness, one should compare the benefits of IFα treatment with the benefits of the other program or activity affected.23 See Box for summary points. Caution is especially warranted when, as in this case, a decision-analytic model has been employed, as it is often difficult to assess the validity of the assumptions made. The protracted nature of HCV infection, however, makes it difficult to assess the cost effectiveness of treatment by another means.24,25 Decisions on when and how to use IFα have to be made with available data. However, our comprehensive sensitivity analysis showed that, for most of the assumptions made, the results appear to be robust. The exceptions are the two subjective variables -- the utility attached to different disease endpoints and the rate at which future costs and benefits are discounted. HCV infection is not the benign disease it was once believed to be, but little is known about the impact it has on people's lives or the lengths to which they might go for relief. Our results are particularly sensitive to assumptions made about the relative effect of living with chronic infection, and its associated risks of long term sequelae versus the known risks and the uncertain effectiveness of treatment. Individual attitudes to risk and time preference will affect the perceived cost effectiveness of treatment. Further research is needed to examine the personal and social impact of HCV infection and the utility of its treatment.26 References Australian Health Ministers' Advisory Council. National Hepatitis C Action Plan, October 1994. Canberra; AGPS, 1994. 2. Garcia de Ancos JL, Roberts JA, Dusheiko GM. An economic evaluation of the costs of a-interferon treatment for chronic active hepatitis due to hepatitis B or C virus. J Hepatol 1990; 11: S11-S18. Shiell A, Briggs A, Farrell G. The cost-effectiveness of alpha interferon in the treatment of chronic active hepatitis C. Med J Aust 1994; 160: 268-272. Dusheiko GM, Roberts JA. Treatment of chronic type B and C hepatitis with interferon alfa: an economic appraisal. Hepatology 1995; 22: 1863-1873. Joliet E, Vanlemmens C, Kerleau M, et al. Cost-effectiveness analysis of the treatment of chronic hepatitis C. Gastroenterol Clin Biol 1997; 21: 336-338. Bennet WG, Inoue Y, Beck R, et al. Estimates of the cost-effectiveness of a single course of interferon-a 2b in patients with histologically mild hepatitis C. Ann Intern Med 1997; 127: 855-865. Kim WR, Poterucha JJ, Hermans JE, et al. Cost-effectiveness of 6 and 12 months of interferon-a therapy for chronic hepatitis C. Ann Intern Med 1997; 127: 866-874. National Institutes of Health Consensus Development Panel statement: management of hepatitis C. Hepatology 1997; 26(3 Suppl 1): 2S-10S. Fattovitch G, Giustina G, Degos F, et al. Morbidity and mortality in compensated cirrhosis type C: a retrospective follow-up study of 384 patients. Gastroenterology 1997; 112: 463-472. Australian Bureau of Statistics. Deaths: Australia 1994. Canberra: ABS, 1994. (Catalogue No. 3302.0.) Poynard T, Leroy V, Cohard M, et al. Meta-analysis of interferon randomized trials in the treatment of viral hepatitis C: effects of dose and duration. Hepatology 1996; 24: 778-789. Carithers RL Jr, Sugano D, Bayliss M. Health assessment for chronic HCV infection: results of quality of life. Dig Dis Sci 1996; 41: 75S-80S. Davis GL, Balart LA, Schiff ER, et al. Assessing health-related quality of life in chronic hepatitis C using the Sickness Impact Profile. Clin Ther 1994; 16: 334-343. Foster GR, Goldin RD, Thomas HC. Chronic hepatitis C virus infection causes a significant reduction in quality of life in the absence of cirrhosis. Hepatology 1998; 27: 209-212. National Health and Medical Research Council. A strategy for the detection and management of hepatitis C in Australia. Canberra: NHMRC/AGPS, 1997. Commonwealth Department of Health and Family Services. Medical Benefits Schedule. Nov 1996. Canberra; AGPS, 1996. Commonwealth Department of Health, Housing, Local Government and Community Services. Manual of Resource Items and their Associated Costs. Canberra: AGPS, November 1993. Drummond MF, Brandt A, Luce B, Rovira J. Standardising methodologies for economic evaluation in health care. Int J Technol Assess Health Care 1993; 9: 26-36. Gold MR, Siegel JE, Russell LB, Weinstein MC, editors. Cost-effectiveness in health and medicine. New York: Oxford University Press, 1996: 230. AHMAC Breast Cancer Screening Evaluation Committee. Breast screening in Australia: future directions. Canberra: Australian Institute of Health and Welfare, 1990. AHMAC Cervical Cancer Screening Evaluation Committee. Cervical Screening in Australia: options for change. Canberra: Australian Institute of Health and Welfare, 1991. Salkeld G, Davey PD, Arnolda G. A critical review of health-related economic evaluations in Australia: implications for health policy. Health Policy 1995; 31: 111-125. Birch S, Donaldson C. Cost-benefit analysis: dealing with the problems of indivisible projects and fixed budgets. Health Policy 1987; 7: 61-72. Bennet WG, Pauker SG, Davis GL, Wong JB. Modeling therapeutic benefit in the midst of uncertainty: therapy for hepatitis C. Dig Dis Sci 1996; 41: 56S-62S. Koff RS, Seeff LB. Economic modeling of treatment of chronic hepatitis B and chronic hepatitis C: promises and limitations. Hepatology 1995; 22: 1880-1885. Owens DK. In the eye of the beholder: assessment of health-related quality of life. Hepatology 1998; 27: 292-293. (Received 20 Nov 1998, accepted 3 May 1999) Authors' details Social and Public Health Economics Research Group (SPHERe), Department of Public Health and Community Medicine, University of Sydney, Sydney, NSW. Alan Shiell, MSc(Econ), Honorary Research Associate. Medical Benefits Fund of Australia, Sydney, NSW. Sue Brown, MPH, BPharm, Pharmacy Manager, Provider Relations. Department of Medicine, Westmead Hospital, University of Sydney, NSW. Geoff C Farrell, MD, FRACP, Storr Professor of Medicine. Reprints will not be available from the authors. Correspondence: Mr A Shiell, Social and Public Health Economics Research Group (SPHERe), Department of Public Health and Community Medicine, University of Sydney (A27), NSW 2006. Email: alansATpub.health.usyd.edu.au Assumptions and methods for the decision analytic technique Natural history of hepatitis C (HCV) Chronic HCV infection to cirrhosis: The rate of progression was assumed to be 20% at 20 years,8 consistent with experience in patients attending liver clinics, but is higher than in a community sample. Cirrhosis to hepatocellular carcinoma (HCC): Rates of progression range from 1% to 4% per year and are higher in older age groups.8 We have assumed an annual rate of 1.4% (14% over 10 years), which is the lowest rate from more than 10 published studies from Europe and Japan.9 The small chance of HCC developing in patients without cirrhosis (< 0.25% per year)8 was ignored. Cirrhosis to advanced liver failure: We assumed that 20% of the cohort would progress to advanced liver failure over 10 years from the onset of cirrhosis.8 Death: All patients developing HCC or advanced liver failure were assumed to die within 2 years of diagnosis. Deaths from other causes were estimated from Australian life tables.10 Effectiveness of IFα treatment Previous evaluation: In our previous evaluation,3 we assumed that 6 months' treatment with IFα would be effective in 20% of cases overall and 26% of cases without cirrhosis at the start of treatment. A recent meta-analysis by Poynard et al11 suggests that a sustained response is achieved in 14%-22% of cases treated with 3 million international units (miu) of IFα over 6 months, and in 28%-38% of patients treated with the same dose for 12 months or longer. Our estimates of the effectiveness of treatment were based on the assumption of an 18% sustained response rate after IFα treatment for 6 months and a 35% sustained response rate after 12 months' treatment, with both rates subject to sensitivity analysis. Quality of life Chronic HCV infection has been described as largely asymptomatic, with less than 20% of patients developing non-specific symptoms such as fatigue.8 However, recent studies suggest that it has an impact on quality of life.12-14 People with chronic HCV infection scored significantly lower than a comparable but healthy population on various generic health measures, such as the 36-item short-form health survey (SF-36).12 Side effects of treatment: Mild side effects of IFα are common and most patients will experience flu-like symptoms which diminish over time. Less transient effects -- fatigue, irritability, depression, thyroid disease and skin disorders -- are more troublesome and cause some patients to discontinue treatment. Less than 2% of patients will experience severe side effects.8 Quality-adjusted life-years (QALYs): The impact of the disease (including its sequelae and treatment with IFα) on quality of life can be incorporated into the analysis by weighting the life-years gained according to their quality, thus generating an estimate of quality-adjusted life-years, or QALYs. These weights are usually calibrated on a scale of 0 to 1, where 0 is equivalent to death and 1 to a year of life in full health. Subjective impact of the disease: A major shortcoming is a lack of understanding of the subjective impact of the disease. In the absence of patient-generated weights, other authors have used quality-of-life weights based on clinical judgement or small scale surveys.4,6,7 The weights are 0.8-0.95 for chronic hepatitis, 0.7-0.8 for compensated cirrhosis, 0.28-0.5 for decompensated cirrhosis, and 0.1-0.25 for hepatocellular carcinoma. The weights we used were adapted from those derived by Kim et al,7 as these were the only ones based on patient judgement (Table 1). In the baseline case, it was assumed that treatment had no additional adverse effect on quality of life -- an assumption relaxed in the sensitivity analysis. Costs of treatment Estimates of the treatment costs for each of the main clinical endpoints were based on clinical protocols as specified by the National Health and Medical Research Council (NHMRC)15 and the clinical opinion of one of the authors (G C F). The protocols were costed using the Medicare Benefits Schedule for medical services,16 and Australian national diagnosis-related groups (AN-DRG-3.1) for hospital admissions (Table 1).17 See Appendix for details. All costs are in Australian dollars at 1996 prices. Cirrhosis: A weighted cost was computed on the basis of specified treatment protocols for each of the main clinical manifestations of cirrhosis. The weights reflect the estimated proportion of patients likely to experience each state.6 It was further assumed that 2% of patients experiencing cirrhosis would undergo a liver transplant each year and that 25% of cirrhotic patients would experience at least one episode of septicaemia requiring hospital admission. IFα: The unit cost of IFα reflected its price to the healthcare system. It was assumed that treatment would be given at a rate of 3 miu three times a week for either 24 or 48 weeks and would be discontinued in people who did not show a reduction in serum alanine aminotransferase (ALT) levels after 12 weeks. Experience in Australia suggests that 26% of people will fail to respond in this period and will discontinue treatment (R G Batey, Deputy Dean, and Professor of Gastroenterology, Faculty of Medicine and Health Sciences, University of Newcastle, Newcastle, NSW, personal communication). Other costs: Lost production capacity caused by morbidity and premature mortality associated with HCV infection was not considered.18 Other patient costs, such as the use of community services and alternative medicine, were also omitted. This biases the findings against treatment with IFα. Cost effectiveness of IFα treatment The cost effectiveness of treatment for 6 months is expressed as the additional cost per QALY gained over and above no treatment (conventional management). The incremental cost effectiveness of 12 months' treatment over 6 months' treatment is also reported. Future costs and outcomes were discounted at both 3% and 5% (as recommended by Gold et al19). Undiscounted results are also presented and the effect of using a higher discount rate is assessed in the sensitivity analysis. (Discounting is the process whereby costs and benefits occurring at different points in time are made commensurate with each other.) Sensitivity analysis The robustness of the results was examined by sensitivity analysis (given the uncertainties inherent in the modelling approach). Key variables included in the sensitivity analysis were response rates, rates of disease progression, time to develop sequelae, costs of treatment, percentage of patients excluded at 12 weeks, age groups, the discount rate, and the adjustment for quality of life. Back to text 1: Baseline assumptions: values and costs used in the Markov modelValueRangeDisease transition probabilities From chronic infection to cirrhosis20%10%-30% From cirrhosis to advanced liver failure20%10%-30% From cirrhosis to hepatocellular carcinoma14%7%-21%Effectiveness of treatment Long term response after 6 months18%14%-24% Long term response after 12 months35%26%-38% Discontinue treatment after 12 weeks because of lack of response26%13%-39%Health state (quality of life) weights Chronic infection0.950.80-1.00 Cirrhosis0.750.50-0.90 Advanced liver failure0.250.10-0.40 Hepatocellular carcinoma0.250.10-0.40 Treatment with interferon alfa (IFα)0.950.80-0.95 Resolved infection1.001.00-1.00Treatment episode costs*$$Medical management of chronic infection405200-600Treatment with IFα 6 months' treatment including discontinuing treatment2 8001 975-3 630 12 months' treatment including discontinuing treatment5 1503 620-6 670Cirrhosis (weighted average)2 8251 400-4 200 Management of compensated cirrhosis660330-990 Diuretic-sensitive ascites1 880940-2 820 Refractory ascites13 6406 820-20 460 Variceal haemorrhage (Year 1)5 8502 925-8 775 Hepatic encephalopathy (Year 1) 6 3753 190-9 565 Hepatocellular carcinoma (Year 1)8 8654 435-13 290 Liver transplant (Year 1)92 52546 265-138 790 Septicaemia5 3002 650-7 950Terminal care28 40014 200-42 600Back to text 2: Summary of costs and outcomes of interferon treatment for chronic hepatitis C infection in a hypothetical cohort of 1000 patients Treatment durationNet costs ($)Lives saved Life-years savedQALYs gainedUndiscounted(a) 6 months1 185 55512.0176.3 531.4(b) 12 months2 013 84523.4 342.7830.7(c) Increment828 290 11.3166.5299.3Discounted (3%)(a) 6 months1 800 3807.694.2320.1(b) 12 months3 209 34514.7183.2490.9(c) Increment1 408 9657.189.0170.8Discounted (5%)(a) 6 months2 049 6455.763.9237.7(b) 12 months3 694 02011.1124.2359.5(c) Increment1 644 3755.460.3121.8Treatment DurationCost/life saved ($)Cost/ life-year saved ($)Cost/ QALY gained ($)Undiscounted(a) 6 months98 7106 7202 230(b) 12 months86 2355 875 2 425(c) Increment73 0204 9752 765Discounted (3%)(a) 6 months238 52519 1105 625(b) 12 months218 67017 520 6 540(c) Increment197 64515 835 8 250Discounted (5%)(a) 6 months360 37032 095 8 620(b) 12 months334 02029 750 10 275(c) Increment306 120 27 265 13 505 Incremental cost and outcomes (a) 6 months' treatment with interferon v. no treatment; (b) 12 months' treatment with interferon v. no treatment; (c) 12 months' treatment with interferon v. 6 months' treatment. Net costs = costs of treatment minus costs of conventional management of the disease. QALY = quality-adjusted life-year. Back to text 3: Discounted costs of interferon treatment for chronic hepatitis C infection per life-year and per quality-adjusted life-year (QALY) gained under best and worst case scenarios (sensitivity analysis)Treatment for 6 months v. no treatmentCosts ($) per QALY (Baseline = $5 625)Costs ($) per life-year (Baseline = $19 110)VariableRangeBest caseWorst caseBest caseWorst caseRate of cirrhosis10%-30% 3 2409 6459 20548 820Time to cirrhosis (years)10-304 09010 29011 64537 470Rate of sequelaeComposite*5 1156 26512 95037 590 Liver failure10%-30% Hepatocellular carcinoma7%-21%Time to sequelae (years)5-155 4955 77516 21522 970Long term response rateComposite3 3908 26511 68027 600 6 months14%-24% 12 months26%-38%Cost of interferon per dose$13-$393 0358 12010 31027 595Cost of health service useComposite4 0657 18513 81024 410 Chronic infection50%-150% Cirrhosis50%-150% Terminal care50%-150%Discontinue treatment at 12 weeks13%-33%5 2406 01017 81020 415Duration of model (years)20-404 30512 95012 89049 090Discount rate0-10%2 23018 6206 72589 900Quality-of-life weightsComposite (See Table 1)2 08028 03019 110† 19 110†Treatment for 12 months v. 6 months Costs ($) per QALY (Baseline = $8 250)Costs ($) per life-year (Baseline = $15 835)VariableBest caseWorst caseBest caseWorst caseRate of cirrhosis3 80019 8257 02542 270Time to cirrhosis (years)5 21012 6859 32026 455Rate of sequelae6 98010 16510 76531 040 Liver failure Hepatocellular carcinomaTime to sequelae (years)7 8358 72513 49518 970Long term response rate 4 36063 1758 125214 105 6 months 12 monthsCost of interferon per dose 4 15512 3407 91023 475Cost of health service use 5 48511 01010 53521 135 Chronic infection Cirrhosis Terminal care at 12 weeks 6 8109 58513 07518 595Duration of model (years) 7 20017 3009 75541 910Discount rate2 76533 4754 97578 310Quality-of-life weights 7 5309 81015 835†15 835† * Composite refers to the aggregate effect on cost per unit of outcome of changing all subsidiary variables simultaneously. †Quality adjustment has no effect on the number of life-years saved. Back to text Summary points Costs and benefits of healthcare interventions have to be considered in the context of a limited healthcare budget. The cost effectiveness of interferon alfa (IFα) treatment of chronic hepatitis C infection in Australia has improved since it was first evaluated in 1994. The major effect of IFα therapy is on improving quality of life, not life expectancy. More research is required on the impact of chronic hepatitis C infection and IFα treatment on quality of life. Back to text APPENDIX 1 Treatment episode costs Back to article 1: Medical management of chronic infection Resource categoryNumberUnit costTotal Cost Specialist visits2112.65225.30 Pathology Liver function test219.8039.60 Alfa fetoprotein219.9039.80 Ultrasound1101.70101.70 Total 406.40 2: Treatment with interferon (6 months) including workup Resource categoryNumberUnit costTotal Cost Specialist review initial consultation194.1594.15 subsequent consultation647.15282.90 Interferon (allowing for drop out)0.871889.281643.67 Pathology Full blood count717.20120.40 Liver biopsy1130.35130.35 Liver function test719.80138.60 International normalisation ratio112.4012.40 Thyroid function test341.00123.00 PCR380.00240.00 Anti-HCV113.7013.70 Total2799.17 3: Treatment with interferon (12 months) including workup Resource categoryNumberUnit costTotal Cost Specialist review initial consultation194.1594.15 subsequent consultation1447.15660.10 Interferon (allowing for drop out)0.813 755.253 041.74 Pathology FBC1517.20258.00 Liver biopsy1130.35130.35 LFT1519.80297.00 International normalisation ratio112.4012.40 Thyroid function test441.00164.00 PCR680.00480.00 Anti-HCV113.7013.70 Total5151.44 4: Management of compensated cirrhosis Resource categoryNumberUnit costTotal Cost GP visits424.5098.00 Specialist visits initial1110.75110.75 subsequent355.45166.35 Pathology LFT219.8029.60 AFP419.9079.60 Ultrasound283.95167.90 Total662.20 5: Management of diuretic-sensitive ascites Resource categoryNumberUnit costTotal Cost Inpatient admissions0.331980.00653.40 Day-only admissions1455.00455.00 Specialist review initial visit1110.75110.75 subsequent visit555.45277.25 Pathology LFT419.8079.20 Creatinine417.7571.00 AFP219.9039.80 FBC217.2034.40 Prothrombin time212.4024.80 Medication Aldactone 200 mg/day199.0699.06 Procedures Paracentesis138.2038.20 Total1882.86 6: Management of refractory ascites Resource categoryNumberUnit costTotal Cost Day-only admissions26455.0011 830.00 Specialist review initial visit1110.75110.75 subsequent visit555.45277.25 Pathology LFT419.8079.20 Creatinine417.7571.00 AFP219.9039.80 FBC217.2034.40 Prothrombin time212.4024.80 Medication Norfloxacillin 200 mg/tds0.33545.15179.90 Procedures Paracentesis2638.20993.20 13,640.30 7: Management of variceal haemorrhage - Year 1 Resource categoryNumberUnit costTotal Cost Hospital admission11980.001980.00 Day-only admissions5455.002275.00 Specialist review initial visit1110.75110.75 subsequent visit555.45277.25 Pathology LFT419.8079.20 Creatinine417.7571.00 AFP219.9039.80 FBC217.2034.40 Prothrombin time212.4024.80 Medication Propanolol182.4982.49 Procedures Oesophagoscopy (+ anaesthetic)3291.95875.85 Total5850.40 8: Management of hepatic encephalopathy - Year 1 Resource categoryNumberUnit costTotal Cost Hospital admission2.41980.004752.00 Specialist review initial visit1110.75110.75 subsequent visit555.45277.25 Pathology LFT419.8079.20 Creatinine417.7571.00 AFP219.9039.80 FBC217.2034.40 Prothrombin time212.4024.80 Medication Lactulose 60 mls1734.96734.96 Procedures Diagnostic endoscopy (+ anaesthetic)1213.75213.75 Paracentesis138.2038.20 Total6376.11 9: Management of hepatocellular carcinoma - Year 1 Resource categoryNumberUnit costTotal Cost Hospital admission (diagnosis)16947.006947.00 Inpatient admission17846.907846.90 Specialist visits initial visit1110.75110.75 subsequent visits955.4555.45 Pathology LFT419.8079.20 Creatinine417.7571.00 AFP219.9039.80 FBC217.2034.40 Prothrombin time212.4024.80 Procedures Paracentesis138.2038.20 Total8866.60 10: Other hospital admissions Reason for admission/treatmentRateUnit cost ($) Liver transplant (+ associated admissions)0.0292,527 Major infection (septicaemia)0.255,300 Terminal care - Advanced liver failure28,400 - hepatocellular carcinoma28,400 Back to text

Alan Shiell · Sue Brown · Geoff C Farrell

Editorial The human element of adverse events Is a certain level of error inevitable in healthcare? MJA 1999; 170: 404-405 The Quality in Australian Health Care Study (QAHCS),1 together with the Harvard study on which it was based,2 were groundbreaking studies that for the first time systematically revealed the nature and scale of iatrogenic injury in healthcare. Morbidity due to healthcare appears to be a major public health problem, and it is very unlikely that this problem is confined to Australia and the United States. The QAHCS revealed particularly high levels of adverse events (AEs), in part because it took a broader, quality-of-care approach rather than one focused on negligence and compensation. In this issue of the Journal, review and content analysis of textual summaries of the AEs by Wilson et al, the QAHCS team, have now yielded a deeper understanding of these events.3 The major categories of human error, accounting for over 70% of AEs, were: Failures in technical performance; Failure to decide and/or act on available information; Failure to investigate or consult; and A lack of care or failure to attend. Do the failures identified by the QAHCS team imply carelessness and/or incompetence on the part of healthcare staff? On occasions this may be so, but research on human error paints a more complex picture.4 Tempting though it may be to simply blame the doctors and nurses, identifying a failure in the process of care is usually just the first step in understanding the causes of AEs. This is especially so when the failure occurs not in some routine procedure, but in complex diagnostic or technical tasks, in which the term "error" may be a misleading oversimplification.5 Should we therefore accept that a certain level of error is inevitable in healthcare? We certainly should not accept such high levels of iatrogenic injury, much of which is preventable. In one sense, though, it is necessary to accept error. Before there can be any serious hope of reducing AEs there must first be a recognition of the frequency of error and of imperfect decision-making in healthcare, as is the case in other human activities.6 The next step, as the QAHCS team argues, is to look beyond the immediate failures to their deeper causes.3 Analyses of accidents in medicine and elsewhere have led to a much broader understanding of the causes of AEs, with less focus on individuals and more on pre-existing organisational factors. The conditions which give rise to failures in the process of care can be considered in a broad framework of individual, task, team, work environment and organisational factors.7 A failure to consult, for instance, may be due to overconfidence in a junior member of staff, inexperience, inadequate knowledge, delay in obtaining test results, or the unavailability of senior members of staff. Each of these problems may be specific to that occasion or may reflect more general problems: the attitudes of individual members of staff, the training policies of the hospital, poor supervisory practices, inadequate and haphazard systems of communication or interpersonal problems within a team. The National Taskforce on Quality in Australian Health Care produced a comprehensive, multifaceted plan of action to reduce healthcare injuries and deaths.8 The Taskforce was surely correct to see both the problem and the solution as multidimensional, as the systems approach implies. Safety programs in industries, involving sociotechnical systems with many similarities to medicine, target the tasks, teams and conditions of work, as well as ensuring that staff are highly skilled.4 Safety needs to be addressed both at the level of the particular clinical process and at the interpersonal and organisational levels. Where tasks can be clearly specified, then greater standardisation, clear guidelines and less reliance on the vagaries of human memory and vigilance are essential. Team and communication failures have been strongly implicated in many accident analyses and remedial measures can be straightforward. Systems have also been developed in industry to monitor the conditions of work, as well as the associated organisational factors and decisions that give rise to these conditions. The Taskforce recommendations have been widely supported9 and a number of working groups have been established by Australian health departments. In 1997, a National Expert Advisory Group on Safety and Quality in Australian Health Care was established, and their recommendations will be considered by the Health Ministers later this year. In the 1998 Australian Health Care Agreements, $658 million was allocated for quality improvements within the public health system over five years, and a further $253 million for, among other objectives, improving the integration of public hospital and community services. Welcome though these initiatives are, the pace of change nevertheless seems slow given the stark message of the original QAHCS study four years ago. The findings from QAHCS suggested that each year 50 000 Australians suffer permanent disability and 18 000 die at least in part as a result of their healthcare. Further evidence emerged in 1997 with the publication of AE rates in Victorian hospitals.10 Since then, thousands more Australians have presumably been injured or died through deficiencies in the healthcare system. Furthermore, the QAHCS found that AEs lost Australia over three million bed-days per annum. In its interim report, the National Expert Advisory Group pointed out that the extrapolated potential saving from preventable AEs in 1995-96 would be $4.17 billion.11 AEs also lead to increased disability benefits and time lost off work, which all impact on the Australian economy. Achieving change on the required scale will require a specific commitment from all healthcare providers, administrators and consumers, as well as unequivocal, sustained government support. It is hoped that 1999 will see the necessary consensus for urgent action from all the parties involved and the implementation of specific, carefully evaluated safety initiatives. It would be tragic if the "lack of care and failure to attend" and "failure to decide and act", revealed as causes of AEs, ultimately also applied to those professional and government bodies responsible for programs of prevention. Charles A Vincent Reader in Psychology, Clinical Risk Unit, Department of Psychology University College London, UK Wilson RM, Runciman WB, Gibberd RW, et al. The Quality in Australian Health Care Study. Med J Aust 1995; 163: 458-471. Brennan TA, Leape LL, Laird NM, et al. Incidence of adverse events and negligence in hospitalized patients. N Engl J Med 1991; 324: 370-376. Wilson RMcL, Harrison BT, Gibberd RW, Hamilton JD. An analysis of the causes of adverse events from the Quality in Australian Health Care Study. Med J Aust 1999; 170: 411-415. Reason JT. Understanding adverse events: human factors. In: Vincent CA, editor. Clinical risk management. London: BMJ Publications, 1995. Cook RI, Woods DD, Miller C. A tale of two stories: contrasting views of patient safety. Report of the National Patient Safety Foundation. Chicago: American Medical Association, 1998. Leape LL. Error in medicine. JAMA 1994; 272: 851-857. Vincent CA, Taylor-Adams S, Stanhope N. A framework for the analysis of risk and safety in medicine. BMJ 1998; 316: 1154-1157. The Final Report of the Taskforce on Quality in Australian Health Care. Canberra: AGPS, June 1996. Wilson RM, Harrison BT. Are we committed to improving the safety of health care. Med J Aust 1997; 166: 452-453. O'Hara D, Carson NJ. Reporting of adverse events in hospitals in Victoria 1994-1995. Med J Aust 1997; 166: 460-463. National Expert Advisory Group on Safety and Quality in Australian Health Care. Interim report - Commitment to quality enhancement. July 1998. <http://www.health.gov.au/about/cmo/neag.htm> Journalists are welcome to write news stories based on what they read here, but should acknowledge their source as "an article published on the Internet by The Medical Journal of Australia <http://www.mja.com.au>". <URL: http://www.mja.com.au/> We appreciate your comments.

Charles A Vincent

Research An analysis of the causes of adverse events from the Quality in Australian Health Care Study Ross McL Wilson, Bernadette T Harrison, Robert W Gibberd and John D Hamilton MJA 1999; 170: 411-415 For editorial comment, see Vincent Abstract - Introduction - Methods - Results - Discussion - Acknowledgements - References - Authors' details - - More articles on Administration and health services The Quality in Australian Health Care Study (QAHCS), published in the Journal in 1995,1 reported that 16.6% of hospital admissions were associated with an iatrogenic patient injury, termed an adverse event (AE) (see Box 1). This compares with the rate of 3.7% for AEs in the Harvard Medical Practice Study (HMPS),2 and a rate of 17% in a more recent study with an alternative observational method of determining AEs.3 Fifty per cent of the AEs in the QAHCS were judged to have a high preventability score (4 or more on a scale of 1-6 of increasing likelihood of preventability).1 The disability caused by these adverse events ranged from temporary disability (fully resolved in one month) in 46.6% of AEs, to death in 4.9% of AEs. Although recording AEs emphasises only the "complications" of rather than the benefits derived from healthcare, AEs are of great significance to individual patients as well as to the whole healthcare system. Abstract Objective: To examine the causes of adverse events (AEs) resulting from healthcare to assist in developing strategies to minimise preventable patient injury. Design: Descriptions of the 2353 AEs previously reported by the Quality in Australian Health Care Study (QAHCS) were reviewed. A qualitative approach was used to develop categories for human error and for prevention strategies to minimise these errors. These categories were then used to classify the AEs identified in the QAHCS, and the results were analysed with previously reported preventability and outcome data. Results: 34.6% of the causes of AEs were categorised as "a complication of, or the failure in, the technical performance of an indicated procedure or operation", 15.8% as "the failure to synthesise, decide and/or act on available information", 11.8% as "the failure to request or arrange an investigation, procedure or consultation", and 10.9% as "a lack of care and attention or failure to attend the patient". AEs in which the cause was cognitive failure were associated with higher preventability scores than those involving technical performance. The main prevention strategies identified were "new, better, or better implemented policies or protocols" (23.7% of strategies), "more or better formal quality monitoring or assurance processes" (21.2%), "better education and training" (19.2%), and "more consultation with other specialists or peers" (10.2%). Conclusion: The causes of AEs or errors leading to AEs can be characterised, and human error is a prominent cause. Our study emphasises the need for designing safer systems for care which protect the patient from the inevitability of human error. These systems should provide new policies and protocols and technological support to aid the cognitive activities of clinicians. Introduction An additional analysis of data from the Quality in Australian Health Care Study (QAHCS)1 was undertaken in order to understand more fully the causes of the adverse events (AEs) identified and to assist in developing prevention strategies. Here, we describe the error or errors in the delivery of healthcare which led to the AEs. This contrasts with our previous report,1 which focused on the patient characteristics associated with AEs and the nature and consequences of the AEs. Methods The method of determining AEs in the QAHCS has been described previously.1 The AEs were re-examined with the specific goals of determining the causes for, or the underlying errors leading to, each AE. In addition, strategies that were judged to have the potential to prevent AEs were recorded. To obtain this information the first and subsequent review forms (RF1 and RF2 forms1) collected during the QAHCS were re-examined. The source material for these forms had been the hospital medical records, but neither the hospitals nor the medical records were revisited in this analysis. Categories for the causes of the AEs were devised by an iterative process during a three-day workshop. For this, we sought additional expertise in clinical epidemiology and qualitative research methods. Using these categories, the AEs recorded on the review forms were assessed by three of the senior medical specialists who had originally reviewed the medical records in the QAHCS. All the material from each AE was reviewed by only one reviewer, as the agreement between the medical reviewers in determining the presence or absence of an AE during the QAHCS was 80% (kappa, 0.55). A proforma was completed which asked the reviewer to identify the error and then classify it by human cause and preventive strategy. All AEs were also categorised into some of the processes of clinical care. Results for the "delay", "treatment" and "investigation" categories are presented. The categories were not mutually exclusive. These data were then entered into a database, merged with the original data from the QAHCS for each case and analysed. Two of the original total of 2353 AEs were missed in this review; thus, results are given for 2351 AEs. Our analysis provides the frequency of occurrence of each of the categories of causes of AEs, together with the proportion in each category resulting in permanent disability (including death) and the proportion with high preventability. Results Human error categories Box 2 shows the frequency of occurrence of each of the human error categories, and the proportion of the AEs in each category judged to have permanent disability and high preventability. Of the 2351 AEs, 1922 (81.8%) were associated with one or more human error categories. As the error categories were not mutually exclusive, the 1922 AEs were associated with 2940 causes. "Complication of, or failure in, the technical performance of an indicated procedure/operation" was the most frequent cause of AEs; examples of this category are shown in Box 3A. Human errors associated with categories of failure of cognitive function were the next most frequent cause of AEs (Box 2). These included "Failure to synthesise, decide and/or act on available information", "Failure to request or arrange investigation, procedure or consultation", and "Misapplication of, or failure to apply, a rule; or use of a bad or inadequate rule". The most frequent error category, "complication of, or failure in, the technical performance of an indicated procedure/operation", had a lower proportion of AEs with permanent disability (14.2%). The next five most frequent human error categories all had a high proportion of AEs with permanent disability (25% or more) (Box 2). This pattern was also seen in the proportions of AEs with death as the outcome: 2.2% in the first category, and 8% or more in each of the next five categories. Of the 1201 AEs having high preventability, 9 (0.7%) were not associated with a human error category; for the remaining 1192 AEs, 2051 causes were identified (Box 2). Delay categories The importance of timeliness to the quality of healthcare led to further analysis of all AEs to ascertain the nature and role of delay in their causation (Box 4A). Delays contributed to 20.0% of AEs: of these, delays in diagnosis accounted for 56.8% and treatment delays for 40.6%. Diagnostic delay was usually the failure to make, or attempt to make, a diagnosis of a patient's condition rather than just providing symptomatic or even no treatment. Treatment delay was when the diagnosis had been made but there was a delay in initiating specific therapy. Examples of AEs in the delay category are included in Box 3B. The AEs with delay categories were judged to have very high preventability (86%-90%) compared with the average (51.2%) for all AEs (Box 4A). Treatment categories AEs categorised as caused by a treatment error were also analysed (Box 4B). In 19.6% of all AEs, treatment error contributed to the cause. The majority of AEs in this group fell into the categories of "no or inadequate treatment" (51.5%), or "wrong or inappropriate treatment" (27.4%). As with AEs caused by delay, these AEs were judged to have much higher preventability than the average for all AEs. Examples of AEs involving treatment errors are shown in Box 3C. Investigation categories Analysis of the AEs caused by patient investigation issues is shown in Box 4C, and examples are given in Box 3D. There was a problem with clinical investigation in 10.7% of AEs. Paralleling the results in the treatment category, most (78.6%) of these AEs were in this category because an investigation was not done, rather than the investigation being inappropriate (3.6%), or not acted upon (15.5%). Consistent with other AEs that are attributed to cognitive failure, there was a very high percentage of these AEs rated as high preventability. Strategies for preventing AEs When describing AEs, preventability refers to the identification of an avoidable error that led to the adverse event. This is not to say that the error could be avoided on every occasion, and that the adverse event would not occur. Rather, it implies that, with the current state of knowledge and technology, it is possible to identify and avoid that particular error, and hence reduce the probability of an AE. The reviewers were making a judgement, having identified the error, on the particular strategy for a change in the healthcare system that could have prevented the AE. The outcomes of these judgements are given in Box 5. Nineteen (1.6%) of the 1201 high preventability AEs did not have a prevention strategy category. Of the 2613 prevention strategies identified in the 1182 AEs with high preventability, 24.7% (646) were for "better education and training", 20.9% (545) were for "new or better implemented policies or protocols" and 18.6% (486) were for "more or better formal quality monitoring or assurance processes". Discussion AEs are important to patients, healthcare providers and to the custodians and funders of health services. One estimate of the national cost to the Australian healthcare system of just the additional hospital bed-days (as a result of the AEs identified in 19921) is in excess of $800 million dollars per year.4 This estimate ignores any subsequent hospital admissions and out-of-hospital healthcare expenses, loss of productivity of the patients involved, and long term community costs of permanent disability from AEs. It also ignores the benefits received from healthcare. Providing insights into how AEs occur can help in developing prevention strategies to reduce the frequency and severity of patient injuries during healthcare. Our review and analysis of the AE data from the QAHCS have shown that the causes of AEs or errors leading to AEs can be characterised, and that human error is a prominent cause. It is important to recognise that human error is inevitable for even the best-trained and best-qualified healthcare providers. Weed has recently pointed out that the unaided human mind is incapable of performing consistently at the necessary level to provide optimal healthcare.5 However, other studies6 have noted that the label "human error" is prejudicial and non-specific; it may retard rather than advance our understanding of how complex systems fail. It is postulated that within complex systems error is a symptom of organisational problems, and this is likely to apply to healthcare. Therefore, we need a healthcare-system response to error that moves the system towards being as "failsafe" as possible rather than one that blames the clinician who may have erred. Examples from the more frequently studied area of adverse drug events7 would be decision-support technology for antibiotic prescribing,8 with its demonstrated benefits, and electronic prescribing to reduce prescribing and transcription errors in hospital.9 Our analysis identified broad functional categories that are linked to the processes that make up the system of healthcare delivery and hence cut across specialties, diagnosis-related groups (DRGs) and particular patient groups. The sample size is large enough to provide useful information even when several AEs could not be classified into the categories chosen, or insufficient information was available to indicate cause. On the other hand, several factors bias the information available for assessing AEs because of an emphasis on procedures and short term outcomes and possible under-reporting of the contribution of the supporting systems to the cause of the AEs. Firstly, because the original data source was the hospital medical record, the information available about AEs is biased towards the patient involved and away from other potentially important contextual events at the time. Further, the medical record often focuses more on the actions of clinicians involved in direct or procedural patient intervention, and less on the actions of other staff or systems with a more supportive role. These and other factors will lead to an emphasis on procedures and short term outcomes, and a possible under-reporting of the contribution of supporting systems in causing AEs. Finally, information about subsequent or prior hospitalisations is usually only available if the patient attended the same hospital on all occasions. Having acknowledged these potential limitations, cognitive failure (Box 2) appears to have a role in 57% of all the causes of AEs, and most of the AEs involved were judged to be of high preventability and to have caused significant disability. These AEs were largely associated with errors of omission rather than commission. Does this represent a minimum "obligatory" error rate resulting from a combination of human error and our healthcare system, and hence which cannot be improved? Our data are not able to answer this question unequivocally, but we believe they show sufficient opportunities for moving the system towards a failsafe mode to suggest that the answer is no. Until recently there has been an under-recognition of the role and responsibilities of the healthcare system and its custodians in providing a "safe environment" using systems-improvement tools.10 One response to these data should be to look at the factors in healthcare delivery that may interfere with the cognitive or technical performance of healthcare providers. Insufficient use of information technology to assemble the necessary information at the time of decision-making may increase error. Another important factor is fatigue, which has already been shown to increase error in doctors.11 Sleep deprivation may have a much more significant role in human error in healthcare than the current work-load patterns pay heed to, but more research is needed. Other factors that may be important include the level of supervision provided to junior staff, and the pervasive effect of the culture of medical practice, which can unhelpfully portray error as individual failure or deviation from perfection.12 Our study method does not provide direct information about the role of these factors. The high proportion of causes of AEs involving cognitive failure must represent a manifestation of human error occurring in a system that is not patient protective, if one accepts that these practitioners are appropriately trained and competent by international standards. Our study provides clear guidance on methods for improvement, with "new, better, or better implemented policies or protocols" accounting for 24% of prevention strategies identified for the AEs, "quality monitoring and assurance processes" accounting for 21%, and "better education and training" for a further 19%. In summary, improvement is needed in the agreed processes of care, supported by information systems that allow general dissemination of current knowledge of diseases or treatments, and information on outcomes of care for each patient, through appropriate quality processes. Simple examples are the availability of practice guidelines and protocols at the point-of-care, and the use of automated reminders for patients and practitioners when a particular test or follow-up is required. In addition, having adequate patient "outcome" information in a form that can be benchmarked is a powerful tool in identifying unacceptable variation. Acknowledgements We acknowledge the contributions of Professor B Armstrong, Professor W R Runciman, Professor R Holland, Dr T Robertson and Dr A Hobbes. References Wilson RMcL, Runciman WB, Gibberd RW, et al. The Quality in Australian Health Care Study. Med J Aust 1995; 163: 458-471. <eMJA pdf> Brennan TA, Leape LL, Laird N, et al. Incidence of adverse events and negligence in hospitalised patients: results of the Harvard Medical Practice Study I. N Engl J Med 1991; 324: 377-384. Andrews LB, Stocking C, Krizek T, et al. An alternative strategy for studying adverse events in medical care. Lancet 1997; 349: 309-313. The Final Report of the Taskforce on Quality in Australian Health Care. Appendix 7. Canberra: AGPS, June 1996. <http://www.health.gov.au/pubs/hlthcare/toc.htm> Weed LL. New connections between medical knowledge and patient care. BMJ 1997; 315: 231-235. Cook RI, Woods DD. Operating at the sharp end: the complexity of human error. Human performance in anaesthesia: a corpus of cases. Report to the Anaesthesia Patient Safety Foundation, 1991. Columbus, Ohio: The Ohio State University: 255-307. Classen DC, Pestonick SL, Evans RS, et al. Adverse drug events in hospitalised patients: excess length of stay, extra costs and attributable mortality. JAMA 1997; 227: 301-306. Evans RS, Pestonick SL, Classen DC, et al. A computer-assisted management program for antibiotics and other anti-infective agents. N Engl J Med 1997; 338: 231-238. Bates DW, Boyle DL, Vander Vliet MB, et al. Relationship between medication errors and adverse drug events. J Gen Intern Med 1995; 10: 199-205. Leape LL. A systems analysis approach to medical error. J Eval Clin Pract 1997; 3: 213-222. Nocera A, Khursandi DS. Doctors' working hours: can the profession afford to let the courts decide what is reasonable. Med J Aust 1998; 168: 616-618. Leape LL. Error in medicine. JAMA 1994; 272: 1851-1857. (Received 4 May 1998, accepted 20 Jan 1999) Authors' details Royal North Shore Hospital, Sydney, NSW 2065. Ross McL Wilson, MB BS, FRACP, Senior Specialist in Intensive Care; Director of QARNS (Quality Assurance Royal North Shore); Bernadette T Harrison, RN RM, Manager QARNS. University of Newcastle, Newcastle, NSW 2308. Robert W Gibberd, PhD, Associate Professor, Department of Statistics; and Director of Health Services Research Group. John D Hamilton, MB BS, FRCP, Professor of Medicine, Faculty of Medicine and Health Sciences. Reprints: Dr R McL Wilson, Director of QARNS, Royal North Shore Hospital, Pacific Highway, St Leonards, NSW 2065. Email: rwilsonATdoh.health.nsw.gov.au Journalists are welcome to write news stories based on what they read here, but should acknowledge their source as "an article published on the Internet by The Medical Journal of Australia <http://www.mja.com.au>". <URL: http://www.mja.com.au/> 1: Terms and definitions Adverse event (AE): An AE was defined as an injury or complication which resulted in disability or prolongation of hospital stay and was caused by the healthcare received rather than by the disease from which the patient suffered. The AE either occurred during the hospital admission, or during an earlier contact with healthcare services, and was responsible for all or part of the hospital admission. Error: An act of commission or omission that caused, or contributed to the cause of, the unintended injury. for errors of commission this will usually be the immediate morbid consequences of the error for errors of omission this will usually be the continuation of, and consequences of, an existing morbid state that could have been cut short, or had a better outcome, if the error had not occurred. Prevention strategy: Changes in the system in which an error occurred that mayreduce the probability of the error occurring increase the probability that the error would be remedied before an unintentional injury occurredPreventability: Preventability of an AE was assessed by the detection of "an error in management due to the failure to follow accepted practice at an individual or system level"; accepted practice was taken to be "the current level of expected performance for the average practitioner or system that manages the condition in question". Back to textBack to text 3. Examples of categories of causes of adverse events and preventability scoresA. Human error categories Example 1: A 50-year-old man sustained a bowel perforation from colonoscopy for investigation of abdominal pain. Laparotomy required. Category: "Technical performance". Preventability score: 3. Example 2: A 71-year-old man required six operations for femoral hernia repair. Category: "Technical performance". Preventability score: 2. Example 3: A 32-year-old woman had persisting severe back pain after two laminectomies, three myelograms, one decompression/fusion, and three thecal/epidural injections over 18 months. In pelvic traction at the time of review. Category: "Technical performance". Preventability score: 4. Example 4: A failed attempt at percutaneous endoscopic gastrostomy on a 32-year-old woman was followed by an open procedure. The patient died 9 days later. Autopsy revealed acute peritonitis, subphrenic abscess and bilateral pneumonia. There did not appear to have been an antemortem diagnosis of intra-abdominal sepsis, or any specific treatment for it. Category: "Technical performance". Preventability score: 6. B. Delay in diagnosis and/or treatment categories Example 1: Diagnosis of cancer of the colon was delayed until the patient, a 62-year-old woman, presented with a ruptured caecum and peritonitis from an obstructing tumour. In hospital 3 months earlier with a history suggestive of cancer of the colon and iron-deficiency anaemia, but no investigation performed. Categories: Diagnosis delay, violation of protocol or rule; failure to synthesise, decide or act on available information; lack of care/attention. Preventability score: 5.5. Example 2: A 28-year-old man with abdominal pain was treated with cholecystectomy. Gallbladder was macroscopically and histologically normal. Small bowel lymphoma was eventually diagnosed and treated, with resolution of the presenting symptoms. Categories: Diagnosis delay; failure to synthesise, decide or act on available information; failure to request or arrange an investigation, procedure or consultation. Preventability score: 5. C. Treatment categories Example 1: A 52-year-old man with known asthma was prescribed a beta-blocker for hypertension. This resulted in acute respiratory failure leading to artifical ventilation and tracheostomy. Categories: Wrong or inappropriate treatment; misapplication of or failure to apply a rule; failure to synthesise, decide or act on information. Preventability score: 6. Example 2: A 54-year-old man developed gastrointestinal bleeding (haemoglobin level, 45 g/L) while receiving non-steroidal anti-inflammatory drugs and steroids for rheumatoid arthritis. This required hospital admission and blood transfusion, at which time the correct diagnosis of osteoarthritis was made. Categories: Wrong or inappropriate treatment; acting on insufficient information; failure to request or arrange an investigation, procedure or consultation. Preventability score: 5.5. Example 3: Hospitalisation and surgical intervention for septic arthritis that followed steroid injection into a joint. Categories: Unclassified treatment; technical; lack of care/attention. Preventability score: 4.5. D. Investigation categories Example 1: A 75-year-old woman died from acute renal failure after developing gentamicin toxicity. Gentamicin was used to treat an infected pleural effusion, and drug levels were not measured. Categories: Investigation not performed; failure to request or arrange an investigation, procedure or consultation; lack of care/attention. Preventability score: 5. Example 2: A 58-year-old woman had recurrent hospital admissions for chest pain and impaired cardiac function without specific investigation, and hence a reduction in treatment options. Categories: Investigation; violation of protocol or rule; failure to synthesise, decide and/or act on available information. Preventability score: 5. Back to text 4: Contribution of delay, treatment and investigation categories to adverse events (AEs). Values are number (%) of AEsPermanentHighA. Delay categoryFrequencydisabilitypreventabilityDiagnostic delay267 (56.8%)93 (34.8%)231 (86.5%)Treatment delay191 (40.6%)53 (27.7%)172 (90.1%)Administrativedelay12 (2.6%)3 (25.0%)11 (91.7%)Total470 (100%)149 (31.7%)414 (87.9%) B. Treatment categoryNo or inadequatetreatment237 (51.5%)72 (30.4%)176 (74.3%)Wrong/inappropriatetreatment126 (27.4%)35 (27.8%)96 (76.2%)No or inadequateprophylaxis41 (8.9%)9 (22.0%)34 (82.9%)Treatmentunclassified36 (7.8%)7 (19.4%)28 (77.8%)Missed treatment20 (4.4%)4 (20.0%) 16 (80.0%)Total460 (100%) 127 (27.6%)350 (76.1%) C. Investigation categoryInvestigationnot performed198 (78.6%)81 (40.9%)171 (86.4%)Investigationnot acted on39 (15.5%)13 (33.3%)36 (92.3%)Investigationinappropriate9 (3.6%)2 (22.2%)9 (100.0%)Investigationunclassified6 (2.4%)2 (33.3%)5 (83.3%)Total252 (100%)98 (38.9%)221 (87.7%)Back to text 5: Frequency of occurrence of categories of prevention strategies and the proportion of adverse events (AEs) judged as causing permanent disability or having high preventability. Values are number (%) of AEsPermanentHighCategoryFrequencydisabilitypreventabilityNew, better, or better implementedpolicies or protocols884 (23.7%)206 (23.3%)545 (61.7%)More or better formal quality monitoringor assurance processes790 (21.2%)186 (23.5%)486 (61.5%)Better education and training715 (19.2%)160 (22.4%)646 (90.3%)Consultation with other specialistsor peers391 (10.5%)133 (34.0%)294 (75.2%)Don't know341 (9.2%)51 (15.0%)186 (54.5%)Better access to, or transfer of, information135 (3.6%)40 (29.6%)100 (74.1%)Discharge procedures and protocols122 (3.3%)27 (22.1%)100 (82.0%)Other89 (2.4%)22 (24.7%)46 (51.7%)Changes in organisation management88 (2.4%)22 (25.0%)75 (85.2%)Changes in organisation culture77 (2.1%)26 (33.8%)66 (85.7%)More or better personnel72 (1.9%)29 (40.3%)53 (73.6%)More or better equipment or otherphysical resources22 (0.6%)8 (36.4%) 16 (72.7%)Total3726 (100%)*910 (24.4%)2613 (70.1%) * Total is greater than the number of AEs (2351) as the categories were not mutually exclusive. Back to text

Bernadette T Harrison · Robert W Gibberd · John D Hamilton

Editorial Research and the acute-care hospital of the future A grand history of failed predictions is an argument for scientific prognostications MJA 1999; 170: 292-293 It is difficult to explain the history of healthcare systems, and the interpretation of contemporaneous events is even more challenging. The hardest enterprise, however, is that of futurist -- if it is to be done well. It involves extrapolating past and present trends, anticipating coming events and painting a cogent picture for posterity. Many people have failed miserably for various reasons.1-3 Lord Kelvin's claim in 1895 that "heavier than air flying machines are impossible" foundered on inadequate modelling. Technological change exposed the conjecture by the Chairman of IBM in 1948 that there was "a world market for about five computers". Arrogance probably led to the insouciant prophecy by the US Secretary of the Navy in 1941 that "[we are] not going to be caught napping". The recent prediction by the Australian Private Hospitals Association that the private health insurance rebate has the potential to "completely eliminate public hospital waiting lists"4 will no doubt be sorely tested. Hillman, in this issue of the Journal,5 combines the skills of historian, contemporary commentator and futurist to survey the acute-care hospital. He expresses views with which many would agree. The hospital sector has emerged in response to a wide range of policies and practices, many of which are no longer relevant. More recently, advances in practice and technology have been impressive, but the sector is exhibiting signs of systems failure,6,7 despite the skills and efforts of the individuals who work within it. Measures such as diagnosis-related groups (DRG) funding, involving clinicians in management, basing decisions on evidence and continuous improvement initiatives represent both a recognition of the problems and an indication that people with different perspectives on the healthcare sector, including policymakers, economists, clinicians and managers, are searching for solutions. Some recent trends seem destined to continue. These include further compression of length of stay, increased outsourcing and privatisation, renewed efforts to manage quality of care, and greater use of care options such as ambulatory care, day-only hospitalisation and home care.8,9 However, mere extrapolation is an insufficient basis for prediction given the many changes in clinical practice that could hardly have been anticipated. Further, in view of the lack of strategic vision of most Australian governments, there is no coherent framework for these trends. Moreover, the trends have been influenced by unfortunate constraints. For example, we have maintained the illogical splits in healthcare financing between the Commonwealth and the States despite 50 years of expert opinion that this system is counterproductive. It similarly makes no sense to separate private and public insurance. To allow privately insured patients to congregate in privately owned hospitals ensures there is little or no helpful competition across ownership types. Exactly how the healthcare delivery system will change is open to debate, which is one of the reasons Hillman's contribution is timely and useful. He paints a plausible picture that will no doubt stimulate valuable discussion and will be validated or invalidated over time. We would do well to heed four main points in the article. One is to consider how the idea of "hospitalist" -- essentially a specialist in acute-care and emergency medicine who releases other specialists from these activities -- would translate from the American to the Australian context. Second, the community health-hospital interface needs to be better integrated. Hillman envisages a more prominent role for general practitioners and community medicine, and the experience of the National Hospital Demonstration Program and the Coordinated Care Trials is of considerable value. Third, there will be challenges ahead for medical education in a more complex system.10 The fourth point is the emerging need for more research on the delivery system. The Health and Medical Research Strategic Review has shown that Australian research support is less than that of other Organization for Economic Cooperation and Development (OECD) countries ($28 per capita, compared with a GDP-weighted OECD average for developed countries of $42).11 There are thus grounds for increased expenditure on health and medical research, but health services research appears to be especially at risk. The Figure shows the most recent National Health and Medical Research Council (NHMRC) data comparing the relative success rate of grant applications by research field. The type of research that Hillman calls for is within the very field for which it is most difficult to secure NHMRC funding, the largest, and in some cases the only, source. Yet there are undoubtedly further gains to be made in delivery efficiency, structure and quality of care by enhancing health services' research efforts. We could head in several directions. At one extreme, there could be an intensification of what we have today -- more pressure to produce, more privatisation, more band-aid attempts to link fee-for-service general practitioners with public hospitals and home care services under strictly capped budgets, and more quarterly worrying about private health insurance, even with the 30% tax rebate. On the other hand, we could shoot for the social democrats' dream -- a single public insurer, all-encompassing area health services, multidisciplinary clinical teams as the prime contractors, increased preventive and community services with hospitals demoted to providers of intensive care beds, and so on. Health services research tools, such as critical historical incidents analysis, policy evaluation, scenario planning, computer modelling, decision analysis and risk assessment, can provide guidance to decision makers. They will help reduce the mistakes of the past, illuminate present problems and make future predictions more precise. Jeffrey Braithwaite Senior Lecturer Don Hindle Professor School of Health Services Management Faculty of Medicine University of New South Wales, Sydney NSW Email: j.braithwaiteATunsw.edu.au Cerf C, Navasky V. The experts speak. New York: Pantheon Books, 1984. Starbuck WH. Strategising in the real world. Intl J Technol Management 1992; 8 (1/2): 77-85. Shoemaker PJH. Scenario planning: a tool for strategic thinking. Sloan Management Rev 1995; Winter: 25-40. Australian Private Hospitals Association. An open letter to all Labor, Democrat, Green and Independent Senators. The Australian 9 December 1998: 9. Hillman K. The changing role of acute-care hospitals. Med J Aust 1999; 170: 325-328. Wilson RM, Runciman WB, Gibberd RW, et al. The Quality in Australian Health Care Study. Med J Aust 1995; 163: 458-471. Bolsin S. Professional misconduct: the Bristol case. Med J Aust 1998; 169: 369-372. Braithwaite J. The 21st-century hospital. Med J Aust 1997; 166: 6. Komesaroff PA, Clunie GJ, Duckett SJ. What is the future of the hospital system? Med J Aust 1997; 166: 17-23. Larkins RG, Martin TJ, Johnston CI. The boundaryless hospital -- a commentary. Aust N Z J Med 1995; 25: 169-170. Health and Medical Research Strategic Review. The virtuous circle: working together for health and medical research. Canberra: Commonwealth of Australia, 1998. URL: http://www.hmrsr.com (accessed 1 March 1999). Journalists are welcome to write news stories based on what they read here, but should acknowledge their source as "an article published on the Internet by The Medical Journal of Australia <http://www.mja.com.au>". <URL: http://www.mja.com.au/> Back to text

Jeffrey Braithwaite · Don Hindle

For Debate The changing role of acute-care hospitals Acute-care hospitals are moving away from their central role in the healthcare system and becoming specialised institutions for the care of a particular kind of patient. Ken Hillman MJA 1999; 170: 325-328 For editorial comment, see Braithwaite & Hindle Introduction - The technological boom - System failure - Community care alternatives - A narrower role for the hospital? - Enter: a new specialty - Clinical experience and education - General practice and innovation - References - Authors' details - - More articles on Administration and health services Introduction The publicly funded acute-care hospital had its origins as a charitable institution.1 Until the middle part of this century, the working life of medical practitioners was predominantly based on private practice. Private patients were attended in doctors' rooms and, when necessary, usually cared for in small private hospitals.2 Large public hospitals were for the poor. The clinician would visit the public hospital for several hours each week to attend the poor and teaching and research were centred on these patients. Everyone seemingly gained. The sick received free care and the clinician's conscience and sense of righteousness were satisfied. Because private medical practitioners were accommodating the poor on a charitable basis, the hospital system was established around practitioners' needs. For example, surgeons had their own operating theatre, theatre nurse, ward, ward nursing staff and a cluster of junior doctors, usually organised in a hierarchical way, with house staff at the bottom and senior registrars-in-training at the top. Similar systems existed for other specialties, such as internal medicine and obstetrics. The legacy of these arrangements is that the acute-care hospital has grown in a haphazard way, resulting in inefficiencies, duplication and the development of a system that is often designed around medical practitioners rather than patients. This system is now clashing with increasing demands by consumers to be involved in their own care, pressures from funders for more financial accountability and changing technology in medical care. As a result, the nature and role of acute-care hospitals are undergoing upheaval. The technological boom Until as recently as 40 years ago, hospitals were mainly places for bedrest and convalescence. The range of surgical operations was limited, high-powered investigations and monitoring were almost non-existent and medical treatments were largely restricted to a small number of procedures and relatively simple drugs. Nature, more than medical interventions, determined whether patients recovered or not. An explosion of medical knowledge occurred in the 1950s. Complex surgery such as cardiac valve replacement, transplant surgery, microsurgery and complex cancer surgery became commonplace. Great advances occurred in anaesthesia, making the performance of these procedures possible. Intensive care units (ICUs) kept many patients alive who previously would not have survived. Physicians developed interventions such as endoscopy and chemotherapy. Investigations such as computed tomography expanded our knowledge of diseases and treatment options. Whereas previously all hospitals provided a similar range of options for patients, there now emerged a complex institution serviced by an expanding range of medical specialties, complemented by expensive technology. A two-tiered system of hospitals developed. One was limited in its range of expertise and technology, while the other was keeping abreast of all the rapidly emerging developments. The winners were the hospitals in the heart of capital cities. Outer metropolitan and rural hospitals increasingly had to refer patients to these centres of excellence. The reasons why some hospitals developed as centres of excellence and others did not are complex; it was largely related to the clustering of medical expertise in large, centrally located, university-affiliated hospitals. The developing expertise in one specialty was often dependent on similar rates of development in others, in order to perform increasingly sophisticated interventions. System failure Despite increasing specialisation and remarkable advances in technology, the fundamental organisation in hospitals has changed little. Concepts such as clinical directorates, clinical pathways, evidence-based medicine, benchmarking and quality improvement are to a greater or lesser extent affecting the way we manage patients in acute-care hospitals. However, patients are still admitted under an individual clinician who "owns" them; the patient is discharged at the admitting clinician's convenience; and, in the larger institutions, nursing staff, together with a hierarchy of junior medical staff, still manage the day-to-day care of the patient. Basic issues such as standardised indications and protocols for the admission and discharge process are usually not addressed and patient management is usually not well coordinated. The flow of patients through a hospital is often inefficient, dislocated and disorganised. While individual specialists and departments may deliver excellent individual standards of care, the system often falls apart at the interfaces of that care. For example, a patient may be operated on by the world's best plastic surgeon and be treated in a ward renowned for plastic surgical care, but, if the patient bleeds excessively, the system may soon be sorely tried. Let us imagine that the patient becomes tachycardic and hypotensive. Hypovolaemic shock is not a common occurrence in a plastic surgery ward. Vital signs are only recorded four-hourly. Nursing staff inform junior medical staff, who in turn inform up the hierarchy. The plastic surgery registrar may be a great technician, but often does not have formal training in management of the seriously ill and recent advances in resuscitation. Let us imagine further that the patient, as is increasingly common, has comorbidities such as underlying ischaemic heart disease, hypertension and chronic lung disease related to smoking. The patient has a myocardial infarction and things go from bad to worse. The system fails, because it is a system designed for performing procedures, somewhat at the convenience of doctors, and not a system for the coordinated care of patients. A sobering example of system failure has recently been widely reported.3 Between 10 000 and 14 000 preventable deaths may occur in Australian hospitals each year.4 Similar problems exist in other countries.5 Of course, this is the tip of the iceberg: for every preventable death, there are many potentially preventable serious complications. The incidence is the same whether the hospital is a small rural one, a large metropolitan hospital or a teaching and referral centre.4 This incidence of adverse events may worsen as hospital bed numbers are "downsized" and the remaining patients become more seriously ill and at risk of preventable death and complications. There is now enormous pressure to reduce hospital bed numbers, to cut hospital admissions and to reduce the length of stay in hospitals. Hospitals will have to respond by lifting the effectiveness of their system of care. Community care alternatives These pressures are largely due to financial constraints, yet it may not be such a bad thing for most patients to spend less time in hospital. Institutional care in hospitals is not necessarily the most sensitive and caring environment for many patients, including those who are dying, those requiring rehabilitation and those with mental illness. In other words, it may not only be cheaper but better for ambulant patients to be treated in more appropriate environments.6 As alternatives are developed, hospitals are restricting their function to managing patients who have serious, complex and potentially recoverable illnesses. Specialties such as psychiatry, geriatrics, rehabilitation and palliative care are increasingly becoming community based. Many investigations, even the more complex ones, are now being performed in the community. Up to 60% of patients are now having day-only surgery.7 Imaginative alternatives to hospital-based care are being developed. This is leading to a radical change, both for the broader healthcare picture and for the future of acute-care hospitals. A narrower role for the hospital? The acute-care hospital will, in the near future, care mainly for the sick who have a chance of recovering.8,9 Increasingly, in-hospital patients will have more complex problems and a greater number of comorbidities. Specialised units caring for the seriously ill are increasing. Emergency departments are increasingly managing the seriously ill rather than offering primary healthcare; operating suites are performing more complex procedures for in-hospital patients. As a result, far more intensive-care and high-dependency beds are required, while the total number of acute-care hospital beds is decreasing as the more ambulant and less sick are managed elsewhere.10Ironically, the increasing specialisation that has occurred over the last 40 years may not provide support for the changing population of hospital patients. Specialists will, of course, continue to provide specific expertise. Opinions will be sought on a particular problem or a specialised procedure will be performed, but modern specialists may not always be appropriate for providing overall care for a complex in-hospital patient.10-12 Increasingly, specialists who were once based almost entirely in a hospital setting are providing care for patients in ambulant and out-of-hospital settings. Enter: a new specialty These developments have led in some countries to the emergence of a "hospitalist"13 who has a wide range of expertise, but concentrating more on acute hospital medicine -- more like a general physician, but specialising in acute and serious illness rather than chronic and mainly ambulant medicine. The hospitalist also has advanced resuscitation and procedural skills. They are familiar with the medical comorbidities increasingly associated with surgical patients and understand how different organs fail and interact in acute illness. They are a move back to the generalist physician. The equivalent in Australia is probably the intensive care or emergency physician. The hospitalist also understands about continuity and coordination of patient care, managing the patient's in-patient course and arranging a seamless transition to a community setting.13The proponents of the hospitalists argue that, as hospital stay becomes shorter and more intense, it is unlikely that high value care can continue to be delivered by traditional specialists who spend only some of their day in an acute hospital setting and do not have the time to keep abreast of all the developments in acute-care and emergency medicine, or to maintain competence in acute-care resuscitation. It has always been the case that most acute hospital care is performed by the permanent hospital junior medical and nursing staff.11 The role of the specialist has changed little in that way over the last hundred years. Specialists manage their in-hospital patients at a distance, using rotating junior medical staff and nursing staff for most of the day-to-day care. A hospitalist could enable community-based specialists to devote more time to what they do best, rather than being continuously confronted by the dilemma of maintaining a busy professional practice with tight appointment schedules and having seriously ill in-hospital patients who might require their attention day or night in an unpredictable way. Having skilled clinical cover 24 hours a day would also help guarantee patient safety. However, there are many ways of achieving this goal, and, while the concept of a "hospitalist" may be working in the United States, Australia could explore other ways of achieving the same standards. Clinical experience and education The changing nature of acute-care hospitals will also have wide-ranging effects on undergraduate and postgraduate medical training in Australia.14,15 While many welcome changes have occurred in undergraduate training in Australia, the bulk of it remains based on hospital patients, who are in turn not only decreasing in number but (even more importantly) represent an increasingly limited part of the healthcare spectrum. Patients with the common problems on which undergraduate education was based are now managed in other environments, such as the specialist's rooms or in the community. Moreover, the skills necessary to manage an increasingly ill population of in-hospital patients have either never been taught, or are taught suboptimally.16,17 Similarly with postgraduate education. While physicians and surgeons may have had some exposure to emergency and intensive care medicine, there is currently no formal or obligatory requirement for training in advanced resuscitation. With increasing specialisation, this might become even more of a problem for physicians as their skills become more orientated to the less seriously ill and more ambulant patients. Moreover, hospital systems are poorly designed to deal 24 hours a day with the seriously ill. Up to 80% of in-hospital cardiac arrests are preceded, often for many hours, by slow and documented deterioration in vital signs.18 Among critically ill patients who do not have an arrest, there is a high incidence of serious complications that are not adequately managed in a timely fashion.19 Systems dealing with the seriously ill, such as those for trauma20 and acute in-hospital medical problems,21,22 are being developed in some centres but they are not, as yet, seen as fundamental to the care of the critically ill. In-hospital patients with cross-specialty problems are usually subject to a complex system of referral. This works well for non-life-threatening problems, but for the increasing population of at-risk patients in acute-care hospitals the lack of systems which work at the interfaces between specialists, professions and departments may be contributing to excessive mortality and morbidity.19,23 General practice and innovation The role of the general practitioner (GP) in the larger health picture is also being re-evaluated. While GPs have probably always seen acute-care hospitals as expensive and relatively insignificant players in the big healthcare picture, acute-care hospitals have, until recently, seen themselves as the self-appointed flagships of healthcare. Now GPs and community-based healthcare delivery are becoming more dominant in healthcare. Healthcare is being devolved back to them at a rapid rate, as acute-care hospitals attempt to decrease admission rates, reduce length of stay and facilitate early discharge. The way community health and hospital care interact is also being reinvented. Most Western countries are struggling with the issue of how to deliver better healthcare at the same or reduced cost. Australia has a unique opportunity to develop its own way of achieving this without necessarily slavishly adopting overseas systems such as managed care or seeing privatisation as a panacea for healthcare delivery problems. Already we are seeing many exciting Australian examples of innovation in this area. The New South Wales system of discrete Health Areas, with one authority being responsible for all acute-care hospital and community-based services, is proving an exciting platform for re-engineering health in innovative ways. The Commonwealth Government has funded innovative models developed by actively practising clinicians working together from community and acute-care hospitals (National Demonstration Hospital Programs). Hospitals will increasingly develop systems based on patient needs as well as the needs of the admitting clinicians. Community-based healthcare, including GPs, will provide most healthcare. Hospitals will treat fewer patients who are increasingly ill. Acute-care hospitals will become more specialised in their function and, as such, will probably be inappropriate platforms for comprehensive undergraduate and postgraduate medical training. Whether adequate funding to the community will follow this change in healthcare is debatable. As a result of these changes, it is crucial that we carefully and methodically devote more health research funding to evaluate the effects of these changes on patients. References Abel-Smith B. The hospitals 1800-1948. Heinemann, London 1964. Physicians, practitioners and fees. BMJ 1878; 1: 197-198. Bolsin S. Professional misconduct: the Bristol case. Med J Aust 1998; 169: 369-372. Wilson RMcL, Runciman WB, Gibbert RW, et al. The Quality in Australian Health Care Study. Med J Aust 1995; 163: 458-471. Brennan TA, Leape LL, Laird N, et al. Incidence of adverse events and negligence in hospitalised patients: results of the Harvard Medical Practice Study I. N Engl J Med 1991; 324: 370-376. Caplan GA, Brown A, Crowe PJ, et al. Re-engineering the elective surgical service of a tertiary hospital: a historical controlled trial. Med J Aust 1998; 169: 247-251. Morgan M, Beech R. Variations in lengths of stay and rates of day case surgery: implications for efficiency of surgical management. J Epidemiol Community Health 1990; 44: 90-105. Braithwaite J, Vining RF, Lazarus L. The boundaryless hospital. Aust N Z J Med 1994; 24: 565-571. Hillman KM. Reducing preventable deaths and containing costs: the expanding role of intensive care medicine. Med J Aust 1996; 164: 308-309. Moss F, McNicol M. Alternative models of organisation are needed. BMJ 1995; 310: 925-928. Smith J. Consultants of the future. BMJ 1995; 310: 953-954. Mather HM, Elkeles RS on behalf of the North West Thames Diabetes and Endocrinology Specialist Group. Attitudes of consultant physicians to the Calman proposals: a questionnaire study. BMJ 1995; 311: 1060-1062. Wachter RM, Goldman L. The emerging role of "hospitalists" in the American Health Care System. N Engl J Med 1996; 335: 514-517. Brooks PM, Goulston KJ. Future of medical training in Australia. Med J Aust 1998; 168: 504-505. Lawson KA, Armstrong RM, Van Der Weyden MB. A sea change in Australian education. Med J Aust 1998; 169: 653-658. Buchman TG, Dellinger RP, Raphaely RC, Todres ID. Undergraduate education in critical care medicine. Crit Care Med 1992; 20: 1595-1603. Harrison GA, Hillman KM, Fulde GWO, Jacques TC. The need for undergraduate education in crit care. Results of a questionnaire to Year 6 medical undergraduates, UNSW and recommendations on a curriculum in critical care. Anaesth Intensive Care 1999; 27: 53-58. Schein RMH, Hazday N, Pena M, et al. Clinical antecedents to in-hospital cardiopulmonary arrest. Chest 1990; 98: 1388-1392. McQuillan P, Pilkington S, Allan A, et al. Confidential inquiry into quality of care before admission to intensive care. BMJ 1998; 316: 1853-1858. Report of the Working Party on Trauma Systems. The National Road Trauma Advisory Council. Canberra: Commonwealth Department of Health, Housing, Local Government and Community Services, 1993. Lee A, Bishop G, Hillman KM. Daffurn K. The medical emergency team. Anaesth Intensive Care 1995; 23: 183-186. Hourihan F, Bishop G, Hillman KM, Daffurn K, Lee A. The medical emergency team: a new strategy to identify and intervene in high risk patients. Clin Intensive Care 1995; 6: 269-272. Lundberg JS, Perl TM, Wiblin T, et al. Septic shock: an analysis of outcomes for patients with onset on hospital wards. Crit Care Med 1998; 26: 1220-1024. Authors' details The Simpson Centre for Health Service Innovation, The University of New South Wales, Sydney, NSW. Ken Hillman, FRCA, FFICANZCA, Director, and Professor of Intensive Care. Reprints will not be available from the author. Correspondence: Professor K M Hillman, Co-Director, Division of Critical Care, The Liverpool Health Service, PO Box 103, Liverpool, NSW 2170. Email: k.hillmanATunsw.edu.au Journalists are welcome to write news stories based on what they read here, but should acknowledge their source as "an article published on the Internet by The Medical Journal of Australia <http://www.mja.com.au>". <URL: http://www.mja.com.au/> The hospitalist Cares for patients with complex acute illness Specialises in acute-care hospital medicine Makes a career wholly within the hospital system Has advanced resuscitation and procedural skills Knows the medical morbidities of surgical patients the interactive effects of organ systems in stress and failure Coordinates care for patients across departments, from doctor to doctor Ensures continuity of care for patients and through these skills and action Prevents hospital systems failure Back to text

Ken Hillman

Ethics Ethical implications of competition policy in healthcare We need to debate the ethical and philosophical questions underlying the application of market economics to healthcare Paul A Komesaroff MJA 1999; 170: 266-268 Introduction - Assumptions underlying competition policy - Effects of competition policy - Ethical and cultural implications of competition policies in healthcare - Conclusion - References - Authors' details - - More articles on Ethics Introduction The Melbourne Age of 28 July 1998 reported the case of Dr Stephen Vaughan, a medical oncologist, who, after 23 years in public hospitals, resigned, disillusioned and dispirited. According to the Age, Dr Vaughan left medical practice because the value he holds dearest -- caring -- seems to have disappeared. In Dr Vaughan's own words: The personal dimension of care is regarded in the public sector as an optional extra -- but it shouldn't be optional. It is essential. . . . Public hospitals used to be the holder of the values of community and personal caring, irrespective of ability to pay . . . but now they're just another organisation chasing the buck, and if you don't get paid you don't do it.1As the responses in the letters columns seem to attest, this experience of contemporary medicine is common in Australia today. There appears to be a widely felt sense that the opening up of medicine to commercial interests and the promotion of economic competition have undermined fundamental values and seriously threaten patient care. It is widely felt, too, that these issues have been substantially neglected in the public debates, which have focused almost exclusively on technical issues of financing at the expense of ethical and cultural questions.2 I shall argue that the social policy which promotes economic competition as a major technique for regulating the healthcare industry raises a wide range of issues about the organisation and dynamics of healthcare and is likely to lead to a variety of outcomes that are not beneficial. Before committing ourselves irrevocably to such a policy we need to consider not just the economic variables, narrowly defined, but also the underlying ethical and philosophical questions. Assumptions underlying competition policy Soon after taking office, in May 1996, the Minister for Health, Dr Michael Wooldridge, declared the government's commitment to promoting competition in the healthcare sector: One fundamental of micro-economic reform has been the application of competition principles to industry -- including those where public sector funding and provision has been significant, as it is in the health sector. These principles are based upon an approach [in] which decisions about the use of resources are made in the light of independent bids for the provision of goods or services made by players who are not in any way in collusion.3An increasing emphasis on the role of the market in regulating decision making is at the centre of the national competition policy for healthcare in Australia (Box). Its advocates argue that enhanced conditions of competition among doctors, hospitals and insurers should be supported for two reasons: because they are necessary to contain healthcare costs and because they will provoke a shift in the healthcare power balance from providers -- that is, doctors -- to consumers -- that is, patients. Many of the assumptions underlying such a perspective, however, depend on a view of human action and relationships that can be contested on both philosophical and factual grounds. For example, it is assumed that consumers always act out of self-interest, that they use their own money to buy all goods and services, and that they seek the best price quantity/quality combination to maximise total utility. Similarly, it is assumed that providers are also primarily concerned with their own interests, adapt their prices and throughput in the light of consumers' purchasing, act to maximise profits by increasing market share at acceptable prices, and always seek to use labour and resources sparingly. All of these assumptions are mistaken, at least with respect to medicine. Although economic constraints of some kind are obviously unavoidable, it does not follow that these must be derived from the market. As is widely acknowledged, the healthcare market is not a perfect one.9 Individual patients by and large do not behave like typical consumers. Ordinary people cannot always understand the complex healthcare field, their needs are immediate, and decisions need to be taken under conditions of duress. In addition, patients become dependent on doctors with whom they have established ongoing relationships of trust and who in turn are sincerely committed to their patients' interests. Effects of competition policy Where competition policies have been introduced elsewhere it is not clear that they have produced beneficial effects. Indeed, economic competition in healthcare may raise costs rather than reducing them.3,10 For example, in California, where these models have been heavily promoted, healthcare-spending growth is faster than in any other American state and costs are now the second highest in the country. Likewise, in New Zealand, where similar policies were introduced over the past six years, it is claimed that distortions created by the economic incentives have led to overservicing in some areas and underservicing in others.11-13Similarly, the effect of competition policies on consumer choice has been mixed. Limitation of the sovereignty of physicians does not necessarily mean increased possibilities for patients. On the contrary, to the extent that market-based incentives tend to operate against the most needy and vulnerable members of the community, the indigent and socially disadvantaged populations are likely to be worse off under a more competitive system. In the US, where it is commonplace for healthcare organisations to seek openly to maximise their profits by restricting medical care in individual cases, this appears commonly to be the case.3,14 In Australia, the introduction of casemix funding has openly discouraged admissions for social or compassionate reasons by attributing low weights in these categories, and there is evidence that specific social groups may be particularly disadvantaged.15 Ethical and cultural implications of competition policies in healthcare The promotion of market-based incentives and discentives as the main regulating mechanism for the healthcare system affects not just the "economic variables" -- it also influences the quality of healthcare in general and the experiences of patients and doctors that emerge from it. Indeed, competition policies explicitly seek to challenge many of the traditional norms underlying medical practice, on the assumption that these are simply devices for protecting the financial interests and power of physicians.10As both doctors and patients have always recognised, however, the medical relationship cannot be understood purely as a commercial relationship. Patients come to doctors because they are experiencing pain, illness or fear. They offer access to their bodies and to the intimate recesses of their personal lives. They grant wide discretion and decision-making power to doctors, on the understanding that doctors will exercise their judgement in a disinterested and compassionate manner. It is mutually agreed that the power of doctors is subject to rigorous ethical constraints arising from the long tradition of medicine, which have been upheld by the professional organisations for hundreds of years. These constraints, which constitute a complex, self-generated system of professional norms, limit the nature of personal relations between doctors and patients, the use and dissemination of information, licensing and credentialling of practitioners, and specific commercial practices such as fee splitting, advertising, self-referral, and ownership of pharmacies and hospitals by physicians. They primarily reflect altruistic concerns of doctors to separate personal and financial considerations from the paramount professional goal of doing what is best for their patients, even if, undeniably, they also have the effect of protecting doctors' financial interests. They do not prohibit competition, but rather channel it into non-economic forms, such as competition for reputation, recognition and status, and social influence. Emphasising economic values undermines the role and power of ethical values.16 This fundamental shift may in the longer run prove deeply significant for society as a whole, for it may lead to changes in the structure and dynamics of the clinical process itself. A crucial aspect of the medical encounter is that it is not purely "instrumental" in character. It does not merely subserve technical functions, the solution of problems in biochemistry or physiology through the application of scientific modes of thought and analysis. It is also involved in setting goals, in identifying and scrutinising meanings, and in establishing the frameworks within which the technical problems are identified and given a value. These latter functions are "non-instrumental" in character, and become possible because of the peculiar nature of the contact between doctor and patient: its intimacy and openness, its reliance on vulnerability and trust, the moment of sanctuary it offers with respect to the utilitarian relationships of everyday life. It is through the contact that the doctor is granted with the lifeworld of the patient that the healing process becomes possible. This contact, which occurs through a variety of mechanisms, including language and touch, stands at the irreducible core of clinical medicine. It is an unavoidable consequence of the introduction of the unrestrained operation of market forces into healthcare that economic values penetrate to the heart of the medical relationship. Indeed, it is precisely the rationale of the policy that financial imperatives take over as the motivating principle of all medical decision making. To open up the clinical relationship to such forces, to subject it to criteria that are purely calculable and quantitative, risks undermining the dynamic structure on which the entire medical enterprise rests. The physician becomes the agent of the hospital or the system rather than of the patient. His or her primary obligation to act on behalf of the patient is displaced in favour of conformity to a complex system of economic incentives and disincentives. The scope for disinterested, compassionate care is greatly contracted.17 The opportunities to respond to individual needs, to the specific details of the predicament of a particular patient, are severely contracted in the face of the overwhelming power of economic imperatives.18 Health-financing policies cannot be understood as exclusively technical, or "value free", mechanisms for regulating the healthcare system. Rather, they must be interpreted and evaluated in accordance with philosophical and ethical criteria and in relation to their social and cultural consequences.19 We need to ask not merely Is this a way to balance the books? but also Is this the kind of healthcare system we want to have? If this simple test is adopted it becomes immediately apparent that a reliance on economic incentives to regulate the quality and distribution of healthcare resources is, through its effect on the conduct of doctors and the outcomes for patients, very likely to lead to consequences widely considered unacceptable. Conclusion Clearly, action to limit healthcare costs is widely supported in the community. Among the possible strategies for achieving this end, an enhanced emphasis on economic incentives and disincentives has gained popularity around the world. Although the stated aim of this policy is to reduce healthcare costs and increase consumer sovereignty, whether it will achieve these objectives is open to question. The employment of economic competition as a key device in the regulation of the healthcare system, however, is more than a mere technical solution to a fiscal problem. It is an intervention that raises issues at medicine's philosophical core. One of the major objectives of competition policies is to challenge the traditional system of norms that guide the behaviour of physicians; the implications of this are potentially far-reaching. The possibility that the introduction of economic imperatives at the heart of the medical endeavour may compromise it in a fundamental way also needs to be considered. The globalisation of the economy -- in the dual sense of the elimination of national boundaries and the universalisation of economic values -- has the capacity to profoundly transform the nature of the entire domain of healthcare. To be sure, it may usher in lower prices for some services and enhanced availability of others. However, the cost of these gains may be very high, for it may also lead to the corruption of some of the central values of medicine, and to a contraction of the sphere for individual action in favour of the uncompromising demands of the ever-expanding system. This scenario -- and that depicted by Dr Vaughan -- may, of course, be too bleak. Perhaps the traditional values of medicine will prove to be sufficiently resilient to survive under the changed social and economic conditions, as indeed they have over the millennia. Naturally, it is to be hoped that this will be the case. Nonetheless, it is essential that proposed new directions in healthcare policy are subjected to rigorous scrutiny in relation not merely to narrowly conceived fiscal criteria but also to cultural and ethical ones in open, public debate. References Toy M-A, Birnbauer B. This man has been a cancer specialist for 23 years. Last week he quit. Why? The Age (Melbourne) 1998; 28 July: 1. Lown B. Physicians need to fight the business model of medicine. Hippocrates 1998; 12: 25-28. Wooldridge M. Opening. In: AMA Summit proceedings. Competition in health: a brave new world? Canberra: Australian Medical Association, 1996; 2-9. Glaser WA. The competition vogue and its outcomes. Lancet 1993; 341: 805-812. Enthoven AC, Kronick R. Consumer-choice health plan for the 1990s. N Engl J Med 1989; 320: 29-37, 94-101. Kuttner R. Physician-operated networks and the new antitrust laws. N Engl J Med 1997; 336: 386-391. Changra J, Kakabsadse A. Privatisation and the National Health Service. Aldershot: Gower, 1985. Fels A. The ACCC approach to health. In: AMA Summit proceedings. Competition in health: a brave new world? Canberra: Australian Medical Association, 1996; 14-20. Reinhardt UE. Accountable health care: is it compatible with social solidarity? London: Office of Health Economics, 1997. Robinson JL, Luft HS. Competition and the cost of hospital care. JAMA 1987; 257: 3241-3245. Pezaro D. The New Zealand view. In: AMA Summit proceedings. Competition in health: a brave new world? Canberra: Australian Medical Association, 1996; 9-13. Hemenwon D, Killen A, Cashman SB, et al. Physicians' responses to financial incentives: evidence from a for-profit ambulatory care center. N Engl J Med 1990; 322: 1059-1063. Hillman A, Pauly MV, Kerstein JJ. How do financial incentives affect physicians' clinical decisions and the financial performance of health maintenance organisations. N Engl J Med 1989; 321: 86-92. Brown ER, Dallek G. Changing health care in Los Angeles. In: Ginzberg E, Berliner HS, Oston M, Brown ER, editors. Changing US health care: a study of four metropolitan areas. Boulder: Westview, 1993. Ruben AR, Fisher DA. The casemix system of hospital funding can further disadvantage Aboriginal children. Med J Aust 1998; 169 Suppl Oct 19; S6-S10. Pellegrino ED. Ethics. JAMA 1994; 271: 1668-1670. Agich GJ, Begley CE. Some problems with pro-competition reforms. Soc Sci Med 1985; 21: 623-630. Weber M. Science as a vocation. In: Gerth HH, Mills CW, editors. From Max Weber: essays in sociology. London: Routledge and Kegan Paul, 1964; 129-158. Charlesworth M. The new ideology of health care: ethical issues. In: Halasz G, on behalf of the Psychiatrists Working Group, editors. She won't be right, mate: the impact of managed care in Australian psychiatry and the Australian community. Melbourne: Psychiatrists Working Group, 1997; 104-110. A version of this article was given as an oral presentation at the Australian Medical Association conference Competition in health, Canberra, 31 July 1998. Authors' details Department of Medicine, Monash University, Melbourne, VIC. Paul A Komesaroff, PhD, FRACP, Associate Professor, and Director, Eleanor Shaw Centre for the Study of Medicine, Society and Law, Baker Medical Research Institute, Melbourne. Reprints will not be available from the author. Correspondence: Dr P A Komesaroff, Director, Eleanor Shaw Centre for the Study of Medicine, Society and Law, Baker Medical Research Institute, PO Box 6492, St Kilda Central, VIC 8008. Email: Paul. KomesaroffATbaker.edu.au Journalists are welcome to write news stories based on what they read here, but should acknowledge their source as "an article published on the Internet by The Medical Journal of Australia <http://www.mja.com.au>". <URL: http://www.mja.com.au/> What is competition policy? Competition policy is an economic and political strategy for ensuring that market forces operate as the principal device for the regulation of economic relations. Several approaches reflect the range of economic theories and philosophical perspectives represented.4 In the United States, antitrust laws are used to break up arrangements such as fee schedules by medical associations, corporations among hospitals, collective bargaining between providers and insurance carriers and payer reimbursement. More recently, managed care has emerged as a major approach to cost containment.5,6 In the United Kingdom under the Thatcher Government, certain services were contracted out to private firms and hospital and general practitioners were granted a substantial degree of financial autonomy.7 In Australia, a National Competition Policy was introduced in 1995 with bilateral support, establishing competition and cost considerations as the guiding principle of public policy at every level of government. This policy is enforced through a framework of law -- including the Trade Practices Act 1973, the Competition Policy Reform Act 1995 and the Prices Surveillance Act 1983 -- and two key regulatory bodies, the Australian Competition and Consumer Commission and the National Competition Council.8 These regulatory bodies have very wide powers to oppose "anti-competitive conduct and unfair market practices" of all kinds, and to regulate "mergers or acquisitions of companies, product safety/liability and third party access to facilities of national significance". Back to text

Paul A Komesaroff

Editorial Clinical pathways A practical tool for specifying, evaluating and improving the quality of clinical practice MJA 1999; 170: 54-55 The article by Dowsey et al1 in this issue of the Journal is significant. This is the first report in the Australian medical literature that documents the impact of clinical pathways in a tertiary care setting, and is also one of the first randomised trials to show that the use of pathways can improve clinical outcomes. A clinical pathway is a tool that sets locally agreed clinical standards, based on the best available evidence, for managing specific groups of patients. The pathway forms part or all of the patient's record and allows the care given by members of the multidisciplinary team, together with the progress and outcome, to be documented. Variations from the pathway are recorded, and analysis allows a continuous evaluation of the effectiveness of clinical practice.2,3 Information thus obtained is used to revise the pathway to improve the quality of patient care. Pathways were introduced into the United Kingdom in the early 1990s and are used for treating patients with a wide variety of clinical conditions in primary, secondary and tertiary care. They may be diagnosis-based (as in the management of myocardial infarction), or symptom-based (as for the investigation and treatment of patients presenting with chest pain). They may also include a specific procedure, such as renal biopsy, or encourage the use of therapeutic guidelines, such as postoperative analgesia. Standardisation of care has been shown to improve outcomes4 and poor quality healthcare is often associated with unjustifiable variation in clinical practice.5Dowsey and colleagues1 have shown that when they introduced pathways for hip and knee joint arthroplasty better patient outcomes were achieved. The use of clinical practice guidelines based on the best available evidence has generally been welcomed,6 but implementation requires specific action at a local level.7,8 Pathways facilitate the use of guidelines by the multidisciplinary team, as they are locally agreed and are available in the patient's record when decisions are being made. Analysis of the causes of variation further encourages adherence to the guidelines when they are clinically appropriate. Some clinicians believe that guidelines and pathways over-emphasise the clinical condition at the expense of individual patient care. In our experience, pathways provide patient-focused care, as they constantly monitor quality, and any deviation from the pathway identifies complications early. The plan of care is clearly defined and shared with the patient; in some instances patients are involved in the development of this plan. Pathways also facilitate discharge planning as the median length of stay is defined. As Dowsey et al and others have shown,1,9 pathways reduce the length of hospital stay without an increase in complications or unscheduled reattendance. In our clinical experience, pathways have been used successfully to coordinate care across the primary-secondary care interface. Chronic conditions such as asthma, obstructive pulmonary disease, diabetes and palliative care have been managed in this way.10 Some hospitals and general practices coordinate care using pathways for investigating and managing patients who present with conditions such as a breast lump or acute rectal bleeding. While few papers have been published, the National Pathways Association in the UK has information on the successful use of pathways in many clinical settings (a website is currently being developed, but is not yet available; Australian readers can contact D J K by emailing Denise. KitchinerATRLCH-TR. NWEST. NHS. UK). Pathways also have a part to play in clinical risk management. When the pathway is developed, current practice is reviewed and the most recent evidence incorporated into the pathway. Potential risks can be identified and procedures established to minimise them. By including these in the pathway, changes in practice can rapidly be communicated to all members of the multidisciplinary team. Analysis of variation from the pathway can be used to monitor areas of potential risk. Poor documentation can fail to indicate whether a guideline has been followed, and this can readily be addressed by the introduction of the pathway. Another aspect of risk management is preventing the recurrence of untoward events. Pathways can include guidelines that ensure all health professionals are aware of potential risks and take appropriate action to prevent them from recurring. The National Pathways Association in the United Kingdom is undertaking research into the factors that contribute to the successful implementation of pathways. Most clinicians involved in this process agree that making changes that lead to improved outcomes requires active involvement from senior medical staff. There must also be a commitment from management to provide resources to establish and run the program, as time is needed to develop pathways and educate staff. Analysis of variation from, and regular revision of, the pathways is also essential to maintain the improvements in clinical practice. The concept of pathways is based on sound principles, but evaluation of their use is essential, and the article by Dowsey and colleagues contributes towards that evaluation. There is a need for further research into the use of pathways, the outcomes that they achieve and the costs involved. Recently, the National Health Service in the UK introduced the concept of Clinical Governance.11 This involves a process of continuous quality improvement for which senior clinicians and managers are directly responsible. It has moved the emphasis from cost containment, as demonstrated in the North American model of managed care, to a process of managing clinical care to improve quality within the resources available. Pathways have been recognised as one option for facilitating this process,12 allowing changes to be driven by clinicians rather than managers. Denise J Kitchiner Consultant Paediatric Cardiologist, and Past Chairman, National Pathways Association Royal Liverpool Children's Hospital, Liverpool, United Kingdom Peter E Bundred Reader in Primary Care, University of Liverpool Liverpool, United Kingdom Dowsey M, Kilgour M, Santamaria N, Choong PFM. A prospective study of clinical pathways in hip and knee arthroplasty. Med J Aust 1999; 170: 59-62. Campbell H, Hotchkiss R, Bradshaw N, Proteous M. Integrated care pathways. BMJ 1998; 316: 133-137. Kitchiner D, Bundred P. Integrated care pathways. Arch Dis Child 1996; 75: 166-168. O'Connor GT, Plume SK, Olmstead EM. A regional intervention to improve the hospital mortality associated with coronary artery bypass graft surgery. JAMA 1996; 275: 841-846. Chassin MR. Quality of health care. Part 3: Improving the quality of care. N Engl J Med 1996; 335: 1060-1063. Dwyer P. Legal implications of clinical practice guidelines. Med J Aust 1998; 169: 292-293. Thomson R, Lavender M, Madhok R. How to ensure that guidelines are effective. BMJ 1995; 311: 237-242. Ward JE, Boyages J, Gupta L. Local impact of the NHMRC early breast cancer guidelines: where to from here? Med J Aust 1997; 167: 362-365. Rossiter DA, Edmondson A, Al-Shahi R, Thompson AJ. Integrated care pathways in multiple sclerosis rehabilitation: completing the audit cycle. Multiple Sclerosis 1998; 4: 85-89. Ellershaw J, Foster A, Murphy D, et al. Developing an integrated care pathway for the dying patient. Eur J Palliat Care 1997; 4: 203-207. Scally G, Donaldson LJ. Clinical governance and the drive for quality improvement in the new NHS in England. BMJ 1998; 317: 61-65. Information for health: an information strategy for the modern NHS. Leeds: NHS Executive, 1998. Make a comment Readers may print a single copy for personal use. No further reproduction or distribution of the articles should proceed without the permission of the publisher. For permission, contact the Australasian Medical Publishing Company. Journalists are welcome to write news stories based on what they read here, but should acknowledge their source as "an article published on the Internet by The Medical Journal of Australia <http://www.mja.com.au>". <URL: http://www.mja.com.au/> We appreciate your comments.

Peter E Bundred

Abstract Objective: To ascertain the effectiveness of clinical pathways for improving patient outcomes and decreasing lengths of stay after hip and knee arthroplasty. Design and setting: Twelve-month randomised prospective trial comparing patients treated through a clinical pathway with those treated by an established standard of care at a single tertiary referral university hospital. Participants: 163 patients (56 men and 107 women; mean age, 66 years) undergoing primary hip or knee arthroplasty, and randomly allocated to the clinical pathway (92 patients) and the control group (71 patients). Main outcome measures: Time to sitting out of bed and walking; rates of complications and readmissions; match to planned discharge destination; and length of hospital stay. Results: Clinical pathway patients had a shorter mean length of stay (P = 0.011), earlier ambulation(P = 0.001), a lower readmission rate (P = 0.06) and closer matching of discharge destination. There were beneficial effects of attending patient seminars and preadmission clinics for both pathway and control patients. Conclusion: Clinical pathway is an effective method of improving patient outcomes and decreasing length of stay following hip and knee arthroplasty. Introduction The past two decades have seen an 85% rise in Australian health costs to 36.6 billion dollars, with the largest proportion of this expended in acute hospital care.1 Newer health policies now incorporate measures to rationalise and improve the efficiency of many services. Such policies, however, are economically driven and frequently fail to consider the optimum level of service required by the community.2 Treatment protocols, variously known as clinical pathways, critical pathways and care paths, that aim to streamline and standardise management through a systematic approach so that high quality care may be provided in a timely and cost effective manner3,4 have been developed. Clinical pathways describe the course of hospitalisation for patients with a specified illness and encompass a predetermined plan of treatment. The use of clinical pathways is now well established and their successes are widely reported.5-7 Joint arthroplasty is a common and costly procedure associated with high resource use that is frequently performed in the elderly who may have many coexisting morbidities. These characteristics suggest that joint arthroplasty may be a suitable procedure to incorporate into a clinical pathway.8 As part of a "best practice" initiative in line with quality assurance activities at St Vincent's Hospital, the hospital's Orthopaedic Service has developed clinical pathways for hip and knee joint arthroplasty for treating osteoarthritis which aim to maximise the use of all available resources and minimise negative patient outcomes, thereby improving patient care. To this end, we report the effects of introducing clinical pathways at our hospital on quality indicators such as mobilisation, complication rates, discharge planning and readmission rates while also exploring the impact on length of stay. Methods We used a prospective randomised control group design to compare the outcomes of patients who underwent hip or knee joint arthroplasty at St Vincent's Hospital, Melbourne (a tertiary referral hospital affiliated with the University of Melbourne), between 1 January 1996 and 30 December 1997. All such patients were randomly allocated to either the control or clinical pathway group by a clerical assistant who was blinded to their demographic and clinical profiles. Diagnostic category and comorbidities had no bearing on the allocation of patients to either the pathway or control groups, but patients were excluded from the study after randomisation if they were having revision arthroplasty, simultaneous bilateral joint arthroplasty, arthroplasty for acute trauma or complex tumour surgery. The management of patients undergoing joint arthroplasty at St Vincent's Hospital, Melbourne, is outlined in Box 1. Outcome measures Length of stay (calculated from the time of the patient's admission to the time of discharge and expressed in days); Time to sitting out of bed and ambulation (time between surgery and the patient's first day of sitting out of bed or walking with assistance); Complications (wound infections, including all wound erythema lasting more than 24 hours, chest infections, deep vein thrombosis [DVT] as diagnosed by clinical features and confirmed by ultrasonography, joint dislocation, decubitus pressure areas, failure to cope at home and a decreased range of motion after discharge); Readmission (for complications during a follow-up period of three months from discharge); and Discharge matching (between the presumptive discharge destination given at the preadmission clinic and the patient's postdischarge destination). Clinical pathway and control patients Patients randomly allocated to the clinical pathway received proactive treatment whereby specific goals were set each day for the patient and treating team. Their hospital records included a special written protocol which listed milestones to be achieved, identified tests that should be ordered, set daily tasks for patients and members of the treating team, and provided space for documenting any variation in treatment or patient response. Each intervention was signed by the treating health professional and the discharge plan was re-evaluated daily to ensure it remained realistic and appropriate to the patient's needs. The clinical pathway formalised in writing the participation of the various members of the treating team. Patients not allocated to the pathway received "reactive" treatment whereby the treating team responded to the will and condition of the patient in providing postoperative care. Statistical analysis Results were analysed with SigmaStat V2 software.9 Data were compared using t tests for independent groups and multiple linear regression where appropriate. We used the z test for comparisons of proportions between groups. As the data for length of stay (LOS), time to sitting out of bed and time to ambulation were not normally distributed, these data were transformed using a logarithmic transformation before analysis with t tests. We calculated the sample size for this study after reviewing all hip and knee arthroplasty patient data for 1995, which showed a mean LOS of 13 days (range, 5.8-43.3; SD, 5.3). We believed that a 20% reduction in LOS (2.6 days) would represent a clinically significant outcome. Therefore, we calculated that to detect a reduction of 2.6 days in LOS at a significance level of 0.05 with a power of 0.8 would require two groups with a minimum of 65 subjects in each group. Results During the study period 175 patients underwent hip or knee joint arthroplasty and were randomly allocated to the pathway (94 patients) and control (81 patients) groups. Twelve patients were then excluded by the crtiteria listed in the methods, leaving 163 patients -- 92 in the clinical pathway group and 71 in the control group. The sample comprised 56 men and 107 women, with a mean age of 66 years (range, 67-93 years). All patients were followed for a minimum of three months and none were lost to follow-up. Our findings are summarised in Box 2. There was no significant difference between control and pathway patients in terms of age or weight. Although the clinical pathway group included more patients with premorbid conditions than the control group, this difference was not statistically significant (95% CI, - 0.03 to 0.21). Length of stay (LOS) was significantly shorter for the pathway group than for the control group (t = 2.585; P = 0.011). When LOS was analysed for the subgroups of patients in each group with premorbid conditions, this was still significantly shorter for the pathway group than the control group (t = 3.152; P = 0.001) despite the larger number of patients with premorbid conditions in the pathway group. Patients in the clinical pathway group sat out of bed and walked earlier after surgery than control patients. Multiple linear regression for each group showed that time to ambulation was the only significant contributor to reduction in log LOS in the clinical pathway group (time to ambulation -- coeff = 19.6, standard error [SE] = 9.6, P = 0.04; time to sitting out of bed -- coeff = - 4.35, SE = 9.3, P = 0.64, R2 = 0.127). Neither time to ambulation nor time to sit out of bed was significantly associated with reduced log LOS in the control group (time to ambulation -- coeff = 21.05; SE = 26.28, P = 0.42; time to sit out of bed -- coeff = - 4.13, SE = 28.54, P = 0.88, R2 = 0.0251). Patients from both the clinical pathway and control groups who attended either the preadmission clinic (n = 122) or the patient information seminar (n = 61) had a shorter LOS (7.22 days and 6.84 days, respectively) than patients who attended neither (n = 36; LOS, 8.55 days). The 54 patients who attended both the clinic and seminar had the shortest LOS at 6.6 days, and t tests showed that the shorter LOS for these patients relative to those who attended neither the clinic nor seminar was significant (t = 2.66; P = 0.009). Post-hoc t tests showed that the shorter LOS for patients who had attended both preadmission clinics and information seminars relative to those who had attended neither was significant (t = 2.66; P = 0.009). Box 2 shows that a greater proportion of clinical pathway patients were discharged to their planned discharge destination than control patients (95% CI, - 0.05 to 0.23), and that there were fewer readmissions in clinical pathway patients (95% CI, 0.006-0.174), although neither result was statistically significant. However, there were significantly fewer complications in clinical pathway patients (95% CI, 0.036-0.27). Discussion We found that a clinical pathway for hip and knee joint arthroplasty had a beneficial impact on the duration of admission, with patients on the pathway having a 1.5-day shorter stay than control patients. The seven-day LOS for our pathway patients compared favourably with that of Gregor et al,10 who showed a reduction in LOS from 12 to nine days for pathway patients. Length of stay was significantly shorter for the pathway group than the control group despite the larger proportion of pathway patients with premorbid conditions. This result should be interpreted cautiously, as the small overall number of patients with premorbid conditions meant that the test had less than optimal power (0.45). However, we conclude that comorbidities per se should not exclude patients from clinical pathways. Patients with comorbid conditions may actually be better served because of the greater fastidiousness and vigilance imposed by the daily protocol. While our findings that there were fewer complications and readmissions in clinical pathway patients were not significant, we believe that given the appropriate number of subjects in future studies both of these areas may approach significance. We noted that reducing the length of stay did not increase the complication rate, a finding corroborated by others.11 In addition, the readmission rate for complications for pathway patients was one-third that of controls. This contrasts with some studies which have reported an inverse relationship between length of stay and readmission rates.11 We, like other authors,12 believe that it is a lower quality of care and not length of stay per se that increases the risk of unplanned readmission. Discharge planning is an important part of the clinical pathway which appears to be closely linked with the length of stay. Appropriate matching of predetermined discharge destinations is a correlate of shorter admissions. If we are able to improve on our destination matching rate of 70%, we may be able to further reduce our length of stay, thereby making more resources available for other patients. Education of patients and their relatives appeared to have a positive influence on the patients' recovery after joint arthroplasty, with earlier mobilisation and discharge from hospital. Attending information seminars and preadmission clinics assisted in reducing the length of stay by almost two days. Patients and their relatives who understand the disease and the necessary treatment may be in a better position to assist with care and rehabilitation. Attendances for our information seminar and preadmission clinic were 38% and 74%, respectively, and we are endeavouring to increase these. First introduced by the New England Medical Center, clinical pathways are now incorporated into the management philosophy of many hospitals worldwide.13,14 Pathways involve input from medical, nursing, paramedical and administrative staff, and reflect the expertise of all members of the healthcare team while highlighting the interdependent nature of these roles in achieving positive outcomes for patients.15 A valuable subsidiary purpose of pathways is in providing information from which the financial cost of care may also be derived.16 Accurate costing of treatment is fundamental to the operation of institutions where prospective payments are made in accordance with diagnosis-related groups (DRGs), standardised lengths of stay and fixed reimbursement for care. Clinical pathways thus provide an important tool for coordinating and managing clinical resources. However, the driving force behind clinical pathways must remain the need to improve the quality of care and patient outcomes, and not their utility as a tool to ensure that budgetary demands are met. We are encouraged by our findings, which indicate substantial improvements for patients on a clinical pathway. To our knowledge, no other study has investigated the effect of clinical pathways on joint arthroplasty using a contemporaneous control group. 1 Management of joint arthroplasty patients at St Vincent's Hospital, Melbourne Preadmission clinics Preoperative review for patients undergoing elective joint replacement involves a multidisciplinary approach and includes medical, nursing, physiotherapy and occupational therapy consultation and anaesthetic and social work screening. Preexisting conditions are identified and testing and treatment are undertaken to achieve an optimum level of preoperative health. A discharge destination is determined based on medical and projected rehabilitation needs. Appropriate referrals are initiated. Patient information seminars Groups of patients and their families are invited to attend an information seminar about the surgery. The surgeon explains the aetiology of the disease, principles of management, nature of potential risks and their prevention. The nursing staff discuss acute postoperative care, including pain relief, pressure and wound care, intravenous therapy, and prophylaxis for deep venous thrombosis. The physiotherapist discusses the regimen of postoperative exercises, cautions and mobilisation. The occupational therapist describes the availability and use of various personal aids which assist the patient in preventing complications such as falls, injury or dislocation. Patients are able to raise any questions related to their surgery. Patients and their families are encouraged to take an active role in the postoperative management, and are acquainted with their very important role in the postdischarge phase. All members of the team stress the philosophy that the primary intention is to return patients home in preference to a rehabilitation hospital after the surgery. Discharge Patients are discharged home or to a rehabilitation unit. For those discharged home, community nursing care is provided at regular intervals for the first three weeks after discharge. Community nurses pay special attention to the nature of the patient's wounds, their exercise regimen and general medical condition. Any concerns are immediately related to the medical staff for further attention. Patients are followed up on a regular basis in the outpatient department. 2 References MacIntyre CR, Brook CW, Chandraraj E, Plant AJ. Changes in bed resources and admission patterns in acute public hospitals in Victoria, 1987-95. Med J Aust 1997; 167: 186-189. Parry TG. Health expenditure in Australia -- the current dilemma. Med J Aust 1992; 156: 592-594. Wigfield A, Boon E. Critical care pathway development: the way forward. Br J Nursing 1996; 5: 732-735. Grudich G. The critical path system. AORN J 1991; 53: 705-714. Gouveia WA, Massaro FJ. Critical pathway experience at New England Medical Center. Am J Health-Syst Pharm 1995; 52: 1068-1070. Saltiel E. Critical pathway experience at Cedars-Sinai Medical Center. Am J Health-Syst Pharm 1995; 52: 1063-1068. Stevenson LL. Critical pathway experience at Saratosa Memorial Hospital. Am J Health-Syst Pharm 1995; 52: 1071-1073. Leininger SM. Tools for building a successful orthopaedic pathway. Orthop Nurs 1996; 15: 11-19. SigmaStat [computer program]. Version 2. San Rafael, CA: Jandel Scientific Software, 1995. Gregor C, Pope S, Werry D, Dodek P. Reduced length of stay and improved appropriateness of care with a clinical path for total knee or hip arthroplasty. Joint Commiss J Qual Improv 1996; 22: 617-628. Rushworth RL, Rob MI. Readmissions to hospital: the contribution of morbidity data to the evaluation of asthma management. Aust J Public Health 1995; 19: 363-367. Ashton CM, Kuykendall DH, Johnson ML, et al. The association between the quality of inpatient care and early readmission. Ann Intern Med 1995; 122: 415-421. Zander K. Managed care within acute care settings: design and implementation via nursing case management. Health Care Supervisor 1988; 6: 27-43. Bower KA. Managed care: controlling costs, guaranteeing outcomes. Definition 1988; 3: 14. Heacock D, Brobst RA. A multidisciplinary approach to critical path development: a valuable CQI tool. J Nurs Care Qual 1994; 8: 38-41. Weilitz PB, Potter PA. A managed care system. Financial and clinical evaluation. J Nurs Admin 1993; 23: 51-7. (Received 27 Jan, accepted 20 Aug, 1998) Authors' details Department of Orthopaedics, St Vincent's Hospital, Melbourne, VIC. Michelle M Dowsey, BN, GradCertOrth, Clinical Nurse Specialist; Meredith L Kilgour, BN, GradDipAdvClinPrac, Nurse Unit Manager; Nick M Santamaria, BAppSc, PhD, Director of Nursing Research; Peter F M Choong, MD, FRACS, Professor, and Director of Orthopaedics. Reprints: Professor P F M Choong, Department of Orthopaedics, St Vincent's Hospital, 41 Victoria Parade, Fitzroy, VIC 3065. Email: PeterChoongATc031.aone.net.au

Michelle M Dowsey · Meredith L Kilgour · Nick M Santamaria

Viewpoint Rethinking the early childcare agenda Who should be caring for very young children? Peter S Cook MJA 1999; 170: 29-31 Introduction - High-quality childcare - Evidence of undesirable outcomes - Being with mother - Many mothers want to care for their own children - A rethink is needed - Acknowledgement - References - Authors' details - - More articles on Paediatrics Introduction In Western societies, mothers often seek paid employment because of societal or economic pressures or a desire to continue a career, and place their infants in childcare centres. There is a perception that trained carers can rear children as well as, or perhaps better than, the mothers themselves.1 The Australian Child Care Task Force2 has recommended subsidised expansion of the "childcare industry", saying that all families should have access to affordable, high quality childcare by trained, professional carers. "Childcare" in this article refers to institutional day centre care, but in research studies it may variously mean any regular non-maternal care or non-parental care. Theoretically, children can spend as many hours in childcare by the age of five as they will spend in school over the next 12 years.3 I argue here that for children up to 2½ to 3 years of age, and particularly during infancy, this agenda of subsidised, universally available, high quality professional childcare is misconceived, and a rethink is needed. Evidence suggests that this agenda: Is unrealistic (eg, high quality childcare for all is not affordable); Overlooks accumulating evidence of risks of undesirable outcomes sometimes associated with early childcare; Is contrary to much expert opinion about what is likely to be best for infants; Is contrary to the desire of many working mothers to care for their own children, if they could afford it; and Relies partly on the now-discredited ideology of cultural determinism. High-quality childcare for all is unrealisable Morgan concluded that "Affordable care is low-quality care" and the "difficulties and cost of providing good quality care, with its highly involved and trained staff, small group size, caregiver stability and low infant to caregiver ratios, should surely demonstrate how 'affordable, universally available, good-quality, easily accessible childcare' . . . is a chimaera, unrealisable in the real world."1Australian standards require one carer for five infants under two, which professionals consider inadequate.1,4,5 Moreover, although Australian governments subsidise 60% of childcare costs,2 Loane found "mediocrity more prevalent than excellence",4 reporting that an assessment of half of Australia's 2400 childcare centres showed 13% failed the national accreditation3 and 40% achieved only the minimal standard, with frequent inadequacies in areas such as child management, safety, health, and nutrition.4 Evidence of undesirable outcomes, sometimes independent of quality Evidence about the effects of childcare, beneficial or harmful, is incomplete and sometimes contradictory. Research into outcomes (whether by standardised tests, or behavioural or socioemotional ratings) is inherently complex, with imperfect instruments, and many confounding variables. Longitudinal studies, showing longer term outcomes, require dedication, expertise, time and money. The interpretation of outcome studies has been hotly debated.6-9 While many infants in childcare apparently thrive, Morgan has reviewed the "mounting evidence of adverse side-effects",1 and some of the evidence pointing to risks is outlined here. Not surprisingly, children in childcare have an increased risk of infectious diseases,10 but the psychological effects are of most concern, as the foundations of the human mind and emotional development are laid in these early years.11 An enduring aspect of the child's world is the parent-child relationship, and one central feature of this relationship is the infant-mother attachment. As mammals, secure attachments between infants and their mothers (and/or effective surrogate mothers) have been vital for our species' survival.7,8,12 Research shows that the security or insecurity of this attachment provides the foundation upon which subsequent relations with adults and peers are built.12 According to Rutter, moderate but significant associations have been found between insecure attachment and various forms of psychopathology both in childhood and adult life.13 To settle some controversies, a multicentre, longitudinal US childcare study is currently investigating the influence and interactions of selected variables on childcare outcomes. These variables include child's sex and temperament, mother's psychological adjustment and sensitivity in the home and at play, and type of childcare, age of child at entry, amount and stability of childcare, and childcare quality assessed for the individual child. This study has established that the security of infant-to-mother attachment can be reliably and validly assessed at 15 months of age.14 Some findings associated with increased risk are shown in the Box. While some of these differences were modest or small, they were consistent in direction. Further analysis through the course of this major study may illuminate the longer-term significance of these findings. Meanwhile, although earlier research had limitations (eg, sample bias and lack of standardised measures of childcare quality), a meta-analysis17 of the 101 childcare outcome studies from many countries published in peer-reviewed journals between 1957 and 1995 found robust evidence of adverse outcomes associated with non-maternal care in the areas of children's infant-mother attachment security, their socioemotional development (including increased anger, anxiety, and hostility in boys, and overdependency, anxiety, and depression in girls), and in their behaviour (including hyperactivity, aggression and non-compliance). They found no support for the belief that high quality day care is an acceptable substitute for parental care. Statistical analysis of group findings can obscure individual reactions. Harsman18 studied 26 infants before they commenced Swedish quality long daycare centre at ages ranging from 6 to 12 months. She followed them through five months in childcare, comparing them with 26 controls (matched pairwise for age, sex and socioeconomic background) cared for by their mothers. Although many infants adjusted easily to childcare, at one stage 11 of the children were assessed as "sad and depressed" in the childcare situation. By the end of the study, the childcare group showed significantly lower scores than the mother-care group in the hearing, speech, and personal-social subscales of the Griffiths' Mental Development Scale.18 Space precludes discussion of the adverse effects on parents, but many mothers in two-income families are overloaded and "stressed-out".1,2 Being with mother is likely to be best This childcare agenda, in disregarding the child's age, is contrary to much expert professional opinion that, ideally, it is likely to be best for very young children to be mostly with their mothers. Of 904 professional members of the World Association for Infant Psychiatry and Allied Disciplines from 56 countries, 402 responded anonymously to a survey asking what kinds of care, at various ages up to 36 months, they considered likely, ideally, to be best from the infants' viewpoint.19 A majority of the respondents believed that it is "very important" for infants "to have their mothers available to them through most of each 24 hours" for more than one year, and to be cared for "principally by mother" until over two years. Only 11% selected full-day group care as the best option for children aged up to 30 months. The author concluded: "The findings show that the polled professionals consider that the development and well-being of children under 3 would be served best by patterns of care that are diametrically opposed to those politicians promise, policy-makers aspire to provide and parents strive to find".19 Many mothers want to care for their own children According to extensive surveys of mothers seeking or using childcare in order to work, many mothers would prefer to care for their young children at home if they could afford to do so.1,20,21 Moreover, in 1993, 65% of Australians reportedly thought it preferable that mothers of preschool children should not take paid employment outside the home.22 Yet when, as in Australia, taxation systems largely disregard childrearing costs23 and favour two-income families, the latter can outbid single-income families in acquiring homes. Prices rise to the level the market will bear and, to compete, more mothers seek paid employment and childcare.1,24 Childcare subsidies aggravate this vicious circle, unless balanced by equal help to home-caring parents through "family-friendly" taxation policies.23,25 A rethink is needed This childcare agenda relies partly on the now-discredited ideology of cultural determinism,26-28 which taught that human nature is culturally determined by social conditioning, denying evolutionary and biological influences. Yet the needs of infants and their mothers, as mothers, are based in our genes and cannot be refashioned to suit ideologies. We need social patterns of support for parenting which respect the human givens, recognising that we each have a pedigree of mothers who, overall (through millions of years), were selected for success in all the essential processes of primate mothering -- including childbirth, breastfeeding, and bonding/attachment, as well as the carrying and rearing of a baby girl who would grow up to do likewise -- not in isolation but within a related social group.8,29,30 Research increasingly illuminates the long-term significance of optimal early maternal nurture for healthy cognitive, emotional and physical development.11,31-35 The precautionary principle -- primum non nocere -- is fundamental in healthcare. Large-scale institutional, long-daycare rearing of babies and very young children by professionals offering no continuing relationship with them is without successful precedent in the history of our species. When the evidence and professional opinion agree that mothers are the best people to care for their young children, it seems neither wise nor cost-effective15 for governments to spend large sums of money subsidising childcare for mothers who would prefer to be helped to care for their infants themselves. Perhaps "How can we provide quality childcare for everybody?2" asks the wrong question. Taking into account the biologically determined needs of young human beings and their mothers, we should be asking "How -- in our detribalised societies -- can we best help and support those parents who wish to do a mutually satisfying job of mothering and fathering their infants and young children without jeopardising their own futures?". Some proposals have been offered,1,8,20,23,30,36 and I suggest that if some of the resources directed towards providing childcare were creatively redirected to supporting high quality parenting we would be more likely to achieve our real goal of enhancing the well-being of mothers, young children, and society. Acknowledgement I am indebted to Professor Jay Belsky, Distinguished Professor of Human Development and Family Studies at Pennsylvania State University, for his generous willingness to communicate with me, but responsibility for the text is mine. References Morgan P. Who needs parents? The effects of childcare and early education on children in Britain and the USA. London: Institute of Economic Affairs, 1996: 1-15, 48-58, 90-98, 114-118. Economic Planning Advisory Commission Child Care Task Force. Future child care provision in Australia. Canberra: AGPS, 1996: xv, xvi, 16, 37. National Childcare Accreditation Council. Putting children first: quality improvement and accreditation system handbook. Sydney: National Childcare Accreditation Council, 1993. Loane S. Who cares? guilt, hope and the child care debate. Melbourne: Reed, 1997: 120-152. Hope D. Spare the non-maternal care and nurture the child. The Australian 1998 4 June. Belsky J. Consequences of child care for children's development: a deconstructionist view. In: Booth A, editor. Child care in the 1990s: trends and consequences. New Jersey: Lawrence Erlbaum, 1992: 83-94. Karen R. Becoming attached: unfolding the mystery of the infant-mother bond and its impact on later life. New York: Warner, 1994. Cook PS. Early child care -- infants and nations at risk. Melbourne: News Weekly Books, 1997: 26-31, 76-89, 154-158, 182-190. Ochiltree G. Effects of child care on young children: forty years of research. Melbourne: Australian Institute of Family Studies, 1994. (Early childhood study paper No. 5.) Ferson MJ. Control of infections in child care. Med J Aust 1994; 161: 615-618. Cockburn F. The minds of our children: sensory input and the development of the human infant brain and mind. The British Association of Perinatal Medicine Founder's Lecture. Proceedings of the XVth Congress of Perinatal Medicine; Sep 1996; Glasgow. London: Parthenon, 1997: 53-60. Belsky J, Cassidy J. Attachment: theory and evidence. In: Rutter M, Hay D, editors. Development through life: a handbook for clinicians. Oxford: Blackwell Scientific Publications, 1994: 373-402. Rutter M. Clinical implications of attachment concepts: retrospect and prospect. J Child Psychol Psychiatry 1995; 36: 549-571. National Institute of Child Health and Human Development. Early Child Care Research Network. The effects of infant child care in infant-mother attachment security: results of the NICHD study of early child care. Child Dev 1997; 68: 860-879. Belsky J. Early childcare, parenting, and the parent-child relationship. Invited testimony delivered to the US Senate Subcommittee on Children and Families, 23 Jan 1998. National Institute of Child Health and Human Development. Early Child Care Research Network. Mother-child interaction and cognitive outcomes associated with early child care: results of the NICHD study up to 36 months. Bethesda, Maryland: NICHD, April 1997. Violato C, Russell C. A meta-analysis of the published research on the effects of non-maternal care on child development. In: Violato C, Genuis M, Paolucci E, editors. The changing family and child development. London: Ashgate. In press. Harsman I. Dagliga separationer och tidig daghemsstart. (Daily separations and early entry into day care). Stockholm: HLS Forlag, 1994 (ISBN 91-7656-334-0). Leach P. Infant care from infants' viewpoint: the views of some professionals. Early Dev Parent 1997; 6: 47-58. Leach P. Children first: what society must do -- and is not doing -- for children today. Harmondsworth, Middlesex: Penguin, 1994: 68-102: 240-265. Vandenheuvel A. Mothers with young children: should they work? Do they want to work? Family Matters 1991; 30: 47-49. (Melbourne: The Australian Institute of Family Studies.) Evans MDR. Norms on women's employment over the life course: Australia 1989-1993. Worldwide Attitudes, International Social Science Survey, Australia, ISSN 1323-9589, Canberra: Research School of Social Sciences, Australian National University, 1995. Sullivan L. Tax injustice: keeping the family cap-in-hand. Sydney: Centre for Independent Studies, 1998. (Issue analysis No. 3.) Ochiltree G, Edgar D. Today's child care, tomorrow's children. Melbourne: Australian Institute of Family Studies, 1995. (Early childhood study paper No. 7.) Casey DJ. Economic justice for the family. The Australian Family 1996; 17(3): 11-17. (Melbourne: The Australian Family Association.) Freeman D. The debate at heart is about evolution. In: Fairburn M, Oliver WH, editors. The certainty of doubt: Tributes to Peter Munz. Wellington: Victoria University Press, 1996. Freeman D. Margaret Mead and the heretic: the making and unmaking of an anthropological myth (Foreword). Melbourne: Penguin, 1996: vi-xiv. Freeman D. The fateful hoaxing of Margaret Mead: an historical analysis of her Samoan researches. Boulder, Colo: Westview, 1998. Werner EE. Infants around the world: cross-cultural studies of psychomotor development from birth to two years. J Cross-Cult Psychol 1972; 3: 111-134. Cook PS. Childrearing, culture and mental health: exploring an ethological-evolutionary perspective in child psychiatry and preventive mental health, with particular reference to two contrasting approaches to early childrearing. Med J Aust 1978; Spec Suppl 2: 3-14. Lucas A, Morley R, Cole TJ, et al. Breast milk and subsequent intelligence quotient in children born pre-term. Lancet 1992; 339: 261-264. Prescott JW. Affectional bonding for the prevention of violent behaviors: neurobiological, psychological, and religious/spiritual determinants. In: Hertzberg AJ, et al, editors. Violent behavior, Vol 1: Assessment and intervention. New York: PMA Publishing, 1990: 110-142. Prescott JW. The origins of human love and violence. J Prenat Perinat Psychol 1996; 10(3): 143-188. Higley JD, Thompson WW, Champouz M, et al. Paternal and maternal genetic and environmental contributions to cerebrospinal fluid monoamine metabolites in Rhesus monkeys (Macaca mulatta). Arch Gen Psychiatry 1993; 50: 615-623. Meaney MJ, Bhatnagan S, Dioria J, et al. Molecular basis for the development of individual differences in the hypothalamic-pituitary-adrenal stress response. Cell Mol Neurobiol 1993; 13: 321-347. Cook PS. Antenatal education for parenthood, as an aspect of preventive psychiatry: some suggestions for programme content and objectives. Med J Aust 1970; 1: 676-681. For comment see Slack-Smith et al's Letter to the Editor 2 August 1999 Authors' details 62 Greycliffe Street, Queenscliff, NSW 2096. Peter S Cook, FRANZCP, MRCPsych, Child Psychiatrist (retired). Reprints: Dr P S Cook, c/o PO Box 84, Repton, NSW 2454. Email: pcookATmidcoast.com.au ©MJA 1999 © 1999 Medical Journal of Australia. Some findings of a major longitudinal childcare study in the United States Analysis of children aged 15 months found:14,15 Quality of care was important, assessed, not globally, but by how sensitive, responsive, affectionate and (cognitively) stimulating the carers were in the individual carer-child relationship. Children in lower quality childcare risked adverse outcomes.15 Evidence for whether quality childcare compensated for lower quality maternal care was mixed, but the less time children of insensitive mothers spent apart from them in childcare the more likely they were to be securely attached. Regardless of childcare quality and other variables, boys in more than 30 hours of non-maternal care per week had an increased risk of insecure attachment. Infants whose mothers rated in the lowest 25% for "sensitivity" (summarising extensive observational assessments) had an increased risk of insecure attachment if they had over 10 hours' non-maternal care per week. Childcare of low quality, or instability (more than one change of arrangement), each independently increased an infant's risk of insecurity. Separate risk factors appeared to be cumulative in their effects. Analysis of children aged 36 months found:16 Family and child characteristics were major influences in predicting outcomes, both in mother-child relationships and in cognitive and language areas. Childcare variables had smaller, but consistent, additional effects on mother-child relationships. Poorer-quality childcare had adverse influences, and more hours in non-maternal care (mean weekly hours recorded across 0-6, 0-15, 0-24, and 0-36 months) were associated with less sensitive and engaged mother-child interactions across the first three years, and with the child showing less affection towards the mother at 24 and 36 months. Back to text

Peter S Cook

Medical Research Perspectives Medical research in New South Wales 1993-1996 assessed by Medline publication capture Emmanuel J Favaloro MJA 1998; 169: 617-622 Abstract - Introduction - Methods - Results - Discussion - Conclusions - Acknowledgements - References - Author's details - - More articles on Informatics and computers Abstract Objectives: To assess medical research publication output in New South Wales (NSW). Design: Analysis of publication information from the Medline indexing database, 1993-1996 inclusive. Setting: Teaching hospitals and affiliated universities and medical research institutes within NSW, the major sites for NSW medical science publications. Major outcome measures: Cumulative number and location of Medline-identified publications; journal citation indices (impact factor and immediacy index). Results: 8860 published articles were captured for the analysis period. Universities and hospitals accounted for most of the publications (n = 7755). A mean of 73.1% (range, 36%-100%) of all articles were published in overseas journals, and the rest in Australian journals. This average trend applied to most universities and teaching hospitals, whereas research institutes published almost exclusively in overseas journals. Average publication impact factor values for most universities and teaching hospitals were around the average value for all NSW publications (2.203). The range for teaching hospital publications was 1.000-2.823, but for the overseas-publishing medical research institutes it tended to be higher (2.480-5.423). Immediacy index data yielded similar findings. Conclusions: The universities and teaching hospitals account for most of the medical publications arising from NSW, and also those appearing in Australian journals. Thus, these sites provide the bulk of Australian medical practice end-user information. In contrast, the medical institutes concentrate on publishing in overseas journals with higher and quicker citation rates (higher impact factor and immediacy index). Introduction The Medline database can be used to capture research publications arising from within one institution or the search can be expanded to include, for example, all Medline-held publications from one State. Further, to help analyse publication activity, publication data derived from Medline searches can be merged with markers of publication citation, such as "impact factor" and "immediacy index". This latter information comes from the Institute for Scientific Information (ISI; Philadelphia, USA), which catalogues most of the major research journals in Science Citation Index (SCI) publications,1 and publishes "impact factor" and "immediacy index" data. Data on impact factors are often also used as surrogate markers of publication "quality", although there is much debate about the validity of this approach.2-5Recently, Bourke and Butler analysed individual article citation rates as a measure of basic medical and health sciences research in Australia and concentrated largely on universities and high profile research institutes.6 Although these authors have produced several other reports analysing Australian research activities,7 none has looked specifically at teaching hospitals, "affiliated" research institutes (defined as the "research arm" of the hospital) and associated universities within New South Wales (NSW). This article reports the results of such a sampling analysis. Methods A complete description of the methods used is beyond the scope of this report. In brief, the Medline publication indexing database (Silverplatter version) was used to capture "quantitative" research publication information. This database indexes most major journals in medical and related fields (veterinary, pathology and cell science), and each publication indexed includes the primary author's address. A hospital-affiliated medical research institute was defined as such if more than a third of its publications included the teaching hospital as part of the Medline address field. That is, the medical research institute itself, and its researchers, clearly recognised the affiliation within the context of the publication. Adoption of this strict criterion resulted in exclusion of some research institutes, or their not being identified as hospital-affiliated sites, despite being "popularly perceived" as affiliated with a particular teaching hospital. The teaching hospitals, their affiliated universities and medical research institutes included in this report are listed in Box 1. Data capture: The approach which was found to best capture publication data was to use (i) general ("primary") locality markers (ie, the terms "New South Wales", "NSW", "Sydney"), and (ii) separate specific ("secondary") locality markers (ie, names of "suburbs" in which the medical research organisations were located). This led to more complete capture of relevant publications than use of specific organisational names because of inconsistencies in the organisational names in the publications (eg, University of Sydney v. Sydney University, etc). Captured data were then merged with journal citation data. Years of analysis: Medline capture and analyses were conducted for the years 1993 to 1996 (inclusive), as these were the most recent four consecutive years for which SCI-published impact factor and immediacy index information was available. Subsequent analysis: Applicable publications were downloaded to a personal computer, and a composite database was constructed specifically for analysis of derived information. Author's address: Author's address, and thus research institution location, was defined essentially as indicated by the downloaded author's address and Medline publication information, always attempting to be as objective as possible. If a publication noted Sydney University as the author's address, then Sydney University was the designated publication address. Where multiple authors' addresses were noted then the address was "shared" (Box 2). Analysis of research output and outcome measures: Research output can be assessed in various ways according to its underlying purpose. Thus, several objective analyses were undertaken to answer separate questions, including: Gross research (publication) output of medical or related subjects -- this is assessed by the total number of publications captured; Journal publication patterns -- assessed by analysis of journal citation data using impact factor and immediacy index (Box 3) (only available for certain publications); and Relevance to Australian medical practice -- assessed by analysis of the number and proportion of papers published in Australian versus overseas journals. Results Publication output The composite NSW-derived Medline-captured database (1993-1996 inclusive) showed that "medical, veterinary, pathology and cell science" researchers (having given one of various localities within NSW as their address) published 8860 articles in this period. A total of 7755 of the NSW-based publications captured by Medline arose from the universities and hospitals. Figure 1 shows data for teaching hospitals and research institutes with more than 35 publications, and Figure 2 shows data for universities affiliated with these research sites. Figure 1: Medline-captured publications arising from NSW teaching hospitals and medical research institutes (1993-1996 total; only those sites with more than 35 publications over this period are shown). Data shown as a composite bar graph for those hospitals with an affiliated research institute (as defined in Methods). POWH=Prince of Wales Hospital. Figure 2 (inset): Medline-captured publications arising from NSW universities affiliated with the research sites in Figure 1 (1993-1996 total). Overseas v. Australian publication More than 70% (73.1%; range, 36%-100%) of the research publications from NSW researchers appeared in overseas journals and the remainder in Australian journals, with a similar division evident across different hospital and university sites (Figure 3). In contrast, the medical research institutes tended to publish almost exclusively in overseas journals. Figure 3: Medline-captured publications arising from NSW research. Percentage of journal articles in Australian journals v. overseas journals; data shown are 1993-1996 average. Data shown separately for the hospitals, universities and research institutes in Figures 1 and 2. POWH=Prince of Wales Hospital. Journal citation data Excluding publications not listed in the SCI1 publication statistics, the NSW-based average impact factor (all NSW Medline-captured journal publications) was 2.203 (1993-1996 averaged). Averaged impact factor and averaged immediacy index data for each research organisation are shown in Figure 4. For comparison, data for hospital, university and medical research institute sites are shown separately. Figure 4: Average impact factor and immediacy index (1993-1996 average) for Medline-captured publications arising from NSW research. Data shown separately for the hospitals, universities and research institutes in Figures 1 and 2. (Average impact factor = cumulative impact factor of all journal publications for each research site divided by total number of journal articles captured for that site. Average immediacy index = cumulative immediacy index of all journal publications divided by total number of journal articles captured for that site.) POWH=Prince of Wales Hospital. Average impact factor values for most hospital sites (around 2) are similar to those generated from each of the affiliated universities. Indeed, the "all hospital average" impact factor was similar to the "all university average" impact factor. In general, the research institutes' tendency to publish in overseas-based journals increased their impact factor averages (Figure 4). The pattern of immediacy index data closely followed the pattern observed for impact factor (Figure 4). Discussion General findings This report confirms the importance of the NSW teaching hospital system in ongoing medical research and teaching activity. Together with their affiliated universities, these sites provided the great bulk of medical publications arising from NSW. While the research institutes tended to target "international" journals directed at specialised scientific research, teaching hospitals and their affiliated universities targeted Australian journals as well. This means that the "non-research institute" sites play the predominant role in providing local educational support to Australian health practitioners via journals published and widely read within Australia. Although publishing in Australian journals often carries less international "prestige" or "visibility" than publishing in overseas journals, Australian publications play an important role in education of medical, scientific, nursing and allied health practitioners. Furthermore, Australian publications have particular relevance to Australian medical practice, with reporting of specific local data or locally relevant issues (eg, local epidemiological or local infectious disease data). Advantages and disadvantages of the method Data were collected by a well recognised and accepted method of capturing publication information. The Medline database has previously been used with success in bibliometric studies to show publication trends,8-10 and has been consistently shown to provide the strongest health discipline indexing coverage when compared with other databases.11-15 Based largely on internal comparative research estimates, the method used would be expected to capture in excess of 60% of the published research output from NSW medical researchers, and is thus only an approximation of the level and scope of all such activity. Missing would be: Valid research publications not indexed by any indexing service (eg, reference book chapters, articles in popular science or society journals); and References in non-Medline indexing services. Moreover, the Medline indexing service may exclude certain journals preferentially favoured by some research organisations. However, an advantage of the method is that it does not capture: Non-standard publications (which would complicate any analysis); Low grade ("self-promotional") publications which may be included in subjective analyses (eg, publications in annual research reports, "in press" publications, conference presentations); and It minimises the likelihood of "tally duplication" because of research collaborations. Some exclusions or errors in location assignment will have occurred despite extensive cross-checking to certify a publication's origin. I relied almost entirely on authors to provide their own affiliation information. However, this was not always provided, or the address details were not always consistent. Finally, Medline catalogues only the primary author's address, so that publications of research collaborations for which the base research site (ie, principal author(s) address) is (i) outside the Medline capture search limit, or (ii) does not contain collaborating ("secondary") authors' addresses will be excluded from the tallies from these institutions. Importantly, while research output will necessarily be underestimated by this process, it would be expected that (apart from the limitations noted above) no individual hospital or other research organisation would be differentially disadvantaged in a direct-comparison process. The process employed within this report can easily be validated by any institution should there be any concern regarding objectivity or validity. Journal citation analysis The research institutes tended to target journals with higher and quicker citation rates (ie, average impact factor and immediacy index, respectively, was highest in their chosen journals), partly because these institutions published almost exclusively in overseas journals. These tend to have higher citation rates, and thus higher impact factor and immediacy index values (as shown by a breakdown of average impact factor values for SCI-listed journals with publications from NSW in 1993-1996 found by Medline capture) (Box 4). Impact factor listings derive from the United States and most strongly favour US journals.3 Recalculating average research site impact factor data for overseas publications only (ie, excluding Australian publications) tends to increase the relative average impact factor value for most hospital sites by between 0.5 and 1.0, and thus brings their average values very close to those of the research institutes. The medical research institutes concentrate more specifically on publishing specialist research work targeted at other research scientists, which cultivates further research activities and citing of publications by research peers, maintaining these journals' high impact factors. The core hospital sites publish this sort of research as well as publishing "generalist education" or "local content" papers aimed at non-research ("end-user") health specialists. Both forms of publication are valid and valuable, although only the former has high "international visibility". That immediacy index data largely follow the pattern of the impact factor data suggests that use of both citation markers may not be required in subsequent analyses, and that journals with high citation rates (impact factor values) also have quicker citation (immediacy index) values (confirmed by review of the Medline database and SCI publications1 -- data not shown). Citation values as markers of research quality Publication citation data are popularly used as a surrogate marker of publication "quality" on the premise that the higher the citation rate, the greater the scientific quality of the articles in that journal. The validity of this approach can be questioned and has given rise to much recent debate.2-5,16-18 The main problems relate to: Accessibility of journals and journal listing bias, with only journals in the SCI database included in the analysis and listings strongly favouring English language journals published in the United States; Inferences that a journal's impact factor or citation pattern reflects each article's citation pattern (which is not the case; also article citation rates determine journal impact factor, not the other way around), and that citation reflects scientific quality (not necessarily -- an article may be cited often to exemplify a scientific flaw); Citation bias, as there is no correction for the influence of self-citation in impact factor calculations (authors and journals may both favour self-citation); and Specialty bias, as impact factors differ according to the research field. There are many other potential traps.2-5 However, the impact factor process is relatively easy, and it offers an achievable comparison process, so its popular use as a quality marker persists. In practice, the impact factor may better reflect "international visibility" than "scientific quality". Furthermore, use of averaged data (eg, average impact factor and average immediacy index) perhaps shows "average visibility". A fairer comparative process might be to correlate total (or cumulative) impact factor as a marker of "total visibility", as shown in Figure 5. Figure 5: Total, (ie, cumulative) impact factor (1993-1996 period) for Medline-captured publications arising from NSW research. Data shown as a composite bar graph for those hospitalswith an affiliated research institute (as defined in Methods). Cumulative impact factor derived by addition of individual impact factor values from all journal publications for each research site. POWH=Prince of Wales Hospital. In a recent comparable analysis, Bourke and Butler6 assessed Australia's basic research in the medical and health sciences, using individual article citation rates to assess the "visibility" of research in different general research sectors (ie, universities, hospitals, medical research institutes, other institutions) by calculating the average number of citations received per publication (cpp). They also listed specific institutions with high cpp values. Use of this more specific marker of article citation, rather than journal citation, overcomes some of the limitations noted above of the use of impact factor as a surrogate marker of publication quality. However, use of cpp is still based on the premise that a high citation rate reflects high scientific quality. With this tool, Bourke and Butler6 concluded that "the bulk of Australia's basic research in the medical and health sciences comes from the universities and hospitals, but Australia's medical research institutes, the members of AAMRI [Australian Association of Medical Research Institutes], have the highest international profiles". In this our data agree. Thus, while these institutes produce publications which appear in the most highly "visible" journals, the universities and hospitals produce the vast bulk of the research output, and contribute most to local medical issues. However, if, as an exercise, Australian journal publications are excluded from the calculations, the remaining overseas-published medical research from the universities and hospitals also appears in these highly "visible" journals. Finally, it is likely that some significant under-representation of specific teaching hospital sites would have occurred in Bourke and Butler's6 study, as "where a research group based in a hospital with a university connection lists the university in the address, we consistently assign the publication to the university". In this report, publications are assigned to both the university and the hospital, and comparisons then made differentially. Based on the Medline database, an average of 14% (but, on a case-by-case basis, up to 43%) of hospital publications include a university address. Conclusions This survey confirms the important contribution to medical research and teaching made by NSW teaching hospitals. Thus, both publication output and perceived scientific quality and visibility can be considered as high compared with peer NSW research institutes. In addition, it is the non-research-institute-based hospital sites that most significantly contribute to research published in Australia. It is hoped that the process of identifying quality research from Australian research institutions, as outlined in this report, will help promote research activity and its future development at these sites, and help to set benchmark standards for this research and teaching activity. Acknowledgements The concept derives from four previous internal research review reports to the Westmead Scientific Advisory Committee (SAC). Most of the data analysis was performed "after-hours", and I am grateful to Ms Beryl Dawson for her patience and understanding. Professor Tony Cunningham and Professor Cres Eastman are thanked for their support and encouragement. Sincere appreciation also to my colleague Dr Brian Nankivell, who set me upon this path of discovery, and to Ms Claire Wolczak, who sought out and found copies of the required SCI reports. Conflict of Interest: I am employed within one of the institutions in this report, but have attempted at all times to be objective. References Science Citation Index. Journal citation reports. A bibliometric analysis of science journals in the ISI database. Philadelphia: Institute for Scientific Information, 1993, 1994, 1995, 1996. Garfield E. How can impact factors be improved? BMJ 1996; 313: 411-413. Seglen PO. Why the impact factor of journals should not be used for evaluating research. BMJ 1997; 314: 498-502. Smith R. Unscientific practice flourishes in science. Impact factors of journals should not be used in research assessment. BMJ 1998; 316: 1036. Williams G. Misleading, unscientific, and unjust: the United Kingdom's research assessment exercise. BMJ 1998; 316: 1079-1082. Bourke PF, Butler L. The research enterprise: mapping Australia's basic research in the medical and health sciences. Med J Aust 1997; 167: 610-613. Research School of Social Sciences, Australian National University, Internet webpage (URL site: <http://rsss.anu.edu.au/>). Accessed August, 1998. Sittig DF. Identifying a core set of medical informatics serials: an analysis using the MEDLINE database. Bull Med Libr Assoc 1996; 84: 200-204. Takahashi K, Hoshuyama T, Ikegami K, et al. A bibliometric study of the trend in articles related to epidemiology published in occupational health journals. Occup Environ Med 1996; 53: 433-438. Dunn K, Chisnell C, Sittig DF. A quantitative method for measuring clinical user journal needs: a pilot study using CD Plus MEDLINE usage statistics. Medinfo 1995; 8: 1428-1432. Schloman BF. Mapping the literature of allied health: project overview. Bull Med Libr Assoc 1997; 85: 271-277. Schloman BF. Mapping the literature of health education. Bull Med Libr Assoc 1997; 85: 278-283. Wakiji EM. Mapping the literature of physical therapy. Bull Med Libr Assoc 1997; 85: 284-288. Burnham JF. Mapping the literature of radiologic technology. Bull Med Libr Assoc 1997; 85: 289-292. Burnham JF. Mapping the literature of respiratory therapy. Bull Med Libr Assoc 1997; 85: 293-296. Hecht F, Hecht BK, Sandberg AA. The journal "impact factor": a misnamed, misleading, misused measure. Cancer Genet Cytogenet 1998; 104: 77-81. Gallagher EJ, Barnaby DP. Evidence of methodological bias in the derivation of the Science Citation Index impact factor. Ann Emerg Med 1998; 31: 107-109. Opthof T. Sense and nonsense about the impact factor. Cardiovasc Res 1997; 33: 1-7. (Received 3 Feb, accepted 20 Oct 1998) Author's details Institute of Clinical Pathology and Medical Research (ICPMR), Westmead Hospital, Western Sydney Area Health Service, Westmead, NSW. Emmanuel J Favaloro, BSc(Hons), PhD, Senior Hospital Scientist, Haematology. Reprints: Dr E J Favaloro, Senior Hospital Scientist, Haematology, ICPMR, Westmead Hospital, Westmead, NSW 2145. Email: emmanuelATicpmr.wsahs.nsw.gov.au Journalists are welcome to write news stories based on what they read here, but should acknowledge their source as "an article published on the Internet by The Medical Journal of Australia <http://www.mja.com.au>". <URL: http://www.mja.com.au/>

Emmanuel J Favaloro

Medical Research Perspectives Is there gender bias in research fellowships awarded by the NHMRC? Jeanette E Ward and Neil Donnelly, on behalf of the Research Fellowships Committee, NHMRC MJA 1998; 169: 623-624 Abstract - Introduction - Methods - Results - Discussion - Acknowledgements - References - Authors' details - - More articles on Administration and health services Abstract Objective: To assess whether there is gender bias in the allocation of research fellowships granted by the Research Fellowships Committee of the National Health and Medical Research Council. Data sources: Anonymous data from applications for a research fellowship from 1994 to 1997. Results: More men than women apply for research fellowships (sex ratio, 2.5:1), but there is no difference in the proportion of male or female applicants who succeed in their application. Among new applicants, men tend to apply for a higher level of fellowship than women. Conclusions: Lack of data about the numbers of eligible men and women means that we cannot draw conclusions about self-selection biases among potential applicants. However, the selection procedures of the Committee appear to be unbiased. The gender of applicants does not influence the outcome of their application. Introduction Australian researchers seeking to advance their careers in health and medical science can apply for appointment as a National Health and Medical Research Council [NHMRC] Research Fellow. Applications for fellowships from researchers outside the research institutes that receive block-funding from the NHMRC are considered by the Research Fellowships Committee.1 Four levels of fellowship are awarded: Research Fellow, Senior Research Fellow, Principal Research Fellow, and Senior Principal Research Fellow. Applications by researchers for appointment, reappointment or promotion are highly competitive. Criteria used to evaluate applications include the applicant's independence and track record in research, originality of the research, national and international recognition, publications and broader contribution to the applicant's area of research. These criteria are not weighted: rather, the overall merit of each case is assessed from diverse sources of evidence such as curriculum vitae, reports from referees nominated by the applicant, reports from external assessors nominated by the Research Fellowships Committee, consideration of the regional grants interviewing committee score (which indicates the scientific quality of the project or program to which the fellowship application is tied) and interview. A Swedish study showed that reviewers' scores of postdoctoral fellowship applications to the Swedish Medical Research Council were strongly influenced by the gender of the applicant.2 This prompted the Research Committee of the NHMRC to ask the Research Fellowships Committee to conduct its own review. Methods Anonymous data on all applicants for research fellowships were manually extracted from the records for the period 1994-1997. We counted the number of applications from men and women seeking and receiving appointment, reappointment or promotion to research fellowships at each level, calculated sex ratios, and tested for evidence of gender bias by means of 2 tests. Analyses were not conducted for reappointments as we could not be confident that these would not include repeated applications from individuals who had failed in an initial application or an application for promotion within the same period. Results During the study period, 301 applications for appointment, promotion or reappointment were received from men, of which 102 (34%) were successful. One hundred and twenty applications were received from women, of which 43 (36%) were successful. This difference was not significant (2 = 0.14, df = 1, P = 0.7). Applications for initial appointment to the research fellowship scheme We noted that 202 applications for initial appointment to the research fellowship scheme were received from men, yet only 83 were received from women (an unequal ratio, specifically 2.4 : 1). However, the total denominator of eligible applicants by gender could not be determined. Over the study period, 81 applications for initial appointment at Research Fellow level were received from men compared with 45 from women (ratio 1.8 : 1). Similarly, 121 applications for initial appointment to a Senior Research Fellowship or higher were received from men compared with only 38 from women (ratio 3.2 : 1); 30 applications for initial appointment as Principal Research Fellow or Senior Principal Research Fellow were received from men and only four from women (ratio 7.5 : 1); a total of five applications for initial appointment as Senior Principal Research Fellow were received from men compared with only one from a woman (ratio 5 : 1). We combined applications for appointment as Research Fellow or Senior Research Fellow and compared these by sex with those for Principal Research Fellow or Senior Principal Research Fellow. Of the 202 applications received from men, 30 (15%) were for Principal Research Fellowships or Senior Principal Research Fellowships. For women, only 4 (5%) of 83 applications were for initial appointment as Principal Research Fellow or Senior Principal Research Fellow. Having applied for an initial appointment, men were significantly more likely than women to apply for a senior appointment (2 = 5.6, df = 1, P = 0.02). For the study period, 26 applications (13%) from men for initial appointment (irrespective of level) were successful and 176 (87%) were not. In contrast, 14 (17%) applications from women for initial appointment (irrespective of level) were successful compared with 69 (83%) unsuccessful. The difference between men and women is not significant (2 = 0.8, df = 1, P = 0.4). Applications for promotion from Fellows already appointed At different career stages, but typically when they have reached the top of the scale and submitted an application for research grant renewal, Fellows are eligible to apply for promotion. Over the study period, 71 applications for promotion were received from men: 14 (20%) for promotion to Senior Research Fellow and 57 (80%) for promotion to Principal Research Fellow or Senior Principal Research Fellow. Over the same period, 24 applications for promotion were received from women: 9 (38%) for promotion to Senior Research Fellow and 15 (63%) for Principal Research Fellow or Senior Principal Research Fellow (2 = 3.1, df = 1, P = 0.08). For the study period, 34 (48%) applications from men for promotion (irrespective of level) were successful and 37 (52%) were not, out of the total of 71. In contrast, 14 (58%) applications from women for promotion (irrespective of level) were successful compared with 10 (42%) unsuccessful, out of the total of 24. Again, there was no significant gender effect (2 = 0.8, df = 1, P = 0.4). Discussion We are concerned that more applications for initial appointment are received from men than women (a ratio of 2.5:1). As we do not know the size of the pool of eligible men and women, we cannot state whether eligible women are less likely to apply than men, but in 1997 there were more women than men enrolled in PhD degrees in health faculties of Australian universities.3 Were women scientists concerned that the NHMRC research fellowships scheme is biased against women, they might be less likely to apply for initial appointment because they perceived themselves to have a less-than-equal chance of a fair evaluation. Our data shed no light on this question, but analysis of data relating to NHMRC PhD scholarships, postdoctoral awards such as C J Martin Fellowships and R D Wright Scholarships would generate further testable hypotheses about gender bias outside the Research Fellowships Committee. Our study also shows that, among new applicants, men are more likely than women to apply for fellowships at the higher levels. The data might also suggest that male research fellows are more likely to seek promotion to the higher levels than female research fellows. However, these analyses were not adjusted for age or years of postdoctoral experience, so our data on potential gender bias in promotion are very limited. To obtain better data, it would be necessary to select a cohort of research fellows appointed in one year and track their progress, testing statistically whether gender is associated with further applications for promotion or reappointment. The Research Fellowships Committee itself has five male and four female members.1 In keeping with increasing community and professional interest in the accountability of the NHMRC,1,4-6 we place our findings in the public domain to generate discussion. We conclude that the influence of gender bias, if present at all in the research fellowships scheme, is indirect and acts before the process of evaluation of a specific application. Women may be less likely to apply and, once appointed, perhaps more cautious in their applications for promotion. However, having applied and specified a particular level, the gender of applicants does not influence the outcome of their application. We acknowledge the limitations of the available data. Access to applications to calculate publication outputs and acquisition of competitive grants as indicators of research proficiency (as in the Scandinavian study)2 would have required the written consent of the applicants. Further debate and resources to support such a study are recommended, as is research to examine any differential success rates in project or program grant applications to the NHMRC by male and female investigators. Acknowledgements This commentary was written on behalf of the NHMRC's Research Fellowships Committee, of which the first author is a member. We thank Professor John Finlay-Jones (chair); Professor Daine Alcorn; Professor Peter Brooks, Professor Murray Esler; Professor Simon Gandevia; Dr Emanuela Handman; Professor Ieva Kotlarski and Associate Professor David Roder for their interest and constructive advice regarding analysis and writing. Professor Warwick Anderson also provided encouraging support. Kerry Warren, formerly Committee Secretary, NHMRC Career Fellowships, manually extracted data from the NHMRC database. References National Health and Medical Research Council. 1997 Annual Report. Canberra: NHMRC, 1998. (Commonwealth of Australia Catalogue No. 9804863.) Wenneras C, Wold A. Nepotism and sexism in peer review. Nature 1997; 387: 341-343. Department of Employment, Education, Training and Youth Affairs. Selected Higher Education Student Statistics, 1997. <http//www.deetya.gov.au/divisions/hed/ highered/statpubs.htm>. Accessed 18 September 1998. Anderson W. Funding Australia's health and medical research. Med J Aust 1997; 167: 608-609. Ward J, Slaytor E. Enhancing NHMRC investment in public health research. Aust N Z J Public Health 1998; 22: 189-190. Larkins R, Anderson P. Australian medical research: more resources and the right balance. Med J Aust 1998; 168: 535-536. Authors' details Central Sydney Area Health Service Needs Assessment and Health Outcomes Unit, Sydney, NSW. Jeanette E Ward, PhD, FAFPHM, Director. Neil Donnelly, MPH, Statistician. Reprints will not be available from the authors. Correspondence: Associate Professor J E Ward, CSAHS Needs Assessment & Health Outcomes Unit, Locked Bag 8, Newtown, NSW 2042. Email: jwardATnah.rpa.cs.nsw.gov.au Journalists are welcome to write news stories based on what they read here, but should acknowledge their source as "an article published on the Internet by The Medical Journal of Australia <http://www.mja.com.au>". <URL: http://www.mja.com.au/>

Medical Research Perspectives The Menzies School of Health Research offers a new paradigm of cooperative research John D Mathews The Menzies School has addressed problems in Aboriginal and tropical health through research that requires cooperation between disciplines as well as improved communication and trust between researchers, Aboriginal people and the wider community. MJA 1998; 169: 625-629 Introduction - The politics of Aboriginal health - Success in interdisciplinary and crosscultural collaboration - Some research highlights of medical importance - The Menzies School's work in central Australia - Research highlights in tropical and international health - Resources and links - Cooperation is the secret of success - Looking ahead - Acknowledgements - References - Author's details - - More articles on Aboriginal health Introduction The Menzies School of Health Research, in the Northern Territory, has been a surprisingly successful research investment. The dividends since 1985 include increased understanding of Aboriginal and tropical health problems, the transfer of knowledge and skills into training and improved health services, and some 70 research publications each year. The Menzies School is a brave and cooperative venture of the Northern Territory Government, the Menzies Foundation (commemorating the name of our longest-serving prime minister), and the University of Sydney. I was appointed as Foundation Director and we moved to Darwin in January 1985, in quixotic mood, and not knowing what to expect. My wife had found a Thomas Keneally quote: . . . the north is littered with the detritus of great hopes, and Darwin is still an outpost . . . but with a sense of destiny that would have done Athens credit.1 We were naive enough to ignore the implicit warning, and to dream of Athens in the north. To Darwin I brought a research background in medicine and epidemiology; experience from New Guinea, the Walter and Eliza Hall Institute and Oxford; and 10 years as an NHMRC Fellow at the University of Melbourne. My first dream for the Menzies School was to establish a centre of research excellence. The second dream was to somehow make a difference in Aboriginal health. The potential nightmare was to work out how to realise each dream without jeopardising the other. The politics of Aboriginal health Countries with the least education and income tend to have the poorest health, and within any one country persons with the least education and income tend to have the worst health. Box 1 shows the causal linkages between education, income and health in any society, and Box 2 shows how the social dislocation suffered by Aboriginal Australians since colonisation has specifically contributed to their poor health.2 The poor health of Aboriginal Australians is primarily due to social and environmental disadvantage. It is not due to any absolute lack of knowledge about the causes of their ill-health (Box 3), but to the fact that Aboriginal people have had limited access to health resources and knowledge because of their own poverty and educational disadvantage. There has also been limited understanding of Aboriginal health issues by those responsible for funding decisions, compounded by inadequate knowledge and training of health advisers and providers. Unfortunately, the poor state of Aboriginal health has also been perpetuated by disagreements about what should be done and how, who should do it, and who should pay for it. This lack of consensus, amounting to a modern Babel (Box 4), is only now beginning to be resolved. The Menzies School has contributed to the debate on Aboriginal health by helping to fill gaps in understanding, communication and implementation. It has attracted expert staff to the Northern Territory, driven research to identify areas of unmet health need, tested innovative health interventions, and been an evaluator, critic and advocate for Aboriginal health policy. Success in interdisciplinary and crosscultural collaboration The success of the Menzies School has been driven by the quality of our staff, the challenges faced, and by the added value that comes from collaboration and communication between diverse disciplines. Above all, success would have been impossible without the expertise and commitment of Aboriginal staff and colleagues. Major contributions have been made by Lorna Fejo, Jessica Bujevich, the late Sally Ross, Louisa Collins, Daisy Yarmirr, Josie Crawshaw, Annie Bonson, Geoffrey Angeles, Mai Katona and many others. Their achievements have been to communicate the health priorities and values of Aboriginal people to non-Aboriginal researchers, to facilitate research projects in a culturally appropriate manner, and to work with other Aboriginal people to show how knowledge and research findings can be fed back to communities and applied to achieve practical health benefits. Recently, the Tiwi Health Board has played a key role in codifying the many sensitive issues that arise in crosscultural research and providing a framework for future research in a Legal Agreement signed with the School (Box 5). Some research highlights of medical importance (See also Box 6) Understanding streptococcal infection and rheumatic fever At any one time, up to 60% of Aboriginal children in bush schools have skin sores infected with group A streptococci, and there are occasional epidemics of acute poststreptococcal glomerulonephritis. Bart Currie, Jonathan Carapetis and colleagues have shown that the same communities suffer from the highest rates of rheumatic fever in the world. To overcome the limited awareness of rheumatic fever and the low rates of compliance with penicillin prophylaxis, Geoffrey Angeles, Norma Benger and other members of our Aboriginal Unit have developed The Rheumatic Fever Story, a successful education program (booklets, songs and videos) for patients, relatives, health workers and the wider community. K S Sriprakash, a talented molecular geneticist, has led molecular studies of group A streptococci, detecting as many as 13 immunologically distinct types present at the same time in a single bush community of a few hundred children, with a total of about 100 different types circulating through Aboriginal communities in northern Australia, many that have never been identified elsewhere. Candidate nephritogenic strains have recently been identified. This work is linked to studies of the epidemiology and population biology of group A streptococci in Aboriginal communities, to studies of treatment efficacy, and to studies directed towards vaccine development with Michael Good and the Cooperative Research Centre for Vaccine Technology in Brisbane. Understanding endemicity of respiratory bacteria For Aboriginal children, persistent otitis media is a major cause of illness, hearing loss and educational disadvantage. Amanda Leach, Judith Boswell, Terry Nienhuys and others have shown that otitis media develops in all Aboriginal infants within a few weeks of birth immediately after nasopharyngeal colonisation with Streptococcus pneumoniae and Haemophilus influenzae. Although each infection seems to be eventually cleared by the host response, there are some 30 different serotypes of pneumococcus and at least 50 types of haemophilus which can queue up to infect every child in every community. The persistence of nasal infection and respiratory disease is associated with the persistent colonisation by such multiple bacterial strains into adult life. Cross-infection is driven by overcrowding, poor hygiene and the large numbers of bacterial strains circulating. Detailed modelling suggests that each strain is maintained indefinitely, even in relatively small populations, because there are always a few carriers of each strain left to infect susceptible newborn infants. Furthermore, with the carriage of multiple serotypes or strains at the same time by the same host individual, some of the strains are "hidden" from the immune system, giving them an extra survival advantage. Likewise, antibiotic-resistant strains "hide" behind sensitive strains, only to be revealed by antibiotic treatment. Understanding scabies in dogs and people Skin infections associated with scabies infestation are frequent in Aboriginal communities, particularly among children. Because dog scabies was thought to be a source of infection for people, scabies control programs have sometimes treated dogs rather than people. Now, using molecular genotyping, Shelley Walton and colleagues have shown that populations of scabies mites from dogs in Australia and America do not overlap with scabies from people in those same areas. This strongly suggests that scabies from dogs are not driving human scabies in remote communities and that control programs for human scabies must focus on people. Jonathan Carapetis and Daisy Yarmirr, in cooperation with Aboriginal and health service colleagues, have shown that community-based treatment with pyrethrin can reduce both scabies and streptococcal impetigo. Understanding renal disease and cardiovascular disease Mortality from renal failure for Aboriginal Australians is very high and rising. Up to 50% of Aboriginal adults have proteinuria and in some communities 2% are receiving renal dialysis to stay alive. Paul van Buynder and colleagues identified obesity, hypertension and non-insulin-dependent diabetes mellitus (NIDDM) as risk factors for proteinuria in Aboriginal communities. Modelling studies with Alison Goodfellow and others suggest that proteinuria develops from very early in life in those with evidence of past infection with group A streptococci. Wendy Hoy and colleagues have shown that low birth weight is predictive of NIDDM, proteinuria, and presumably renal disease, and have suggested that the risk factors for renal disease can also help to explain the high rates of cardiovascular disease in Aboriginal adults. Causes of disease acting from early in life The role of low birth weight as a predictor of poor health in later life has attracted much recent attention, and is of particular importance for Aboriginal Australians. Wendy Hoy and others have shown that the combination of low birth weight with adult obesity appears to confer the highest risk of NIDDM, proteinuria and other disorders. Sue Sayers has shown that high rates of Aboriginal low birth weight are due to intrauterine growth retardation, possibly resulting from maternal malnutrition, infection and substance abuse. Thus, low birth weight may be best regarded as a marker of those adverse influences in pregnancy that are the actual mediators of adverse health effects in later life. This hypothesis would explain how poor health can pass from generation to generation, and may provide another reason why health has been slow to improve for many Aboriginal Australians. Early treatment of renal disease The epidemic of Aboriginal renal disease should eventually be controllable through public health measures such as improved nutrition and infection control, particularly in pregnancy. In the meantime, there is a strong rationale to provide "best-practice" clinical treatment, not previously available for Aboriginal people. Accordingly, Wendy Hoy, as an adjunct to the NHMRC-funded research program, has introduced treatment with ACE inhibitors for Tiwi people with early renal disease. Compliance is good, and treatment markedly reduces the rate of deterioration of kidney function, which will in turn prolong life and reduce the escalating social and financial costs of dialysis services. The Menzies School's work in central Australia We have a small research unit in Alice Springs to complement our major operation in Darwin. Major contributions include those of Tim Rowse (historical, social and nutritional studies), David Scrimgeour, Robyn McDermott, Ilan Warchivker and John Wakerman (evaluation studies), and Komla Tsey (health and education). Research highlights in tropical and international health David Kemp, FAA, joined the School as Deputy Director in 1992, with support from the Wellcome Trust and from the Howard Hughes Institute to continue his fundamental work with falciparum malaria, and to commence new molecular studies of haemophilus, donovanosis, and scabies. This year saw the culmination of his 10-year search, begun at the Walter and Eliza Hall Institute, to find the cytoadherence gene in Plasmodium falciparum that is believed to explain the stickiness of red blood cells in cerebral malaria. The new gene, designated CLAG, was identified and sequenced, and a CLAG knock-out was shown to have lost the stickiness phenotype. The team has subsequently identified additional genes, similar to CLAG, elsewhere in the malaria genome, opening up exciting new possibilities for treatment or prevention of cerebral malaria. Other malaria projects in Indonesia are funded by a grant from the Northern Territory Government to mark the 50th anniversary of Indonesian independence and a US National Institutes of Health grant to Nick Anstey, and are being carried out in cooperation with Emiliana Tjitra and Indonesian colleagues. Resources and links (See also Box 7) The achievements of the Menzies School have depended on the generous financial support of the Northern Territory Government and the Menzies Foundation, competitive grants from the National Health and Medical Research Council and other agencies in Australia and overseas, and private and corporate donations. In 1998, the annual budget was $6 million to support about 100 employees and postgraduate research students. The School has also enjoyed the goodwill and cooperation of Territory Health Services and other arms of government, Aboriginal communities, medical services and organisations, the National Heart Foundation and other non-government organisations, the University of Sydney, the Northern Territory University, and Flinders University Clinical School at the Royal Darwin Hospital. The Menzies School became the lead agency in a successful bid to establish the Cooperative Research Centre for Aboriginal and Tropical Health in 1997. Through its Board, chaired by Dr Lowitja O'Donoghue, and with a majority of Aboriginal members, the Cooperative Research Centre has an agenda to discover and disseminate knowledge about Aboriginal health problems, to provide more research and training positions for Aboriginal people and to facilitate Aboriginal control of the planning and implementation of health research and health services. From 1994, the School has taught postgraduate coursework in public health to help develop skills in the local health workforce. Now, in partnership with the Northern Territory University, the School is promoting a broader vision of public health education through a Faculty of Public Health. This Faculty will continue postgraduate teaching and promote access to accredited courses at multiple levels and to short courses to meet the needs of teachers and educators, administrators, Aboriginal people and others in need of public health knowledge and expertise. Cooperation is the secret of success The Menzies School has become a leader in tropical and Aboriginal health research, not only through the talent and commitment of individuals, but also because of its capacity to encourage cooperation between disciplines, and to build and sustain cooperative partnerships with Aboriginal stakeholders, health services and governments in northern and central Australia. This cooperative research paradigm, linking the laboratory with the clinic and the community, has delivered important understandings and contributed to more effective strategies for training of health staff, and to improved health promotion, prevention and treatment strategies. Despite its short-term opportunity costs, cooperation in health research pays off in the longer term by helping to translate modern scientific knowledge into direct community benefit, just as natural selection has discovered that cooperative processes provide pay-offs in the longer term in most otherwise competitive biological and social systems. Indeed, interactions that balance competition with cooperation turn up in all evolving systems to achieve a balance between short term returns (efficiency) and longer term strategic outcomes. Looking ahead The multidisciplinary focus of the Menzies School of Health Research has more than justified the vision of its founders by delivering value for money to its stakeholders and the wider community. However, as the School faces the new millennium, it needs to serve the community with a broad public health perspective while maintaining the deep biomedical expertise that underpins strategic research to be an academic critic of health policy, while working in partnership with health services to promote necessary improvements to persuade funding agencies to recognise the value of, and to pay the full opportunity costs of, cooperation and collaboration between different disciplines and organisations to maintain its cohesion, corporate identity, shared values and vision for the future. Talent and enthusiasm are always welcome! Acknowledgements This summary is based on the work of many colleagues to whom I am deeply indebted. Special thanks to Coralie Mathews, Bart Currie, Dave Kemp and Lindy Warrell for reviewing the manuscript, and Debra Davis for its preparation. References Keneally T. Outback. Sydney: Coronel Books, 1983. Mathews JD. Historical, social and biological understanding is needed to improve Aboriginal health. Recent Adv Microbiol 1997; 5: 257-334. Author's details Menzies School of Health Research, Darwin, NT. John D Mathews, AM, MD, Professor and Director. Reprints will not be available from the author. Correspondence: Professor J D Mathews, Menzies School of Health Research, PO Box 41096, Casuarina, NT 0811 Email: johnATmenzies.su.edu.au Journalists are welcome to write news stories based on what they read here, but should acknowledge their source as "an article published on the Internet by The Medical Journal of Australia <http://www.mja.com.au>". <URL: http://www.mja.com.au/> 1: Social determinants of good health Back to text 2: Historical impacts of colonisation upon Aboriginal health Back to text 3: Lessons about Aboriginal health and research Aboriginal health is limited more by the failure to apply knowledge that already exists than by the lack of knowledge itself. Aboriginal people have always understood this, and they have been naturally suspicious of research projects that seem to serve the interests of researchers more than those of Aboriginal people. The most relevant research questions are: How to ensure that existing knowledge is taken up and acted upon by public sector decision-makers and managers and health professionals. How to ensure that Aboriginal people have access to the knowledge and resources that they need to use to improve their own health. How to plan specific research projects to make a difference by finding better ways of working across cultural boundaries. improving access to knowledge, resources, education and health services for Aboriginal people providing social or biomedical insights about better ways to promote health or prevent or treat disease for Aboriginal people. Back to text 4: The modern Babel The biblical Tower of Babel (Genesis, xi) is the traditional metaphor for the schisms in language, beliefs and culture in the modern world. It reminds us that without a common language and shared concepts, we are unable to understand each other. In the Northern Territory in 1985 many different voices were speaking about Aboriginal health. Those on the political right tended to blame the victims, and saw the emergence of Aboriginal control as a threat. There were differences between levels of government. Some officials lacked appropriate expertise and were unused to problem solving, let alone to academia. Some health professionals were escaping from academia, or had a postmodern scepticism about science and medicine. Some romantics said that traditional Aboriginal people should be taught as little as possible about Western culture. Urban Aboriginal people voiced their hurt from discrimination or family experiences as stolen children. At the same time, Aboriginal health workers had strong cultural skills, but only limited health training. Traditional Aboriginal people, with insufficient support to deal effectively with the outside world, saw a progressive erosion of their culture and values. In such a Babel there could be little consensus about how to improve Aboriginal health. Without consensus, our political masters had a continuing excuse to ignore many issues. As a result, the poor state of Aboriginal health has continued to burn into the conscience of Australia. It is likely to be long remembered as the worst-ever failure of our nation. Back to text 5: Creative partnership - Tiwi Health Board and the Menzies School of Health Research Ms Alberta Puruntatameri and Dr Val Asche signing the Legal Agreement between the Tiwi Health Board and the Menzies School of Health Research, 22 October 1998. Back to text 6: Some important research areas at the Menzies School Cultural understandings of Aboriginal illness and death (Tarun Weeramanthri, Ada Parry, Norma Benger, Clifford Plummer, Vicky Nangala-Tippett and others) Education and health Otitis media and hearing disability contribute to poor educational outcomes (Anne Lowell, Terry Nienhuys, Judith Boswell, Joan Koops, Al and Lesley Yonowitz) Poor education contributes to poor health (Komla Tsey)Social and environmental determinants of health Community comparisons (Estrella Munoz, John Mathews and others) Environmental health study (Katherine Henderson, Ross Bailie) Melioidosis and contaminated water supplies (Mark Mayo, Bart Currie and Nick Anstey)Studies of substance abuse and appropriate interventions Evaluations of community interventions for alcohol (Peter d'Abbs, David Scrimgeour) Health effects and interventions for petrol sniffing (David Scrimgeour, Chris Burns and Bart Currie) Health effects of kava drinking and policy implications (John Mathews, Malcolm Riley, Estrella Munoz, Peter d'Abbs, Chris Burns, and Alan Clough)Interventions to improve Aboriginal health Community Nutrition Program at Minjilang (Mandy Lee, Annie Bonson, Daisy Yarmirr and others) Strong Women, Strong Baby, Strong Culture Program Evaluation (Lorna Fejo, Dorothy Mackerass and others) Diagnosis and treatment of donovanosis and sexually transmitted diseases (Frank Bowden, Jenny Carter, David Kemp and colleagues) Improved diagnosis and treatment of otitis media (Amanda Leach, Al Yonowitz, Peter Morris, Harold Koops and colleagues) Treatment of trachoma with azithromycin (Andrew Laming, Annie Bonson and colleagues) Smoking prevention (Rowena Ivers, Ross Bailie and the National Heart Foundation)Health service research and evaluation Best practice procedures (Bart Currie, David Scrimgeour, Peter Morris) Evaluation and planning of service models (David Scrimgeour, Chris Burns, John Wakerman and others) Health economic aspects (Robyn McDermott, Ilan Warchivker, John Wakerman) Coordinated care trials evaluation (Peter d'Abbs, Ross Bailie). See http://www.menzies.su.edu.au for a much more detailed account of the work of the Menzies School over the last five years. See also reference 2. Back to text 7: The Menzies building The Menzies School of Health Research was able to secure generous joint funding from the Northern Territory and Commonwealth governments for its new building in Darwin, opened in November 1996. Back to text

John D Mathews

Medical Research Perspectives The TVW Telethon Institute for Child Health Research The birth and growth of a research institute Fiona Stanley Diverse research workers, variously funded by public and private sources, were drawn together to create an Institute and an opportunity to work together on the complex problems in child health. MJA 1998; 169: 630-633 Introduction - Research origins - Rationale for a multidisciplinary institute for child health research - Growth - Successes - Threats - References - Author's details - - More articles on Aboriginal health Introduction In 1967 two men shared a game of golf and a vision for research to improve child health. Sir James Cruthers, then Managing Director of Channel 7 (TVW, Perth), suggested to Jim Clarkson, then the Chief Executive Officer of the Princess Margaret Hospital for Children (PMH) in Perth, the concept of a "Telethon" to raise money from the community for research at PMH. The Telethon became an annual event and in the first year raised funds for the PMH Children's Medical Research Foundation, which funded two small hospital research groups: a clinical immunology research unit founded by Dr Keven Turner, an immunologist from Adelaide, and a clinical nutrition research group established by Dr Michael Gracey, a paediatric gastroenterologist from Melbourne with a special interest in Aboriginal children and their health. From these beginnings, the TVW Telethon has gone on to fund a range of medical research in Western Australia, ultimately providing the essential infrastructural finance for the Institute for Child Health Research, established in 1990 and now a vigorous multidisciplinary research centre employing nearly 200 people. The Institute's name acknowledges not only this beginning but the continuing support from the TVW Telethon. Sir James Cruthers has only recently stepped down from the Institute's Board of Directors. Research origins The first two research groups funded by the Telethon were based at PMH. In the 1970s, the immunology group was beavering away, almost in isolation, in the neglected area of mucosal immunology, looking particularly at the developing respiratory tree and what role the immune system might play in allergy and asthma. This area of immunology and cell biology has now become of global importance in attempts to explain the epidemic of asthma and allergy sweeping the Western world. The work of Patrick Holt was particularly important at the time and has continued to be pre-eminent in the study of the development of allergic sensitisation and asthma.1,2Meanwhile, I had been fortunate enough to be awarded a National Health and Medical Research Council (NHMRC) overseas training fellowship in epidemiology at London University and at the National Institutes of Health, USA. When I returned to Perth in 1977, I used the $4000 setting-up grant in the last year of my fellowship to establish the Western Australian Cerebral Palsy Register (the only other registers at that time were in Sweden and Denmark) and the first congenital malformations register in Australia (funded by the Commonwealth Government in the wake of the Agent Orange scare). Then, as Senior Medical Officer in Child Health for the Health Department of Western Australia, I and my colleagues developed statewide links with midwives and child health nurses which laid the foundations for the Maternal and Child Health Research Data Base. This population-based, record-linked database has become the best in Australia (and probably the world) and now underpins much of the epidemiological work of the Institute.3 They were great days, as there was so little going on in maternal and child health epidemiology in Australia and we felt like pioneers! In 1980 these databases moved with me into a new NHMRC Unit of Epidemiology and Preventive Medicine at the Queen Elizabeth II Medical Centre, and spawned a range of epidemiological studies describing maternal and child health in WA and testing a range of hypotheses, focusing on birth defects, cerebral palsy and low birth weight. Telethon grants in the 1980s funded the Cerebral Palsy Register for nearly 10 years and a case-control study of dietary folate and neural tube defects as well.4,5 We commenced our work in indigenous maternal and child health and employed Aboriginal health workers in research before others had considered it important. The resulting partnerships with Aboriginal communities have grown even stronger since the Institute was established. Towards the middle of the 1980s I sensed that only by collaborating with basic scientists were epidemiologists ever going to get at biological mechanisms, properly elucidate causal pathways and be able to develop effective preventive strategies. Telethon funds appeared less secure at this time as they were being given away to other causes. I discussed these problems with Professor Lou Landau, who in 1984 had just accepted the Chair in Paediatrics in Perth, and we began to think of setting up an institute of child health research at the Children's Hospital, taking those with NHMRC funding with us, trying to get some additional funds for infrastructure and solving complex diseases! We both thought it a wonderful idea and invited Sir Gus Nossal across from Melbourne to address the hospital on "The birth of a research institute" -- this inspiring lecture was given in 1985 and aroused interest among local people in the concept. By this time Dr Wayne Thomas (from the Walter and Eliza Hall Institute in Melbourne), Dr Geoff Stewart (from the United Kingdom) and Dr Ursula Kees (from Switzerland) had all joined the Clinical Immunology Research Unit at Princess Margaret Hospital, and most of them now had "secure" NHMRC funding. Ursula Kees' group worked closely with the oncologists in the hospital, particularly Dr Michael Willoughby, the head of the oncology unit, who was determined that the Children's Cancer and Leukaemia Foundation would provide some secure funding for her laboratory in the new Institute. He could see this was crucial to the success of better identification of childhood cancers, investigating aetiology and discovering new therapies. Were we mad? We planned to set up a world-class institute in an isolated city in the biggest but most deserted State in Australia, in the middle of the crisis over business and political corruption known as "WA Inc" and as a recession was in full swing. We invited a group of Australia's leading researchers to Perth in 1986 and asked them to interview all of the researchers in child health and make an assessment. Despite the difficulties, the committee felt we had the right ingredients and encouraged us to go ahead. With the support of the Princess Margaret Hospital Board, and particularly of Professor Lou Landau, the proposal was developed further. In 1989, encouraged by Sir Gus Nossal, I applied for and was appointed Director of the new Institute. In 1990 we moved into our building -- the old School of Nursing at PMH, which was renovated with donations from the WA Lotteries Commission and the Incorporated Body of PMH. The support from other groups like the Variety Club of WA and the community has been the most crucial aspect of our success in this whole venture. Rationale for a multidisciplinary institute for child health research The problems in child health are now complex -- epitomised by diseases such as asthma, birth defects and other developmental problems, cancers and psychosocial problems. These stem from a complicated series of interactions between genes and environment, with variable causal pathways demanding complex solutions for their management or prevention. Our thinking was that if we brought together scientists from different disciplines under one roof we might be able to unravel the causes more successfully than working away separately in our little research areas. The aims of the Institute were to describe the burden of diseases in children and families in WA, to seek causal pathways using all types of scientific methods, and then to apply any knowledge to prevent disease in the community or to improve treatment at the bedside. We started as 90 scientists in four separate groups in 1989, with little infrastructure support, although our research grants from the NHMRC and other local foundations were adequate. Cell Biology, Molecular Biology and Cancer and Leukaemia moved in under the direction of Patrick Holt, Wayne Thomas and Ursula Kees, respectively, from the old PMH Children's Medical Research Foundation. My group from the NHMRC Unit moved to form the Division of Epidemiology and Biostatistics. Research in all these groups has blossomed at the Institute. Ursula Kees' group is making a seminal contribution on the role of homeobox gene malfunction in childhood leukaemia and has, in close collaboration with the PMH Oncology Unit and the international Children's Cancer Group, made significant contributions to the use of genetic markers to determine the prognosis and treatment for children.6,7Wayne Thomas's group is best known for its detailed work on the structure and immunology of house dust mite allergens, and a molecular approach to developing new types of immunotherapy8,9and the development of a candidate vaccine for all types of Haemophilus influenzae based on a conserved outer membrane protein.10 Patrick Holt's group has continued to describe the immunological mechanisms which operate during the development of tolerance to inhaled antigens,11,12 which are of extreme interest to both fundamental immunologists and allergists alike. Growth 1992 was the year of recruitment! We conducted an international search for a top biostatistician, which paid off with the recruitment of Dr Paul Burton, who became the Institute's senior biostatistician, and his wife, Dr Jenny Kurinczuk, an outstanding perinatal epidemiologist with a special interest in reproductive issues. Dr Burton conducted theoretical biostatistical research in a range of analytical problems (such as the analysis of complex interacting data sets and new methods of randomised trials), supported much of the biostatistical needs of the Institute and of our collaborators and spearheaded our new endeavours in genetic epidemiology. Within two years he became head of our new Division of Biostatistics and Genetic Epidemiology. Also in 1992 we sought an outstanding clinical researcher to establish a new Division of Clinical Sciences, with the brief of not only doing research in the Institute bridging the basic and clinical sciences, but also being a role model and stimulus for clinical research on the PMH campus. Dr Peter Sly was lured from Melbourne by offering him "fame and poverty" (he still has the letter) and he has continued to be a great success, collaborating with many groups in the Institute, the hospital and with fetal physiologists and respiratory researchers locally and internationally. In that year as well we were extremely fortunate in convincing the Health Department of Western Australia to second to us two outstanding clinical psychologists, Dr Steve Zubrick and Sven Silburn, whose research has underpinned the State Policy on Youth Suicide and other strategies in child and adolescent mental health. Dr Zubrick became head of the new Division of Psychosocial Research, with Silburn his very able deputy. The arrival of Australia's first MacFarlane Burnet Fellow, Professor Colin Sanderson, whose work on interleukin-5 was recognised internationally, created our last new division (Molecular Immunology) in 1994. This was an important bit of the jigsaw in our multidisciplinary attack on the complex disease of asthma. Dr Dierdre Coomb also arrived and established a laboratory specialising in the extracellular matrix, adhesion molecules and the mechanisms of inflammation, metastasis and haematopoiesis. As I look back now, some of our recruitment was part of a grand plan and some, as you would understand if you were in such an isolated and remote community, was opportunistic. Whatever the reason, the resulting mix has worked, as shown by our growth (from less than 50 to nearly 130 research staff in eight years), the way that many groups are collaborating in the Institute and the output to meet our goals. Successes A major reason for our success in fundraising from the local business community was that our research was focused on health problems that were well known as major burdens to the community -- asthma, adolescent suicide, birth defects, cerebral palsy, cancers and Aboriginal health. Another major factor was that we have had significant success in translating results into action (see Box); examples include the research on folate and spina bifida, reducing suicidal behaviours, improving outcome following bone marrow transplants in children with leukaemia, influencing the uptake of Haemophilus influenzae type b vaccination (which virtually eradicated the disease) and establishing a successful maternal and child health program for Aboriginal families in Kalgoorlie. Most of these are national and international issues and our Institute is increasingly being seen as a source of information for government and a model of success in multidisciplinary research and in translating research into policy. So, eight years on, have we been successful? How do you measure success in a multidisciplinary Institute? At the end of the first year of operation (June 1991) the Institute had $1.4 million in peer-reviewed grants, with a total operating revenue of $3 million (which included ongoing refurbishment costs). By the close of 1997 the Institute had gained $5.9 million in grants (including $2.5 million in NHMRC funding) and a total operating revenue of $8.3 million. You cannot force groups of different disciplines such as immunology and epidemiology and biostatistics to work together; all you can do is recruit thoughtful and good scientists and put them next to each other and hope that they talk! I remember two episodes vividly -- Patrick Holt saying "we have a great hypothesis we have developed in the lab and we need you epidemiologists to test it out for us"; this spawned our multidisciplinary asthma cohort study with Patrick Holt, Paul Burton, Peter Sly, Anne Read and myself testing the hypothesis that early and repeated infections may influence the immune response away from allergy and reduce the risk of asthma. The other episode was Colin Sanderson (head of Molecular Immunology) commenting that one of the best people in the Institute was Steve Zubrick, the head of Psychosocial Research -- given the usual contempt in which psychologists are held by "serious" scientists, this was great praise indeed! Bridges being developed between groups enhance the chances of collaboration. Threats With all this success and delight that we have survived our birth, with the new joint Commonwealth and State government $22.5 million building program heading for an early 2000 completion date, with such community support and government acceptance of our role, why am I concerned for our future? Our vulnerability now relates mainly to research funding and the support for our next generation -- our current students and postdoctoral staff. We are finding that research funding is much better in other countries and in other States and that we cannot offer our senior and rising bright young minds incentives to stay with us or even to stay in full time research. Some are off to overseas positions or into the private sector or into academic jobs with all the toil of teaching but at least some security. Our most recent sadness was that Paul Burton and Jenny Kurinczuk have been head-hunted back to the UK to tenured, well paid (at least double the NHMRC salaries they are currently receiving) academic positions at the University of Leicester. We will miss them greatly, but we can take some pride in having provided an environment for these two outstanding young people to develop their research careers to this level. Our policy of establishing an Institute by asking successful scientists to join us and bring their own salaries (usually NHMRC funded) was our only way of getting things going, but is not the way we can continue. It ensured that we only had peer-reviewed science in the Institute and meant that we could spend our precious and scarce resources on infrastructure and not research salaries. This ensured our survival, but it is not good policy in the longer term. The NHMRC roulette is not conducive to recruiting the brightest and the best. The Board needed little convincing to realise that such vulnerability is unacceptable and we are now looking at ways of securing our best people. Independent institutes are disadvantaged compared with universities because they do not receive direct infrastructure support from the Department of Employment, Education and Youth Affairs. Our Institute cannot match this year's increases in academic salaries as the NHMRC decided not to fund such an increase for research for its grant holders. Yet young scientists cannot be expected to work for low wages when salaries in other similar countries are much higher. We continue to lobby at Federal and State level, and wonder why, with our successes in improving child health, excellent research and scholarship, we are so undervalued in this country. Private funding alone is not the answer. I salute the likes of the visionary Sir James Cruthers and all the past, current and future corporate and private sponsors of research in Australia: what you could now do for us is to become advocates to convince governments to join with you in investing in our brightest and our best. Any less and our capacity to do research and benefit from it will be limited. References Holt PG, Yabuhara A, Prescott S, et al. Allergen recognition in the origin of asthma. Ciba Found Symp 1997; 206: 35-49. Holt PG, Macaubas C. Development of long-term tolerance versus sensitisation to environmental allergens during the perinatal period. Curr Opin Immunol 1997; 9: 782-787. Stanley FJ, Croft ML, Gibbins J, Read AW. A population database for maternal and child health research in Western Australia using record linkage. Paed Perinat Epidem 1994; 8: 433-447. Stanley FJ, Watson L. Methodology of a cerebral palsy register. The Western Australian experience. Neuroepidemiology 1985; 4: 146-160. Bower C, Stanley FJ. Dietary folate as a risk factor for neural-tube defects: evidence from a case-control study in Western Australia. Med J Aust 1989; 150: 613-619. Kees UR, Burton PR, Lu C, Baker DL. Homozygous deletion of the p16/MTS1 gene in pediatric acute lymphoblastic leukemia is associated with unfavorable clinical outcome. Blood 1997; 89: 4161-4166. Salvati PD, Ranford PR, Ford J, Kees UR. HOX11 expression in pediatric acute lymphoblastic leukemia is associated with T-cell phenotype. Oncogene 1995; 11: 1333-1338. Thomas WR, Smith W. House dust mite allergens. Allergy 1998; 53: 821-832. Thomas WR, Smith W, Hales BJ. House dust mite allergen characterisation: implications for T-cell responses and immunotherapy. Intern Arch Allergy Immunol 1998; 115: 9-14. Thomas WR, Flack FS, Callow MG, Chua KY. A high-molecular-weight outer membrane protein that is a potential target for protective immunity to type b and untypeable Haemophilus influenzae. J Infect Dis 1992; 165 Suppl 1: S75-S76. Stumbles PA, Thomas JA, Pimm CL, et al. Resting respiratory tract dendritic cells preferentially stimulate Th2 responses and require obligatory cytokine signals for induction of Th1 immunity. J Exp Med 1998. In press. McMenamin C, Pimm C, McKersey M, Holt PG. Regulation of IgE responses to inhaled antigen in mice by antigen-specific gamma delta T cells. Science 1994; 265(5180): 1869-1871. Author's details TVW Telethon Institute for Child Health Research, Perth, WA. Fiona Stanley, AC, MD, FAFPHM, FRACP, Director, and Variety Club Professor of Paediatrics, The University of Western Australia. Reprints: Professor Fiona Stanley, TVW Telethon Institute for Child Health Research, PO Box 855, West Perth, WA 6872. Email: infoATichr.uwa.edu.au URL: http://www.ichr.uwa.edu.au Journalists are welcome to write news stories based on what they read here, but should acknowledge their source as "an article published on the Internet by The Medical Journal of Australia <http://www.mja.com.au>". <URL: http://www.mja.com.au/> Milestones for the TVW Telethon Institute for Child Health Research Year Corporate history Research highlights 1985–1990 Planning for an Institute: including international review Cloning of house dust mite allergens (Wayne Thomas et al, from 1988) 1989 Professor Fiona Stanley appointed Director 5 year NHMRC project awarded to Epidemiology division 1990 Institute opened with a Board of Directors and Scientific Advisory Committee and the following research divisions: Cell Biology (Patrick Holt), Molecular Biology (Wayne Thomas), Epidemiology (Fiona Stanley), Leukaemia and Cancer (Ursula Kees) Cloning of outer membrane protein of all types H influenzae (vaccine candidate) (Wayne Thomas et al) 1991 Affiliation with The University of Western Australia Commonwealth grant to complete laboratories Psychosocial Research (Stephen Zubrick) Clinical Sciences (Peter Sly) Folate confirmed to prevent neural tube defects (Carol Bower and Fiona Stanley) 1992 Affiliation with Princess Margaret Hospital for Children Senior Biostatistician appointed (Paul Burton) Launch of Hib vaccination program World first folate and NTD prevention project launched 1993 New Board and other committees: Intellectual Property, Finance, Fundraising Molecular Immunology (Colin Sanderson) Cell Adhesion Laboratory (Dierdre Coombe) WA Child Health Survey commenced 1994 Biostatistics and Computing (Paul Burton) becomes a division Epidemiology Division now headed by Carol Bower Immune deviation by g/d T cells (Christine McMenamin and Patrick Holt) 1995 Administration and Corporate Services established (Robert Ginbey) State Government pledge for new building "Give every Child a Chance" fundraising campaign ($10 800 000 pledged) International review Child Health Survey Vol 1 (Stephen Zubrick and Sven Silburn) HOX 11 deregulation in T cell leukaemias (Patricia Salvati and Ursula Kees) 1996 Consolidation of infrastructure (UWA, HDWA) New approach to Commonwealth Government for building grant First NHMRC Program for Public Health (Maternal and Child Health) Child Health Survey Vol 2 (Stephen Zubrick and Sven Silburn) Only one case of Hib meningitis reported (after vaccination program) Aboriginal maternal and child health research project in Goldfields becomes a government-funded health service 1997 Joint announcement of Capital Works Grant totalling $22 500 000 from State and Commonwealth Governments Child Health Survey Vol 3 (Stephen Zubrick and Sven Silburn) First reduction in rate of NTD (from average of 2 to 1.2 per 1000) 1998 Commence new building program in September Persistence of fetal Th2 immune responses in atopic versus non-atopic individuals (Susan Prescott and Patrick Holt) 2000 New building complete Second international review

Fiona Stanley

Synopsis Casemix funding was introduced first in Victoria in 1993-94, and since then most States have moved towards either casemix funding or using casemix to inform the budget setting process. The five States implementing casemix have adopted some common funding elements: all use AN-DRG-3; all have introduced capping, most commonly at the hospital level; and all ensure accuracy of diagnosis and procedure coding through coding audits. Two funding models have been developed. The fixed and variable model involves a fixed grant for hospital overhead costs and a payment for each patient treated, covering only variable costs. The integrated model provides an integrated payment to hospitals for each patient treated, covering both the fixed and variable costs. There are different weight setting processes and base prices between the States, which result in marked differences in the price paid for the same type of case treated in similar hospitals. Learning across State boundaries should be encouraged, with knowledge of what is effective and what is ineffective in casemix funding arrangements being used to develop Australian best practice in this area. Introduction In Australia, casemix funding was first introduced in Victoria in 1993-94,1 as part of a program of public sector restructuring to reduce expenditure and improve the efficiency.2,3 South Australia4 followed in 1994-95, with a casemix funding approach modelled substantially on the Victorian scheme5 and also accompanied by significant budget cuts. Since then, Western Australia6 and Tasmania7 have also implemented casemix funding (both in 1996-97), and Queensland8 has commenced a phasing-in process for casemix funding. New South Wales is the only State which has eschewed casemix funding arrangements, instead structuring providers on the basis of an area responsibility for hospitals and other service units (eg, community health centres). Funding is distributed to areas based on their population. Even in New South Wales, policy documents emphasise the importance of casemix in informing budgets for hospitals and in paying for patients across regional boundaries.9 The Northern Territory and the Australian Capital Territory have also incorporated elements of casemix funding, but because of their small populations and small number of distinct providers, funding arrangements are essentially determined individually, even when an elaborated formula is used.10 Initial casemix implementation required an unravelling of hospital activity into the major streams of care: inpatient, outpatient, and teaching and research. Casemix implementation focused first on inpatient services where classification for describing services or "products" was the most sophisticated. Inpatient funding arrangements The essence of casemix funding for inpatient services is quite simple: the budget for a hospital is based on the number and type of patients treated in the hospital. The development of diagnosis-related groups (DRGs) as clinical and resource homogeneous categories for inpatients11 provided a means of grouping types of patients treated, which could be used for payment purposes. The budgets of hospitals could thus be determined primarily on performance or output, rather than negotiation, history or politics. The five States implementing casemix funding have all adopted some common funding elements. Firstly, a common nomenclature is used: all States currently use version 3.1 of Australian national diagnosis-related groups (AN-DRGs). Secondly, as these funding arrangements coincided with budget reductions, all the States have introduced capping, most commonly at the hospital level with hospital-specific targets. In some States, the throughput targets are flexible -- if hospitals exceed these targets, they receive additional funding, albeit at a marginal price. Thirdly, with DRG assignment based on recorded diagnosis and procedure codes, all States have introduced coding audits to ensure accuracy of recording. Other aspects of inpatient casemix funding reveal remarkable variability between the States. The Box compares key elements of inpatient funding arrangements across the States. Funding models Two basic funding models have been developed. The initial Victorian model was based on fixed and variable components, following the recommendations of the 1990 Scotton and Owens review of the prospects of casemix funding in Australia.12 Queensland has also adopted this model. A fixed and variable model involves two elements: a fixed grant to cover hospital overhead costs, and a payment for each patient treated covering only the variable costs of that patient. The theory behind this approach is that efficiency is maximised if the incentives are such that hospitals can treat additional patients up to the point at which marginal treatment cost equals marginal revenue. Marginal revenue is the variable payment made by State health authorities. This fixed and variable model mitigates the incentive for hospitals to maximise admissions. After current capacity limits are reached, additional fixed costs are required (eg, for commissioning new wards), but these are not fully reimbursed by the funding system. Thus, States retain control over growth in system capacity. The alternative model is used in Western Australia and Tasmania, which both provide an integrated payment to hospitals for each patient treated covering both the fixed and variable costs. South Australia also uses an integrated payment system, but if a hospital does not achieve the negotiated volume target, payments are discounted, effectively recognising that the savings to hospitals are at marginal or variable costs. Cost variability It would be expected that the utility of treating a patient in a particular DRG would be constant across all hospitals. Likewise, logically, the payment for that DRG should be the same, regardless of the hospital. However, the different State funding systems recognise that there are differences in costs and four of the State systems (Victoria, Queensland, Western Australia and South Australia) have established several funding subgroups that receive different payments. Interestingly, assumptions about economies of scale vary. The Victorian and Western Australian systems assume economies of scale exist, as the payment for a patient in a particular DRG is less in a larger hospital than in a smaller hospital. On the other hand, in Queensland and South Australian diseconomies of scale are assumed and payments are higher in larger hospitals than in smaller hospitals. Divergence in weights The weight setting process also differs across the country. Three States (Queensland, South Australia and Tasmania) use variants of the weights developed as part of the national cost weight study, which are derived from cost modelling undertaken as part of national costing studies.13 Victoria and Western Australia, on the other hand, use data from clinical costing systems in their own State to set weights. In Victoria, for example, weights are set using a dataset of patient costs from over 0.5 million recorded patient admissions to 15 Victorian public acute hospitals in the financial year two years prior to the payment year.14 Price differences As a result of these different weight setting processes, different relative weights are used across the country for each DRG, as well as different base prices. The different prices and weights mean that there are differences between States in the price paid for the same case treated in a similar hospital. This effect can be seen with AN-DRG 674, Vaginal delivery without complicating diagnoses. In the two States with fixed and variable funding (Victoria and Queensland) the variable price paid for an inlier patient in AN-DRG 674 in a major hospital in 1997-98 varies by more than 20% ($925 in Victoria versus $1121 in Queensland). Similarly, in the integrated funding States there is a difference of more than 40% ($1455 in South Australia versus $2097 in Tasmania, with the Western Australian price lying in between these at $1685). Payment differences of this size need some explanation. Firstly, in some DRGs, these differences might reflect differences in inpatient payment system design (eg, in intensive care payments), but this should not be relevant in this DRG. Secondly, they might be attributable to differences in other aspects of the payment system (eg, in training and development), but this would not be sufficient to account for the magnitude of the payment differences. Finally, the differences might reflect different input costs, a factor taken into account in payment system design in the United States.15 However, most employees in public hospitals are now covered by Federal awards and so input price variation is not a feasible explanation. It is thus difficult to see how cost differences of this order of magnitude can be justified for this reasonably homogeneous DRG. Outliers The DRG classification system has been developed to describe the normal, or typical, case in a DRG, known as an inlier. Outlier cases are those which do not fit the normal pattern and, in terms of distribution, lie outside so called "trim points". The basis for setting trim points, and thus determining outliers in all States, follows work done by McGuire et al on the effect of different trim point methods.16 The common trimming method used in Australia is the L3H3 method: the low trim point is a third of the average length of stay, and the high trim point is three times the average length of stay. Some States use modifications of this approach: Queensland has an extra high trim point based on five times average length of stay; and in South Australia the low trim point is determined parametrically at 3 SD below the mean length of stay (where average length of stay is greater than four days). Two States, Western Australia and South Australia, also have trim points based on cost, which provide for additional funding for cases identified as costing more than $75 000 and $60 000, respectively. The cost-based trim points rely on hospitals having robust clinical costing systems with agreed bases for allocation of costs, as different assumptions about allocation of overhead costs, for example, can significantly affect the recorded cost of a case.14 Intensive care Intensive care funding is a particularly sensitive issue, given that variation in system-wide use of intensive care cannot be fully explained by variation in epidemiological and demographic factors.17 There is considerable variation across States in the funding arrangements for intensive care units, and the payment systems have quite different incentive effects. Within an individual hospital there can also be differential incentives on intensive care unit staff to admit to hospital or retain patients within the unit, depending on the funding structure. Victoria and Tasmania provide no specific additional funding for intensive care units. Western Australia provides block funding for intensive care units on top of the existing funding arrangements. In South Australia intensive care units are effectively funded on a per diem basis, with the DRG cost weight calculation being adjusted to exclude intensive care costs. Private patients Costs of private patients obviously differ from those of public patients. Private patients' medical costs (including pathology and radiology costs) and prostheses costs are met by the patients themselves, and are normally reimbursed by health insurance funds. Hospitals also accrue revenue from these patients. The Victorian and Queensland funding models provide differential payments for public and private patients to take account of these different cost structures. Western Australia provides a block payment to compensate for the differing proportion of public patients. On the other hand, the South Australian and Tasmanian arrangements do not provide differential payments, and although revenue differences are compensated for, there would still be an effective incentive to admit private rather than public patients because of the lower hospital costs for private patients. Conclusion Five States have either implemented or are in the process of implementing casemix funding, but the funding models used have significant design differences. Some of the systems are clearly fairer to hospitals than others, and it is therefore not surprising that recent reviews of both Victorian and South Australian formulas have indicated that providers believe that there are still problems in funding design.18,19 Although the design of a funding system is in part a technical process to ensure that hospitals have appropriate incentives for efficiency, it is also a political process insofar as providers need to be assured that the funding formula is fair. The large variation in prices for the indicator DRG used in this article (DRG 674) also suggests an element of inequality between States in pricing strategies. Design of a casemix funding system involves a number of complex technical choices to maintain appropriate balances between competing policy objectives (eg, minimising waiting lists versus reducing stays in hospital emergency departments). Similarly, maintenance of casemix payment systems needs to take account of changes in health technology and to monitor perverse effects of funding system design. There is thus a strong argument that there should be some form of joint development to facilitate better funding system design. State casemix funding arrangements have evolved in a number of areas, such as in the weight setting processes and in the elaboration of the role of the purchaser (including how volume controls are implemented). Although casemix funding arrangements are characterised by relatively low transaction costs, annual funding policy reviews in each State probably incorporate unnecessary overheads. Differences between the States should not preclude the possibility of learning across State boundaries. As casemix funding enters a more mature phase, knowledge of what is effective and what is ineffective in casemix funding arrangements should be used to develop Australian best practice in this area. National cooperation (and national leadership) produced an agreed national casemix classification. Further national action is warranted to facilitate transfer of the best practice elements of each State's funding systems. This should occur early in casemix funding development to reduce the costs incurred by States "reinventing the casemix funding wheel" each year. Furthermore, there remain several areas in which casemix funding is deficient; for example, in identifying and funding teaching and research activities of hospitals, and in the development of funding policy in ambulatory care. Cooperative national action in these areas is needed. References Duckett SJ. Hospital payment arrangements to encourage efficiency: the case of Victoria, Australia. Health Policy 1995; 34: 113-134. Alford J, O'Neill D, editors. The contract state: public management and the Kennett government. Melbourne: Deakin University Press, 1994. Armstrong A. A comparative analysis: new public management -- the way ahead? Aust J Public Adm 1998; 57: 12-24. Department of Human Services. Victoria -- public hospitals: policy and funding guidelines 1997-98. Melbourne: Department of Human Services, 1997. South Australian Health Commission. Casemix funding for health -- hospitals -- 1997-98. Adelaide: South Australian Health Commission, 1997. Health Department of Western Australia. Western Australian government health system funding 1997/1998: Budget reform. Perth: Health Department of Western Australia, 1997. Department of Community and Health Services. Casemix: managing resources for care (policy paper). Hobart: Artemis, 1997. Queensland Health. Hospital funding model for Queensland public hospitals: policy and technical papers 1997/98. Brisbane: Queensland Health, 1998. NSW Health Department. Implementation of the economic statement for health. Sydney: NSW Health Department, 1996. (PDD No. 96-0081.) Beaver C, Zhao Y, McDermid S, Hindle D. Casemix-based funding of Northern Territory public hospitals: adjusting for 36 severity and socio-economic variations. Health Econom 1998; 7: 53-61. Fetter RB, Shin Y, Freeman JL, Averill RF. Case mix definition by diagnosis related groups. Med Care 1980; 18 (2 Suppl): 1-53. Scotton RB, Owens HJ. Case payment in Australian hospitals: issues and options. Melbourne: Public Sector Management Institute, Monash University, 1990. Commonwealth Department of Human Services and Health. Report on the development of AN-DRG version 3 cost weights. Canberra, The Department, 1995. Jackson T, Wilson R, Watts J, et al. Final Report of the 1997 Victorian Cost Weights Study. Melbourne: Victorian Department of Human Services, 1998. Duckett SJ. Health care in the US: what lessons for Australia? Sydney: The Australian Centre for American Studies, University of Sydney, 1997. McGuire TE, Bender JA, Maskell C. Casemix episodic payment for private health insurance. Canberra: AGPS, 1995. Jackson T, Macarounas-Kirchmann K. Changing patterns of intensive care unit admission and length of stay in five Victorian hospitals. In: Selby-Smith C, editor. Economics and health: 1992. Melbourne: Monash University/NCHPE, 1993: 149-164. Auditor-General of Victoria. Acute health services under casemix: a case of mixed priorities. Melbourne: Victorian Government Printer, 1998. (Special Report No. 56.) Brooker J. An evaluation of casemix funding in South Australia 1994-95. Canberra: Commonwealth Department of Health and Family Services, Casemix Development Program, 1996. Authors' details La Trobe University, Melbourne, VIC Stephen J Duckett, BEc, MHA, PhD, Professor of Health Policy; and Dean, Faculty of Health Sciences. Reprints: Professor S J Duckett, Faculty of Health Sciences, La Trobe University, Bundoora, VIC 3083. E-mail: s.duckettATlatrobe.edu.au

Synopsis The costs of subacute care (palliative care, rehabilitation medicine, psychogeriatrics, and geriatric evaluation and management) and non-acute care (nursing home, convalescent and planned respite care) are not adequately described by existing casemix classifications. The predominant treatment goals in subacute care are enhancement of quality of life and/or improvement in functional status and, in non-acute care, maintenance of current health and functional status. A national classification system for this area has now been developed -- the Australian National Sub-Acute and Non-Acute Patient Classification System (AN-SNAP). The AN-SNAP system, based on analysis of over 30 000 episodes of care, defines four case types of subacute care (palliative care, rehabilitation, psychogeriatric care, and geriatric evaluation and management) and one case type of non-acute care (maintenance care), and classifies both overnight and ambulatory care. The AN-SNAP system reflects the goal of management -- a change in functional status or improvement in quality of life -- rather than the patient's diagnosis. It will complement the existing AN-DRG classification. Introduction The Australian healthcare system is about to implement a new casemix classification system for subacute and non-acute care, the costs of which are not adequately described by traditional diagnostic tools. Subacute care comprises palliative care, rehabilitation medicine, psychogeriatrics, and geriatric evaluation and management. Non-acute care includes nursing home, convalescent and planned respite care. The new casemix classification system, which includes hospital as well as community care, reflects the goal of management -- a change in functional status or improvement in quality of life -- rather than the underlying patient diagnosis. Background Subacute casemix has been evolving for 15 years. In 1983, when the United States Health Care Financing Administration decided that payments for hospital care would be on a prospective payment system, based on acute-care diagnosis-related groups (DRGs), rehabilitation, psychiatric, children's and long-term facilities were specifically excluded. It was recognised that these forms of care, although not acute, were still complex and expensive and required long hospital stays. In 1987, a US Department of Health and Social Services report reiterated that their current DRG system did not adequately take into account the special circumstances of patients requiring long hospital stays.1 Studies in the United States over the following few years not only confirmed that DRGs did not adequately describe costs in one of these areas of care (rehabilitation medicine),2 but that as a consequence quality of care had deteriorated, as measured by changed length of hospital stay, increased readmission rates and a rising number of nursing home admissions.3-5 As casemix development progressed in Australia, Australian studies6-12 also expressed the need for a different approach for costing of rehabilitation,6,8-10,12 geriatric evaluation and management,6,9,12 palliative care7,9,11,12 and psychogeriatrics.6,12 The term subacute care was coined in 199213 to describe "care which is provided for a person who requires health services but whose principal medical diagnosis (modified for factors such as age and procedures) is not adequate in explaining the need for, or the cost of, the services that s/he receives". Goals of subacute and non-acute care In subacute care the predominant goal is enhancement of a patient's quality of life and/or improvement in his or her functional status. In non-acute care the predominant goal is maintenance of a patient's current health and functional status. Because of this difference in goals, it was expected that factors other than diagnosis were more likely to explain the costs of these forms of care. Rehabilitation: Factors contributing to the success of rehabilitation programs have included patient characteristics such as functional status on admission, age, disease site, time from referral to beginning of program, comorbidities such as cognitive function and depression, and availability of resources.14-16 The factor which appears in US and Australian studies to predict cost most accurately in these areas of care is a patient's functional status on admission.12,15-17 Palliative care: Australian clinicians were instrumental in developing a casemix classification system with a primary approach from a clinical perspective. The development involved broad consultation and collaboration. The palliative care classification identified stage of illness or palliative care phase (eg, stable, deteriorating, terminal), symptom severity and acuity level (or nursing dependency) as the major factors explaining costs for this form of care.7 Psychogeriatrics and other aged care: The goals of admission in aged care are improving health status, modifying symptoms and enhancing function, living conditions, behaviour and quality of life.12 Subacute and non-acute care classifications Several classification systems for subacute and non-acute episodes of care have been developed, including the Resource Utilisation Groups and the California Long Term Care System.18 The Resident Classification Index19 is an Australian classification system used in nursing homes to classify non-acute episodes of care. In the United States the FIM-FRG system (Functional Independence Measure- Function Related Groups)17 for rehabilitation medicine is the most developed. Studies in Australia have continued to demonstrate that the best predictor of cost for subacute care is the goal of care. The most recent studies are the 1995 Victorian Rehabilitation Casemix Report10 and the 1996 NSW Sub-Acute Casemix Area Network Project.12 AN-SNAP study The Australian National Sub-Acute and Non-Acute Patient Casemix Study20 was conducted in 1996 in 99 hospital and community health sites in all Australian States and Territories and in five sites in New Zealand. Over 30 000 episodes of care were analysed, including overnight, same day, outpatient and community episodes of care. The study established that there are five case types of subacute and non-acute care. Subacute care includes palliative care, rehabilitation, psychogeriatric care, and geriatric evaluation and management; and the final case type -- maintenance care -- is defined as non-acute care. Each of the five case types is defined according to the characteristics of the patient and the goal of care, and not the institution or service in which she or he is treated (eg, a patient may receive geriatric evaluation and management in a hospice, or palliative care in a rehabilitation unit). A critical finding of the study was that across the spectrum of case types and classes there is significant diversity in the cost of subacute and non-acute care for both overnight and ambulatory episodes. For example, there is a 30-fold variation in episode cost and a five-fold variation in per diem cost between the most expensive and the least expensive classes in the overnight classification, thus confirming the necessity for a classification in this area to allow for appropriate output-based funding. AN-SNAP classification system From the study, a national classification for subacute and non-acute care was developed -- the Australian National Sub-Acute and Non-Acute Patient Casemix Classification System, or AN-SNAP classification.20 AN-SNAP version 1 (Box 1)21 classifies both overnight and ambulatory care. It has 134 classes and the classification explains 58% of the variation in all episode costs. Of this 58%, 21% is contributed by episode type and 37% by the classes. The overnight branch has 66 classes and the classification explains 47% of the variance in the cost of overnight care. The ambulatory branch has 68 classes and the classification explains 28% of the variance in the cost of ambulatory care. These results are an improvement on the performance achieved by acute-care DRGs. Analysis of the decision trees for overnight and ambulatory care in Box 1 shows the factors which have been incorporated into the system as predictors of cost. Palliative care -- phase, functional dependence as measured by RUG-ADL (resource utilisation groups - activities of daily living),18 and age; Rehabilitation -- impairment groupings, functional status as measured by FIM (Functional Independence Measure),22 and age; Psychogeriatrics -- psychiatric symptom severity and functional status as measured by the HoNOS (Health of the Nation Outcome Scale);23 Geriatric evaluation and management -- cognitive status in addition to motor capacity and age; and Maintenance care -- functional status. The AN-SNAP study showed that the variables driving costs in the inpatient setting are also important cost drivers in the ambulatory setting. However, community care is inherently more complex than institutional care. Common variables across institutional and community care are necessary, but are insufficient in explaining cost variations. In consequence, the classification makes use of some community variables not required in institution care (eg, provider type and assessment or treatment episode). Implications of AN-SNAP The implementation of this classification has important implications. Firstly, a number of classifications are now available in Australia and policy decisions on the interaction between these classifications are required. Secondly, data on many of the characteristics used in AN-SNAP are currently collected by individual service providers, but most are not routinely collected by existing hospital and community information systems. AN-SNAP, along with its further development, has been endorsed by the Australian Casemix Clinical Committee for adoption as the national classification for sub- and non-acute care. Implementation remains a State and Territory issue which requires a planned, staged approach. Already some States, including Queensland and New South Wales, are implementing AN-SNAP, and others have indicated their intention to do so in the near future. The adoption of the system will complement the existing DRG system, as illustrated in the New South Wales approach (Box 2). References Batavia AI, DeJong G. Prospective payment for medical rehabilitation: the DHSS Report to Congress. Arch Phys Med Rehabil 1988; 69: 377-380. Stineman MG, Escarce JJ, Goin HE, et al. A case-mix classification system for medical rehabilitation. Med Care 1994; 32: 366-379. Evans RL, Hendricks RD, Bishop DS, et al. Prospective payment for rehabilitation: effects on hospital readmission, home care and placement. Arch Phys Med Rehabil 1990; 71: 291-294. Fitzgerald JF, Fagan LF, Tierney WM, Dittus RS. Changing patterns of hip fracture care before and after implementation of the prospective payment system. JAMA 1987; 258: 218-221. Heinemann AW, Billeter J, Betts HB. Prospective payment for acute care: impact on rehabilitation hospitals. Arch Phys Med Rehabil 1988; 69: 614-618. Roberts R, McKinley S, Brooks B, et al. The Australian National Non-Acute Inpatient Project. Aust Health Rev 1993; 16: 300-319. Smith M, Firms P. Palliative Care Casemix Classification -- testing a model in a variety of palliative care settings -- preliminary results. Proceedings of the Sixth Australian Casemix Conference; 1994 Aug 29-31; Hobart. Canberra: Commonwealth Department of Human Services and Health, 1994. Baker W. Casemix in rehabilitation -- is it safe to dip into functionally related groups? Proceedings of the Sixth Australian Casemix Conference; 1994 Aug 29-31; Hobart. Canberra: Commonwealth Department of Human Services and Health, 1994. Lee L, Goor E, Kennedy C, et al. Non-acute casemix in the Illawarra. J Qual Clin Pract 1994; 14: 23-30. Coopers & Lybrand. Rehabilitation Casemix Project. Final Report. Melbourne: Victorian Department of Health and Community Services, 1995. Hindle D. The Victorian Palliative Care casemix project: statistical analysis and funding recommendations. Wollongong: Centre for Health Service Development, University of Wollongong, 1995. Eagar K, Cromwell D, Kennedy C, Lee L. Classifying sub-acute and non-acute patients: results of the NSW Casemix Area Network Study. Aust Health Rev 1997; 20: 56-74. Eagar K, Innes K. Standard definitions and source data for hospitals in Australia, Canberra: Commonwealth Department of Health, Housing and Community Service, 1992. Carey RG, Posavac EJ. Who makes the most progress in inpatient rehabilitation? An analysis of functional gain. Arch Phys Med Rehabil 1988; 69: 337-343. Rondinelli RD, Murphy JR, Wilson DH, et al. Predictors of functional outcome and resource utilisation in inpatient rehabilitation. Arch Phys Med Rehabil 1991; 72: 447-453. Stineman MG, Escarce JJ. Analysis of casemix and the prediction of resource use in medical rehabilitation. Phys Med Rehabil Clin North Am 1993: 4: 451-461. Stineman MG, Escarce JJ, Goin HE, et al. A case-mix classification system for medical rehabilitation. Med Care 1994; 32: 366-379. Fries BE, Cooney LM. Resource Utilisation Groups: a patient classification system for long term care. Med Care 1985; 23: 110-132. Commonwealth Department of Health, Housing and Community Services. Classification of nursing home residents. Handbook for directors of nursing. Canberra: DHHCS, 1992. Eagar K, et al. The Australian National Sub-Acute and Non-Acute Patient Classification (AN-SNAP): report of the National Sub-Acute and Non-Acute Casemix Classification Study. Wollongong: Centre for Health Service Development, University of Wollongong, 1997. Eagar K. The Australian National Sub-Acute and Non-Acute Patient (AN-SNAP) Casemix Classification. Proceedings of the Ninth Australian Casemix Conference; 1997 Sep 7-10; Brisbane. Canberra: Commonwealth Department Health and Family Services, 1997. Center for Functional Assessment Research, Uniform Data Set for Medical Rehabilitation. 1993 Guide to the Uniform Data Set for Medical Rehabilitation (Adult FIM), V4.0. Buffalo: State University of New York, Buffalo, 1993. Wing JK, Beevor AS, Curtis RH, et al. Health of the Nation Outcome Scales (HoNOS). Research and development. Br J Psychiatry 1998; 172: 11-18. Authors' details South Eastern Sydney Area Health Service, Sydney, NSW. Lynette A Lee, FAFRM, FRACMA, Director Clinical Services. Centre for Health Service Development, University of Wollongong, Wollongong, NSW. Kathy M Eagar, MA(Psych), Associate Professor and Director. Neringah Palliative Care Service, Sydney, NSW. Michael C Smith, MB BS, MRACMA, Director. Reprints will not be available from the authors. Correspondence: Dr L A Lee, South Eastern Sydney Area Health Service, PO Box 430, Kogarah, NSW 1485. E-mail: leelATsesahs.nsw.gov.au

Synopsis The Outpatient Costing and Classification Study was commissioned by the Department of Health and Family Services to evaluate the suitability of the Developmental Ambulatory Classification System (DACS). Data on the full range of ambulatory services (outpatient clinics, emergency departments and allied health services) were collected prospectively from a stratified sample of 28 public hospitals. Patient encounters captured in the study represent 1% of the total ambulatory encounters in Australia in one year. Costing per encounter included time spent with the patient, cost of procedures, indirect costs (salaries and consumables), overhead costs and diagnostic costs. The most significant variable explaining cost variation was hospital type, followed by outpatient clinic type. Visit type and presence or absence of a procedure -- major splits for the proposed DACS -- did not produce splits that were consistent across all hospital strata. The study found that DACS is not an appropriate classification for hospital ambulatory services. A clinic-based structure for outpatients and allied health departments is recommended for classifying and funding ambulatory services in Australia. Introduction The Casemix Development Program which commenced in Australia in July 1988 focused on developing and implementing a national inpatient classification system for acute patients (AN-DRGs). Relatively little work was done on classifying and costing ambulatory services. In the early 1990s, however, two projects were conducted -- the National Ambulatory Casemix Project in Sydney1 and the Flinders Medical Centre Ambulatory Encounters Project in Adelaide,2 the latter in conjunction with the Royal Children's Hospital in Melbourne. These were primarily "demonstration" projects, which tested some overseas classifications and identified issues for future ambulatory classification projects. In 1994, the National Ambulatory Care Reform Program focused attention on ambulatory services by funding studies to facilitate health policy development in this area.3 However, none of these projects addressed the need for a nationally consistent ambulatory classification system. Recognising this, the Department of Health and Family Services requested that the Australian Casemix Clinical Committee establish a subcommittee to oversee the development of an ambulatory classification system for use in Australia. This committee reviewed existing classifications for their applicability in Australia,4 concluded that none were appropriate and recommended that a new classification system be developed to complement other patient-based classification systems. This work resulted in the Developmental Ambulatory Classification System (DACS), which was patient-based and structured around Ambulatory Major Diagnostic Categories (AMDC), similar to the Major Diagnostic Categories of the AN-DRG classification. The major splits in the proposed classification were based on whether the patient was making a new or a repeat visit, and whether a significant procedure was performed (Box 1). A specially constructed expert panel identified which outpatient and emergency procedures were significant cost drivers. In contrast to the other major classification systems, this classification was not based on empirical data. DACS needed to be evaluated for its suitability as a national classification. To address this issue an Outpatient Costing and Classification Study was commissioned by the Commonwealth Department of Health and Family Services in 1997. Methods The Outpatient Costing and Classification Study was conducted in two phases. Phase 1: Selecting and defining the data elements to be captured during the study and developing a sampling framework (conducted by Deloitte Touche Tohmatsu).5 Phase 2: Data capture and analysis of the results (conducted by Coopers & Lybrand and the South Australian Health Commission).6 The study aimed to include the full range of ambulatory services provided in public hospitals. For the purpose of the study, the term "ambulatory service" encompassed designated outpatient clinics (irrespective of location), emergency departments and allied health services for non-admitted patients. Because hospitals' recording of patient activity varies, the study also included same-day patients and inpatients treated within the outpatient and emergency departments. Hospitals Data were collected prospectively from a stratified sample of Australian public hospitals. South Australian hospitals were over-represented, because a similar State-based research project was initiated in South Australia before the Commonwealth project. Twenty-eight hospitals participated in the study. They included eight teaching hospitals, two specialist hospitals, two metropolitan hospitals, seven large rural hospitals and nine small rural hospitals (Box 2). Data collection Senior staff from each hospital met with the consultants before study commencement to ensure optimal data collection, and all hospitals employed a project officer to facilitate on-site coordination. To ensure data accuracy, a quality management plan was developed, including tolerance reports and edit checks on the data. Data collection commenced in September 1997 and continued in SA hospitals for three months, and at other sites for one month. Because of the difficulty in collecting detailed patient data in busy emergency departments, the collection period in emergency departments was four weeks in South Australia and two weeks in other States. Detailed utilisation data were obtained for each patient in the study (Box 3). A patient encounter was defined as "an interchange between one or more healthcare providers and one or more patients, for assessment, consultation and/or treatment for intended unbroken period of time". Telehealth consultations (including videoconferencing, telemedicine and telephone contacts) were included if the clinician who had previously seen the patient was present, and when the service was considered to be a substitute for face-to-face contact. Radiology and pathology services and dispensed pharmaceuticals were not considered encounters in their own right, but were subsequently linked to the "primary" encounter (ie, the encounter in which the services were ordered). Reviewing results, dictating letters and making telephone calls, which are generally consistent across all encounters, were included as indirect costs (although some clinicians elected to record the time associated with these activities as direct patient contact time). Telephone calls were recorded if the clinician who had previously seen the patient was present and when the service was considered to be a substitute for face-to-face contact. Indirect encounters related to consultations with key providers and relatives of patients in which the patient was the focus of the encounter. Group encounters were defined as encounters with more than one patient and/or more than one practising clinician present. All hospital-paid staff who were involved in providing patient care were requested to record the amount of time they spent in direct patient contact. This has been previously reported as the most variable aspect of an outpatient encounter.1 Specific proformas were developed to collect details on nursing time, medical time, allied health time, diagnostic services (pathology and imaging) and therapeutic services (pharmaceuticals). Coding Accurate diagnosis and procedure coding are not routinely collected for ambulatory patients in Australia. ICD-9-CM classification to the three-digit level was adopted as the minimum standard for coding during the project. This did not reduce the specificity of the clinical data, with some 4364 different codes being used across the study. Coding to the fourth and fifth digit was permissible if desired by clinicians. Standardising the clinic profile A set of generic outpatient clinics had to be established to standardise the profile of outpatient clinics within Australian hospitals. The use of outpatient clinics as a classification variable had been supported by several ambulatory studies, including the Victorian Ambulatory Classification System,7 the Queensland Health Ambulatory Project,8 and the Flinders Medical Centre Ambulatory Encounters Project.2 From these sources a list of 76 generic clinics was identified. Data collection sites were requested to map their clinics to this list. Some hospitals had difficulty in mapping their very specialised clinics. In these situations additional clinic names were added. With these refinements a final generic clinic list comprising 78 clinics was obtained. Costing data Patient level cost data were used to determine the cost of each encounter in four steps: Direct costs: The cost of direct time spent with a patient and the cost of significant procedures for individual encounters were allocated to the specific encounter. Indirect costs: Salary costs and costs for consumables (derived by deducting direct cost from total expenditure reported in line items in ambulatory cost centres) were dispersed across all ambulatory encounters. Overhead costs: Overhead costs, determined by an approach similar to that employed in COSMOS,9 were dispersed across all ambulatory encounters. This process allows all costs incurred in providing services -- power, cleaning and infrastructure costs as well as direct costs -- to be allocated to an individual encounter. Diagnostic costs: Patient specific utilisation data relating to radiology, pathology and pharmacy were downloaded from hospitals' information systems. Standardised unit prices were adopted for radiology and pathology services. This was set at 85% of the Medical Benefits Schedule (MBS) fee. Pharmacy costs were directly allocated and included Section 100 drugs. These costs were directly allocated to the primary ambulatory encounter. Most hospitals in the study were able to provide detailed costing information, with the exceptions being some of the small hospitals in South Australia. To estimate outpatient cost in these hospitals, a proxy outpatient fraction was derived from information obtained during the National Hospital Cost Data Collection Study. Statistical analyses Statistical analysis of the data measured the significance of the associations between the independent variables and the dependent variable, which in this case was cost. Results The study collected clinical and demographic data on 248 608 patient encounters (Box 4). Additional data were incorporated into the database: two previous emergency department studies (the Flinders Medical Centre Emergency Department Study10, and the Women's and Children's Emergency Department Study11); the Mental Health Classification and Service Costing Project (MH-CASC) relating to ambulatory encounters in the Mental Health Division of the Women's and Children's Hospital;12 and data from Launceston and Burnie Hospitals in Tasmania. The patient encounters captured in the study represent about 1% of the total hospital ambulatory encounters in Australia each year.10 Over 82% of these encounters were referred from three sources: other services within the hospital (33%); community general practitioners (28%) and self-referral (22%). The high proportion of self-referred patients was due to the inclusion of emergency department data. Thirty-four per cent of all encounters were new visits. The average cost of a new visit was $128, and of a repeat visit, $110. There were 10% more female than male patient encounters in the study population, and the number of public patient encounters greatly exceeded other types (86.6% of patients were public, 7.6% private, and 5.7% Department of Veterans' Affairs). Of the patient encounters analysed, 95% were direct encounters, 3.5% were telephone encounters and 1.5% were indirect contacts. The average cost for these encounters was $116 (direct), $129 (indirect), $115 (telephone) and $152 (telemedicine), respectively. There were only 46 telemedicine encounters captured during the study period. This represented 0.02% of total encounters. The costs of providing services to patients in hospital outpatient departments and in the ambulatory service components of hospital allied health departments are given in Box 5. This clinic structure was standardised for all hospitals. Group encounters were partitioned on the basis of hospital type and clinic type in the same manner as one-to-one encounters to facilitate standardised approaches to data collection and reporting. After trimming data to remove outliers, 0.5% of clinic encounters were group encounters. The average per patient cost of a "group encounter" was $82. This was about $20 less than one-to-one encounters. A list of group encounters and costs is given in Box 6. Emergency department analysis incorporating data from two previous studies (as mentioned above), and other studies conducted in Australia, have identified the key resource drivers in an emergency department as being triage, disposition and age.1 Classification analysis The objective was to design, from first principles, an outpatient classification system which could be used to fund ambulatory activity, and in doing so report on the appropriateness of the DACS as a framework for a patient-based classification system. A total of 198 495 episodes were analysed in detail, after removal of incomplete episodes. For selected components, data were trimmed to exclude cost outliers (defined as < 4 or > 5 SD from the mean); 1008 records were excluded on this basis. Analysis of emergency department data was conducted separately. The most significant variables identified were hospital type (teaching, specialist, metropolitan, large rural and small rural), outpatient clinic type, visit type (new or repeat), age and significant procedure. The impact of hospital type was highly significant and became the principal variable producing splits. An analysis of secondary variables producing splits is given in Box 7. Clinic-based classification Clinic type explained 24.05% of the cost variation in untrimmed data, and 31.60% of the cost variation in trimmed data. The variation explained was less significant for teaching hospitals (18.04% for untrimmed data and 23.93% for trimmed data). The variation in teaching hospital costs may have been a consequence of the higher number of junior staff who may have ordered additional diagnostic tests and the variable profile of clinicians attending the same patient. A detailed review was conducted of the variables associated at the next level of the classification tree, testing, in particular, age, visit type and the presence or absence of a significant procedure. This analysis did not produce splits which were consistent across all hospital strata. These factors were not considered to be significant splitting variables. To complete the classification analysis, it was necessary to examine group encounters and telephone contacts. Difficulty in defining telephone calls for funding purposes has resulted in telephone calls being excluded in many casemix-funding models. As the cost differential between face-to-face contacts and telephone contacts is so small, a case could be made for recommending funding these services in the same manner as face-to-face contacts. However, concerns were raised about the gaming potential for this class of encounters. Emergency department system When analysing emergency department episodes on the basis of urgency (as assessed by the National Triage Scale) and disposition, a significant explanation of variance was obtained. This remained at 34.39% for both trimmed and untrimmed data. Box 8 details the proportion and cost of encounters, by triage, disposition and age. The performance of this classification structure in small rural hospitals was extremely poor and produced a 0.93% reduction in variance. The flat average cost across the range of classes within this hospital stratum suggests that these services should be funded at a standard rate. DACS structure The assignment to DACS classes was based on the principal diagnosis coded, using ICD-9-CM codes. Problems occurred in the assignment of patients to DACS classes because there was no unique mapping of ICD-9 CM codes to AMDCs. For example "fracture of facial bones" could be assigned to AMDC 2, 3 or 8 (Eye; Ear, Nose, Mouth and Throat; and Musculoskeletal System and Connective Tissue, respectively). This was not addressed during the design phase of the project, and to resolve this an additional step was incorporated into the grouping process. This step used "clinic type" as a defining variable. This allowed 80% of all encounters to be assigned to a specific DACS class. It is not possible to determine whether the 20% of episodes excluded from the analysis had a significant impact on the result. The DACS explained only 15.32% of cost variation when stratified by hospital type. The performance of this classification system was marginally improved when a secondary split based on professional discipline (allied health, emergency, outpatient) was included (20.12%). Discussion It is imperative to establish a standard classification system for ambulatory patients, as has been done for acute patients. Healthcare funders and providers need to able to describe the ambulatory patient profile. Previous studies attempting to explain the resource variation for ambulatory patients have found that classifications based on the provider, rather than the patient, explain greater variation in patient costs. This is to be expected, as ambulatory care takes place in a relatively constrained environment. Clinicians designate "time slots" for their patients based on criteria relevant to their specialty areas. Patients may also be seen for the same condition by medical specialists and by allied health professionals -- the characteristics of the patient are unchanged, but the treatment regimens and resource use by the provider can vary greatly. Nevertheless, despite the difficulties entailed in development, a patient-based classification is considered the ideal long term classification structure for ambulatory encounters, as it would truly reflect the clinical condition of patients and thus enhance the clinical utility of such a system. The DACS, developed with input from experienced clinicians, was designed with this intent but, before this type of classification can be introduced, hospital outpatient information systems will have to be greatly enhanced. A complex patient-based classification requires the collection of patient activity and clinical data, which would exceed the capacity of existing manual or electronic systems. The study clearly indicates that the proposed DACS, in its current form, is not appropriate for classifying hospital based ambulatory services, and that in future classification development work the AMDC structure should not be considered an appropriate primary classification variable. More importantly the study identifies the generic clinic classification structure, partitioned by hospital type, as the most appropriate classification system for one-to-one encounters in outpatient clinics and allied health departments. Group encounters should also be classified by generic clinic type. Separate cost weights would apply to one-to-one and group encounters. The classification of emergency department presentations has been the subject of extensive research. This project confirms previous reports that triage category and patient disposition should be used to classify one-to-one encounters in emergency departments.9 In the short term, the generic clinic based structure for outpatients and allied health departments and the urgency and disposition based structure for emergency departments are recommended for classifying and funding ambulatory services in Australia. Acknowledgements This study was funded by the Commonwealth Department of Health and Family Services and sponsored by the Australian Casemix Clinical Committee, receiving constant support from all members and its then Chair, Professor John Hickie. We would like to acknowledge the cooperation of staff at the study hospitals. The burden placed on hospital staff in collecting detailed information on individual outpatient encounters cannot be underestimated and the commitment to "see the project through" was a major undertaking. We also acknowledge the assistance of State and Territory health departments, Malcolm Bond from Flinders University, Dr Chris Baggoley from Flinders Medical Centre and Coopers & Lybrand Consultants. This article is based on the Outpatient Costing and Classification Study undertaken by Coopers & Lybrand on behalf of the South Australian Health Commission and the Commonwealth Department of Health and Family Services, April, 1998. References Hindle D, Ligaida R. A casemix classification for hospital-based ambulatory services: a report from the National Ambulatory Casemix Project, New South Wales Department of Health. Sydney: New South Wales Department of Health, 1992. Michael R, Piper K, Heard P. Ambulatory Encounters Project, Flinders Medical Centre, Adelaide. Report for the Commonwealth Department of Health and Family Services, 1991 (available from the Department). Medicare agreement 1993-1998. Canberra: Commonwealth Department of Health and Family Services, 1993. Commonwealth Department of Health and Family Services, Classification and Payments Branch. Ambulatory casemix in Australia: Description of relevant classification systems. Canberra: Commonwealth Department of Health and Family Services, October 1995. Deloitte Touche Tohmatsu. DACS Pilot Study Progress Report. Report for the Commonwealth Department of Health and Family Services, Canberra. Sydney: Deloitte Touche Tohmatsu, 1997. Coopers & Lybrand Consultants. Outpatient Costing and Classification Study incorporating the Developmental Ambulatory Classification System Evaluation. Report for the Commonwealth Department of Health and Family Services, Canberra. Adelaide: Coopers & Lybrand Consultants, 1998. Jackson T, Sevil P, Tate R, Collard K. Development of relative resource weights for non-admitted patients. Melbourne: National Centre for Health Program Evaluation, 1989. Coopers & Lybrand Consultants. Queensland Health Ambulatory Project. Brisbane: Coopers & Lybrand Consultants, 1996. COSMOS [computer program], Version 2.0. Sydney: NSW Health. Erwich-Nijhout MA, Bond MJ, Baggoley C. Costings in the Emergency Department, Flinders Medical Centre, Adelaide. Report for the Commonwealth Department of Health and Family Services, 1996 (available from the Department). Erwich-Nijhout MA, Bond MJ, Raftos J. Costings in the Paediatric Emergency Department, Women's and Children's Hospital, Adelaide. Report for the Commonwealth Department of Health and Family Services, 1996 (available from the Department). Mental Health Classification and Service Costs Project. Developing a casemix classification for mental health services. Final report: Volumes 1 and 2. Canberra: Commonwealth Department of Health and Family Services, Aug 1998. Authors' details Princess Alexandra Hospital, Brisbane, QLD. Michael I Cleary, FACEM, MHA, Executive Director of Medical Services. Department of Health and Family Services, Canberra, ACT. Jo M Murray, BSc(Med), Acting Assistant Secretary, Classification and Payments Branch. Deloitte Touche Tohmatsu Consulting Group, Sydney, NSW. Robin Michael, BSc(Hons), MPH, Partner. South Australian Department of Human Services, Adelaide, SA. Kym Piper, MNIA, Principal Consultant, Health Costing and Evaluation Unit. Reprints will not be available from the authors. Correspondence: Dr M I Cleary, Executive Director of Medical Services, Princess Alexandra Hospital, Woolloongabba, QLD 4102. E-mail: clearymAThealth.qld.gov.au

Synopsis The introduction of casemix funding systems has focused attention on the reliability and validity of coded health data. Defining and classifying medical and health related terms are the core activities of the National Centre for Classification in Health (NCCH), which has recently published the Australian modification of the International statistical classification of diseases and health related problems, 10th revision (ICD-10-AM). An important feature is a classification of procedures (MBS-E) based on the Commonwealth Medical Benefits Schedule. Clinicians have made major contributions to the new classification through a network of 21 Clinical Coding and Classification Groups, which advise the NCCH. Major advantages of ICD-10-AM for clinicians include the ability to update the classification within Australia with continued clinical consultation, the familiarity of the procedure codes based on MBS, and the possibility of having one classification for use in public and private healthcare facilities. Introduction Codes for diseases and procedures are the basic ingredients of the casemix recipe. However, the coding function was not invented for casemix. The need to classify and measure has been around for centuries (Box 1). Allied to this need to impose order by classifying is the need to define the elements of a disease or procedure so that the meaning is clear and classification can take place. O'Rourke highlighted the importance of the meaning of medical terms in the context of doctor-patient communication in cardiology.3 Using codes to describe concepts is a shorthand way of ensuring a common understanding of the definition of that concept. The introduction of casemix funding systems based on the classification of diseases and procedures has meant that disciplined attention has been paid to the reliability and validity of coded health data. The connection between the codes and the health dollar has turned the spotlight on coding previously used only to identify groups of similar patients for research, utilisation studies or quality assurance. National Centre for Classification in Health The twin functions of defining and classifying medical and health related terms are the core activities of the National Centre for Classification in Health (NCCH), located at the University of Sydney, and Queensland University of Technology (Box 2). The Quality Division at La Trobe University, Melbourne, examines issues relating to coding and data quality. The NCCH develops codes and coding standards for use in Australian health services, publishes in hard copy and electronically, and educates clinical coders and clinicians in the application of codes. It also publishes methods of measuring coding quality and assists the Australian Institute of Health and Welfare in its role as WHO Collaborating Centre for Classification of Diseases. The Brisbane site supports the Australian Bureau of Statistics (ABS) in relation to its classification of causes of death. The ABS has been recording cause of death using the classification system International classification of diseases (ICD) and its predecessors since 1907 (Box 1). Australian hospitals and health services have collected ICD data on diagnoses and procedures since 1968. Before 1968, the Standard Nomenclature of Diseases and Operations,4 and sometimes the ICD, were used in hospitals to capture disease and procedure information, mainly for research purposes. The use of codes for casemix classification led to the need for Australian national standards in the application of codes, and eventually to the formation of specific Australian codes and classifications. These Australian Coding Standards have been developed by the NCCH.5 ICD-10-AM The NCCH has recently published the International statistical classification of diseases and related health problems, 10th revision, Australian modification (ICD-10-AM),5 which includes Australian extensions of the WHO codes in ICD-10 and some specific Australian disease codes. An important feature is the addition of a classification of procedures based on the Commonwealth Medicare Benefits Schedule (MBS) of fees for health services. It was a deliberate decision of the Casemix Implementation Project Board in 1995 to create this Australian procedure classification based on the fee schedule so that the classification of procedures in the public and private sectors, as well as in ambulatory situations, would be more consistent. The Australian procedure classification, known as the Medicare Benefits Schedule, Extended (MBS-E), is more specific than MBS, and is organised logically according to body system and site and includes a detailed index. Codes have been added for procedures not currently eligible for benefits, such as cosmetic surgery, obstetrics and allied health procedures. ICD-10-AM was introduced in July 1998 in hospitals and other healthcare agencies in New South Wales, the Australian Capital Territory, Victoria and the Northern Territory. It will be introduced in the remaining States from July 1999. The ABS, because of its commitment to report mortality data to the WHO, will continue to use the WHO version of the ICD classification. It is planned to implement ICD-10 for mortality coding in the year 1999 or 2000; the decision will depend on the availability of the Automated Cause of Death coding software from the United States. Casemix classification and mapping Construction of casemix classifications requires data expressed in the source coding systems. Because the national casemix classification system, AN-DRG, has until now been based on the previous standard classification in Australia, ICD-9-CM, the changeover to ICD-10-AM will require mapping between the classifications so that a version of AN-DRG based on ICD-10-AM can be built. Until data are available in ICD-10-AM from Australian hospitals and health services, AN-DRG allocation must rely on mappings between ICD-9-CM and ICD-10-AM. Mappings for grouping purposes are known as "logical" mappings, while those for longitudinal epidemiological studies are called "historical" mappings. The slight differences between these mappings arise because of differences in specificity of the classifications, especially in situations where one code in the new classification maps to many codes in the previous classification, and the many codes are spread over many DRGs (Box 3). Interaction between clinicians and clinical coders The need for accurate decisions on principal diagnosis and code allocation has led to collaboration between clinical coders and clinicians to interpret the documentation in the clinical record and to come to an agreed decision on appropriate codes for episodes of care. Clinicans have made major contributions to the structure and content of the new Australian disease and procedure classifications through a network of 21 Clinical Coding and Classification Groups (CCCG), which advise both the NCCH and the Australian Casemix Clinical Committee (ACCC) on issues relating to coding and casemix refinement. Many additions to the WHO ICD-10 were made as a result of mapping between ICD-9-CM and ICD-10 to ensure that specificity and new Australian codes introduced to ICD-9-CM were replicated in ICD-10-AM. Examples of notable improvements in ICD-10-AM compared with ICD-9-CM are listed in Box 4. To promote clinician-coder communication, the NCCH has been funded by the ACCC to publish a series of specialty booklets on coding and casemix. A series of 21 booklets on different clinical topics is planned, of which a third is already available. Detailed information of interest to clinicians and epidemiologists about changes in ICD-10-AM is currently being prepared by the NCCH and will be available on the NCCH internet homepage.6 The NCCH also has an education function in keeping clinical coders abreast of annual updates to the coding system and the Australian Coding Standards.5 It will play a major role in educating clinical coders in ICD-10-AM. The NCCH's homepage6 is regularly updated and has links to relevant Australian and overseas organisations. Impact of ICD-10-AM Clinicians: Australian clinicians will benefit greatly from the new Australian classification. Firstly, it makes current the description and classification of diseases, and reinforces the Australian clinical contribution to updating the underlying WHO classification. The mechanism of clinical consultation used in constructing the classification will be continued in the updating process so that the classification remains clinically coherent and relevant. Secondly, by using the Medicare Benefits Schedule as the foundation of the procedure classification, the concepts and labels of the procedure codes will be familiar to clinicians, and the update of MBS-E will proceed in tandem with the update of MBS. Having one Australian procedure classification for use in public and private healthcare facilities, inpatient and ambulatory situations will be more efficient than the existing system (ICD-9-CM in the public sector and MBS in the private sector) and will do away with the need for mapping between MBS and ICD. Clinical coder workforce: Introduction of the new classification will have major implications for the clinical coder workforce. They will not only need to become familiar with ICD-10-AM coding, but will also need an understanding of anatomy and the surgical procedures required by the specificity of the MBS-E. ICD-10-AM coding is expected to take longer initially,7 although no allowances have been made in the deadlines for reporting hospital morbidity data in the States and Territories adopting the new classification in 1998. Health facility managers are becoming more aware of the need for resources for clinical coders to reflect the complexity of casemix through accurate and timely clinical coding. Updating the classification: A major benefit is the ability to regularly update the classification within Australia. We intend to maintain close connections with international disease classification systems so that statistics on causes of death and morbidity are comparable. However, having an Australian centre for health classification develops local expertise and fosters robustness of the Australian classification itself, data quality and efficiency of data collection, as well as a clearer understanding of the meaning of clinical terms and their place in classification hierarchies. Synchronising coding systems: Introduction of ICD-10-AM also provides an opportunity for synchronising coding systems with software designed to support electronic patient records. Without appropriate coding standards, data from these systems cannot be extracted, analysed and stored so that it is retrievable and capable of integration with other related modules and functions (eg, pharmacy and laboratory data). Modifications to health service software systems will be required to accommodate the new composition of the codes. The ICD-10-AM disease codes are alpha-numeric (3-5 characters; eg, Ross River disease [B33.1]) and the procedure codes are numeric (7 characters; eg, endoluminal repair of aneurysm [90228-00]). Analysis of longitudinal data: The change in classifications will affect analysis of longitudinal data by epidemiologists and public health practitioners. They will have the option of mapping forwards from the old to the new classification, or backwards from the new to the old classification. In either case, meaning will be lost when the codes of one classification are more precise or less precise than those of the other. However, there will be benefits in the introduction of appropriate new codes and terminology, particularly for infectious diseases, neoplasms, obstetrics and mental health. Conclusion Considerable effort has always been devoted to coding diseases and procedures in hospitals. Casemix funding systems with their reliance on accurate classification of diseases and procedures provide a major incentive to getting the data right. Systems are in place through the ICD-10-AM codes, the Australian Coding Standards, the clinical coder workforce, and through input from clinicians to ensure that coding is clinically appropriate, efficient, accurate and timely. References Lyons AS, Petrucelli RJ. Medicine: An illustrated history. New York: Harry N Abrams, 1987. History of the development of the ICD. In: World Health Organization. International statistical classification of diseases and related health problems. 10th revision. Vol 2, Ch 6. Geneva: WHO, 1993. O'Rourke MF. What's in a name? Med J Aust 1997; 166: 372-373. Thompson ET, Hayden AC. Standard nomenclature of diseases and operations. 5th ed. New York: McGraw-Hill, American Medical Association; 1961. National Centre for Classification in Health. The international statistical classification of diseases and related health problems, 10th revision, Australian modification (ICD-10-AM). Sydney: National Centre for Classification in Health, Faculty of Health Sciences, University of Sydney, 1998. National Centre for Classification in Health. World Wide Web homepage: http://www.cchs.usyd.edu.au/NCCH/ncch.html Department of Health and Family Services. ICD-10-AM impact assessment project. Final report. Adelaide: Coopers & Lybrand Consultants, November 1997: 30. Authors' details National Centre for Classification in Health, University of Sydney, Sydney, NSW; and Queensland University of Technology, Brisbane, QLD. Rosemary F Roberts, MPH, MBA, Director, National Centre for Classification in Health, Sydney. Kerry C Innes, AssocDip(MRA), Associate Director, National Centre for Classification in Health, Sydney. Susan M Walker, BAppSc(MRA), Associate Director, National Centre for Classification in Health, Brisbane. Reprints will not be available from the authors. Correspondence: Associate Professor R F Roberts, National Centre for Classification in Health, University of Sydney, PO Box 170, Lidcombe, NSW 1825. E-mail: R. RobertsATcchs.usyd.edu.au

Synopsis Paediatric patients (compared with adults) require additional time, effort and skill from hospital staff caring for them. Many suggestions for making successive versions of AN-DRGs more child friendly have not been implemented. Rather than relying on age, the AN-DRG classification should allow a better definition of complexity within DRGs. The two groups of children who place a disproportionate burden on paediatric teaching centres are children under 3 years and those with congenital abnormalities and chronic illness. Cost weights are not specific for paediatric patients. The extra costs of caring for children are reflected in nursing costs, highlighting the importance of including nurse dependency data in any costing study. Introduction In recent years attention has been drawn to the differing healthcare needs of children compared with adults, and the high cost of caring for children in hospital.1-6 Children's less-frequent use of inpatient services reflects in part their general well-being, but also a different approach to their care, with every effort being made to keep them out of hospital or to minimise their length of stay. However, children's shorter stay is counterbalanced by their greater dependence, and the intensity of the care they require increases the cost of their hospital stay. A briefing paper prepared by the National Association of Children's Hospitals and Related Institutions (NACHRI) in the United States clearly outlined the uniqueness of children's healthcare services.1 Their findings -- that children are more likely to require acute care than long term care, but when they do have a chronic illness the costs of care are high -- apply also to other developed countries, including Australia. Classification issues -- making DRGs child friendly Studies in the United States have shown inadequacies in many of the classifications describing paediatric care and also found costs to be higher for paediatric patients, in particular for nursing care.7 However, the APR-DRG (all patient refined DRG) classification, widely adopted in the United States, better reflects paediatric care and illness severity than previous casemix classifications. Similarly, studies in Australia have highlighted the inadequacy of the AN-DRG classification.8 Despite the many changes that have been made to AN-DRGs since they were introduced, they are still not seen as ideal for paediatrics. Age splits and comorbidities AN-DRG versions 1 and 2 had a number of adjacent DRGs with an age split at 10 years. These were eliminated from version 3 because they were not supported by length of stay and nurse dependency data. However, in 1996, the Australian Casemix Classification Committee recommended that, for those DRGs with age splits at 10 years, the complications and comorbidities split should take precedence over the age split, so that hospitals caring for a small number of children with complex illnesses would not be disadvantaged. However, because so few children were involved, this was not implemented and remains a major problem for these hospitals. General anaesthesia in children AN-DRGs do not recognise the need for a general anaesthetic for children having procedures (eg, a dental procedure, an endoscopy or a minor orthopaedic procedure) for which adults do not normally require anaesthesia. Many of these procedures are in a "medical" DRG rather than a "procedural" DRG, resulting in an inadequate cost weight for the care provided to the child. Some allowance has been made for this in AR-DRG-4 (Australian refined diagnosis-related groups), which was released in July this year. A general anaesthetic is recognised as a complication in some DRGs, but this is dependent upon there being a split for complications in the particular adjacent DRG. Children under three years High nursing dependency An Australian study in 1996, using paediatric nursing service weights, showed that children under 3 years require significantly more nursing care than older children.6 In specialist teaching centres, children under 3 years required 37% more nursing time per episode of care than patients aged 3-59 years, and despite their shorter length of stay their use of nursing resources was similar to that of elderly people (Box 1).6 Data from this study also suggest that children under 3 years place higher demands on other hospital services irrespective of their length of stay. For children under 3 years versus those over 3 years, 29 AN-DRGs were identified with a cost variation of greater than 50% and 15 with a cost variation of 25%-49%.6 On the basis of these findings and with the restriction that there were to be 10 more DRGs, recommendations were made for future revisions of AN-DRGs: Additional DRGs should be included to cover the high cost of care of younger patients; The DRG age split at 10 years should be adjusted to an age split at 3 years; and If possible, paediatric patients should be shifted from their current DRGs to the adjacent higher-order DRG, if an age split for older patients already existed. Most of these recommendations were rejected on statistical grounds. A limited number of DRGs with age splits were adjusted to 3 years, but others were removed and replaced with splits based on comorbidities and complications. In the long term, replacement of age splits by splits based on severity of illness is preferred. In AR-DRG-4 the problem of complications and comorbidities is better addressed, but further changes still need to be made (Box 2). Cost weights Currently, the cost weights applied to paediatric patients in many States and Territories in Australia are the same as those applied to all other categories of patients. National DRG cost weights have until now been derived by a cost modelling method which allocates costs to DRGs rather than to individual patients (see Phelan). Consequently, it is not possible to compare the costs of caring for children under 3 years derived from actual resource allocation. However, nursing costs are a good proxy for the increased care these patients require. The "average total nursing time per DRG" is the largest component (about 44%) of the total costs per DRG. It is also the most appropriate and available indicator for comparing costs of caring for children under 3 years with those in other age groups. Nursing costs enable a valid comparison of costs across all Australian States and Territories, irrespective of nursing career structures and award rates of pay.9 On average, nursing costs, regardless of the length of stay, are doubled in young children under 3 years -- they account for almost 40% of the throughput of paediatric hospitals. As nursing salaries represent about 35% of all hospital costs and more than 50% of variable costs, this issue needs to be addressed within the payment system.6,9 Several authors have emphasised the higher costs of teaching hospitals (see Butt and Shann; Hart and Wallace; Phillips). Within paediatrics, however, it is difficult to distinguish between the casemix of specialist and non-specialist teaching centres. Because the AN-DRG classification (both versions 3 and 4) is limited in its capacity to take into account complications and comorbidities, it cannot adequately reflect these differences. In attempting to deal with this inequity, paediatric hospitals in Victoria have lobbied individually to have modifications made to their own hospital's reimbursement to reflect the greater cost of providing care for children. South Australia has adopted a standardised approach to developing paediatric cost weights based on benchmark costs. This method entails replacing the cost components for nursing, medical and allied health in the national cost weights with benchmark paediatric costs for South Australia. Paediatric cost weights are derived from these data. Currently, a second national cost weight study is in progress. Data from patient costing systems are being used to update the paediatric cost weights to ensure they are improved for paediatrics. A study into the neonatal services provided by the two intensive care units in South Australia is also in progress. Congenital abnormalities and chronic illness Advances in technology have significantly improved clinical outcomes for a wide variety of paediatric patients. A relatively small group of children with chronic or congenital illness, including newborns requiring neonatal intensive care, accounts for a significant proportion of the cost of acute inpatient care. Many of these children require ongoing care and rehabilitation, which is both resource intensive and often delivered in an acute care setting. This adds considerably to the number of children requiring lengthy hospital admissions ("long stay outliers") and the overall cost of care. In Australia, there are limited facilities for providing ongoing care for these children outside acute-care institutions. Experience in Victoria has highlighted the complexity of children requiring lengthy hospital admissions. A study by Health Solutions5 pointed out that most of these children are erroneously judged to be nursing home type patients. They do not necessarily cost the same as children with shorter stays ("inliers") during the same phase of care, nor do they necessarily cost less than the average cost per day for shorter stay children when their stay continues past the "high trim point". Other specialist paediatric hospitals in Australia and the United States have reported similar problems.7,10 There is substantial underfunding of children who require lengthy admissions, particularly in the areas of neonatology, oncology, and chronic or congenital diseases. The high cost of paediatric care has resulted in health funds in the United States being reluctant to fund paediatric hospitals with patients likely to require long and complex care.10 This situation could easily arise in Australia. Careful case selection by payers or providers in a competitive market can be used to advantage in better risk management within a health plan. Potentially, this can lead to preference being given to children with less-complex conditions, and barriers to access for children requiring longer and more intensive care. With recognition that a relatively small proportion of high cost paediatric patients accounts for almost two-thirds of the expenditure on acute-care paediatric services, it is time for funders to specifically target these children for separate funding so that specialist paediatric hospitals can be more equitably funded. Future strategies Having recognised the different care requirements of children, the issue now is how to have them accepted by the wider health community. The strategies that need to be pursued are clear: The classification should recognise severity rather than rely on age as a proxy; The true costs of paediatric care must be reflected in the cost weights; and Strategies should be implemented to deal with the select group of high cost patients who pose a unique problem to specialist teaching centres. US experience has shown that dealing with these factors alone can decrease the financial losses of children's hospitals from 30% to about 10%.7 AR-DRG-4 allows for better definition of complexity within DRGs. However, the APR-DRGs advocated by NACHRI provide the extensive benefits of a more universal application of grades of severity. References National Association of Children's Hospitals and Related Institutions. Children's health care needs are different - why one size won't fit all. A NACHRI briefing paper. Alexandria, Va: NACHRI, 1993: 1-16. Vertrees JC, Pollatsek JS. Paying for paediatric inpatient care. Final report of the Universal Access for Children Reimbursement Study Project. Conducted for NACHRI. Alexandria, Va: Solon Consulting Group Ltd, 1993. Berry R. Final report of Children's Hospitals' Casemix Classification Study Project. Conducted for NACHRI. Alexandria, Va: NACHRI, 1986. Miller H. Final report of Paediatric Costing Study. Conducted for NACHRI. Alexandria, Va: Center for Health Policy Studies, 1993. Paediatric Costing Study. Kids casemix - more swings than roundabouts. Melbourne: Health Solutions Pty Ltd, 1994. National Paediatric Nursing Study Phase 2. Adelaide: Paediatric Nursing Study Consortium, 1996: 1-19. Muldoon J. Paediatrics and DRG casemix classification. In: Goldfield N, Boland P, editors. Physician profiling and risk adjustment. Chapter 24. Gaithersburg, Md: Aspen Publishers, 1996: 252-270. Phelan PD. Are casemix developments meeting the needs of paediatrics? Med J Aust 1994; 161 Suppl Sep 5: S26-S29. National Paediatric Nursing Study Phase 1. Adelaide: Paediatric Nursing Study Consortium, 1994: 1-13. Andrews JS, Anderson GF, Han C, Neff JM. Pediatric carve outs. The use of disease-specific conditions as risk adjusters in capitated payment systems. Arch Pediatr Adolesc Med 1997; 151: 236-242. Authors' details New Children's Hospital, Sydney, NSW. Ralph M Hanson, FRACP, FACEM, Chair, Division of Information Services. Women's and Children's Hospital, Adelaide, SA. Meradith A Phythian, RN, RM, Clinical Analyst, Clinical Support Unit. Jenni B Jarvis, RN, Head, Clinical Support Unit. Princess Margaret Hospital, Perth, WA. Cyndy Stewart, RN, BAppSc, Head, Best Practice Unit. Reprints will not be available from the authors. Correspondence: Dr R M Hanson, New Children's Hospital, PO Box 3515, Parramatta, NSW 2124. E-mail: RalphHATnch.edu.au

Synopsis AN-DRGs have some splits which take illness severity and complexity into account. Age is also often used as a proxy for severity of illness. The need to transfer a patient may be a marker of illness severity or complexity and therefore resource utilisation. This is supported by studies of patients transferred to intensive care units. Data on the costs and outcomes of all transferred patients should be collected; depending on the results, refinements of DRGs may be indicated. Introduction Greater accuracy of DRG classification would result in more appropriate healthcare funding. A limited number of complications and comorbidity splits in AN-DRGs take into account illness severity and complexity. In addition, age, in both young and old patients, is often used as a proxy for illness severity. DRG accuracy could be further improved, if other easily applied measures of illness severity could be identified. Patients transferred from one hospital to another because they require specialised treatment may represent a different patient population to those not transferred. A recent study has shown the differential resource utilisation of different populations, with hospital care for Aboriginal and Torres Strait Islander patients estimated to cost 30% more than that for non-Aboriginal and Torres Strait Islander patients with a similar DRG classification1 (see Fisher et al). It is possible that hospital care for transferred patients may also be more costly, because being transferred may be a marker for illness severity or complexity and therefore resource utilisation. Summaries of studies of comparative costs of transferred and non-transferred patients are shown in the Box. The studies indicate that transferred patients generally are sicker, use more resources, have a longer length of hospital stay and an increased risk of death. Costs may be higher, particularly if death occurs after a long illness. Most of the currently available data relate to patients transferred to intensive care units. Definitions of transfer status To apply a patient's transfer status as a measure of severity, definitions need to be standardised. We propose the following categories: Referral: Transfer of a patient to a different hospital for a particular doctor's opinion. Up transfer: Transfer of a patient to another hospital for inpatient specialist treatment not available at the primary hospital. Down transfer: Either return transfer of an inpatient to the primary hospital, or transfer of a patient to another hospital for recovery. Sideways transfer: Transfer of a patient to another hospital, because the required facilities at the referring hospital are fully occupied. Further Australian data will need to be collected prospectively on the costs and outcomes of patients who are transferred from one hospital to another for specific, complex treatment. In the light of these results, further analysis of transfer status will be needed, before it can be applied as a measure of illness severity and resource utilisation. Depending on these results, refinements of DRGs may then be indicated. References Commonwealth Department of Health and Family Services. Report on National Aboriginal and Torres Strait Islander Casemix Study. Adelaide: Brewerton and Associates Pty Ltd, April 1997. Munoz E, Soldano R, Gross H, et al. Diagnosis related groups and the transfer of general surgical patients between hospitals. Arch Surg 1998; 123: 68-72. Jencks SF, Bobula JD. Does receiving referral and transfer patients make hospitals expensive? Med Care 1988; 26: 948-958. Pon S, Notterman DA, Kathryn M. Pediatric critical care and hospital costs under reimbursement by diagnosis-related group: effect of clinical and demographic characteristics. J Pediatr 1993; 123: 355-364. Borlase BC, Baxter JK, Kenny PR, et al. Elective intrahospital admissions versus acute interhospital transfers to a surgical intensive care unit: cost and outcome prediction. J Trauma 1991; 31: 915-918. Authors' details Intensive Care Unit, Royal Children's Hospital, Melbourne, VIC. Warwick W Butt, MD, FRACP, Staff Specialist in Intensive Care. Frank A Shann, MD, FRACP, Director of Intensive Care; and Professor of Critical Care Medicine, University of Melbourne, Melbourne. Reprints will not be available from the authors. Correspondence: Dr W Butt, Intensive Care Unit, Royal Children's Hospital, Flemington Parade, Parkville, VIC 3052. E-mail: buttwATcryptic.rch.unimelb.edu.au

Synopsis An Australia-wide patient classification system for nursing is urgently needed as the health system attempts to develop benchmarks against which to measure and compare services. Standardised measures of demand for nursing care must be developed to allow appropriate reimbursement and to act as proxies for illness severity. Nurses need to identify the outcomes that measure the nursing contribution to episodes of care, and assist in developing outcome goals reflecting the efficacy of treatment and the quality of care. A system of measuring nursing requirements and costs of early discharge and coordinated care programs is required. It must be consistent with nursing classifications and hospital costing systems. Introduction Casemix continues to present challenges to the nursing profession. Initially, the focus was on refining the Australian AN-DRG classification to more accurately reflect clinical practice and, although anomalies still exist, this has largely been accomplished. Currently, four issues pose a particular challenge to nursing and relate to integrating the AN-DRG classification with: An Australian patient classification system for nursing; Measures of illness severity within DRGs; Measures of the nursing contribution to quality and outcomes; and, Measures of nursing requirements and costs of home-based and coordinated care programs. A patient classification system for nursing Because patients within a DRG are not necessarily alike in terms of cost and nursing dependency, there is a need for a patient classification system for nursing.1 This has become more urgent as the healthcare system attempts to develop benchmarks against which to measure and compare services. At present, each State and Territory has a very different system of patient classification for nursing acuity, which means that nursing content, reliability, validity and clinical meaning within AN-DRGs cannot be compared across Australia. There have been problems reaching a consensus on nursing classification issues. If nursing does not understand (and agree on) its own cost structure, or its contribution to the costs of patient care, it cannot hope to negotiate prices for the nursing component of an episode of care.2 A comparison of three nursing classification systems used in New York State found that estimates of nursing costs and nursing intensity (resource requirement and complexity of nursing care) varied because each system measured resource use differently.3 In South Australia, information is now available on nursing hours per patient-day and costs per patient-day. In 1995, a computer-based clinical decision-making program was successfully integrated with a computer-based nurse scheduling program. This system has been used in the major metropolitan hospitals and in a small number of larger country hospitals. Data collected can be aggregated to AN-DRGs and nursing costs compared across South Australian hospitals. Information from this system was used in the initial nurse costing study to develop the first nursing service weights incorporated into AN-DRGs. This system lends itself to continual refinement and innovation. Consensus about Australian nursing costs and what constitutes nursing in Australia cannot be reached, and benchmarks cannot be developed, until the nursing profession develops a patient classification system for nursing which applies to the whole of Australia. Illness severity measures The second issue challenging nursing -- measurement of illness severity in terms of nursing dependency -- is directly related to patient classification. Resource use within DRGs varies, as many AN-DRGs are far from homogeneous. Studies have shown that resource use within DRGs can be influenced by a range of factors including illness severity, disease complexity and comorbidities, as well as the socioeconomic profile of the patient.4-7 The South Australian Department of Human Services deals with the issue of case complexity and severity by giving its metropolitan teaching hospitals and regional country hospitals a severity loading. This severity index is calculated on the basis of the number of diagnosis and procedure codes per patient record by AN-DRG, and takes into account length of stay factors and variations in patient acuity and complexity.8 Variables of illness severity have been considered in AN-DRG-3. These include age, specific complications and comorbidities, level of effect of complications and comorbidities, complicating effects of interactions between groups of complications and comorbidities, direct clinical and physiological observations, need for life-support or therapeutic interventions, and admission status.9 AN-DRG-3 addresses some illness severity issues by the inclusion of splits based on three complicating clinical factors (CCFs): complication and comorbidity levels, age, and the presence of malignancy. Studies of illness severity and nursing have concentrated on developing standardised measures of demand for nursing care to allow appropriate reimbursement and to more accurately reflect nursing acuity. A study of the relationship between nursing care hours to DRGs and illness severity found that the demand for nursing resources was associated with illness severity, and that classification of patients by DRG and illness severity produced more homogeneous groups in terms of nursing resources.10 As nursing constitutes such a large proportion of the total expenditure for an episode of care, several tools have been developed to measure the impact of illness severity on nursing care. These include the Patient Intensity for Nursing Index (PINI), Nursing Intensity Weights (NIWs) and Case Mix Index (CMI), which are used across a range of medical and surgical DRGs in the United States, and the Apache (acute physiology and chronic health evaluation) system used in critical care in Australia.2,3,11-13 Because these severity of illness measures do not account for some of the variance in length of hospital stay and costs not explained by DRGs, alternative adjustments have been considered, including functional status indexes (particularly those measuring degree of independence in activities of daily living).14 An accurate method of measuring illness severity within AN-DRGs is yet to be developed. Thus, further work is required to identify whether nursing acuity or therapeutic nursing interventions can be used as surrogate indicators of illness severity. This may be the challenge for casemix and nursing in the future. Quality and outcomes The third challenge for nurses -- quality and the establishment of professionally agreed-upon clinical outcomes -- also presents a challenge to other health professionals. Casemix was originally intended to provide a method of more accurately defining and measuring outcomes within homogeneous groups. DRGs have enhanced the ability to map an episode of care for a group of patients, resulting in a proliferation of clinical pathways or care maps. Nurses have been key players in the development and implementation of these tools.15 Clinical pathways or care maps have been effective in streamlining care and in resource utilisation, and they have improved hospital processes and reduced lengths of stay.16 However, most clinical pathways or care maps fall short in defining and measuring outcomes of episodes of care within an AN-DRG. The same applies to guidelines and clinical protocols. The challenge for nurses is to identify the outcomes that measure the contribution that nursing makes to the episode of care. They need to work with the multidisciplinary team to develop measurable and realistic outcome goals that reflect the efficacy of treatment and the quality of the care given within DRGs. Nurses need to be able to demonstrate the impact of their care on the cost and length of stay of each DRG in order to maintain adequate funding for the nursing component of a DRG. Impact on clinical practice The final issue relates to changes in clinical practice and adapting AN-DRGs, nursing resources and nursing classifications to these changes. Early discharge programs and coordinated care programs for chronically ill people encourage management in the community rather than hospital admission. Casemix funding systems in some States have acted as a disincentive to these hospital-in-the-home initiatives, when DRG funding has been allocated only for hospital stay. A more creative way of determining what constitutes a "hospital bed" needs to be considered, to ensure that these programs are adequately funded. Outcome measures must be developed to determine whether these community-based programs are effective and whether they are accurately costed. In many cases, the nurses who manage hospital-in-the-home patients take on a range of roles, including education of carers, counselling and social work activities. In view of these additional roles, a system of measuring the nursing requirements and costs of home care needs to be considered. This should be compatible with hospital nursing classification and costing systems to enable accurate tracking of costs, outcomes and acuity across a full episode of care within a DRG. References Diers D. Whoa!!. Aust Nurses J 1991; June 20(10): 8-9. Ballard KA, Gray RF, Knauf RA, Uppal P. Measuring variations in nursing care per DRG. Nurs Manage 1993; 24(4): 33-41. Phillips CY, Castorr A, Prescott PA, Soeken K. Nursing intensity: going beyond patient classification. J Nurs Adm 1992; 22: 46-52. The Severity Measurement Protocol. Report to the Clinical Advisory Committee, South Australian Health Commission, 1994. Sharkey PD, Horn SD, Brigham PA. Classifying patients with burns for hospital reimbursement: diagnosis-related groups and modifications for severity. J Burn Care Rehabil 1991; 12: 319-329. Horn SD, Sharkey PD, Buckle JM, Backhofen JE, et al. The relationship between severity of illness and hospital length of stay and mortality. Med Care 1991; 29: 210-220. Rapoport J, Teres D, Lemeshow S, Avrunin JS, et al. Explaining variability of cost using a severity-of-illness measure for ICU patients. Med Care 1990; 28: 338-348. South Australian Health Commission. Severity and cost differentiation. Discussion Paper. Adelaide: SA Health Commission, 1998. Marshall R, Zhang X, Lonergan J. Measures of disease severity in the AN-DRG classification: the case for CC severity level indicators. Proceedings of the Seventh Casemix Conference in Australia; 1995; Jul 31-Aug 2; Adelaide. Canberra: Commonwealth Department of Human Services and Health, 1995. Bostrom J, Mitchell M. Relationship of direct nursing care hours to DRG and severity of illness. Nurs Econom 1991; 9: 105-110. Prescott P. Nursing intensity: needed today for more than staffing. Nurs Econom 1991; 9: 409-414. Adams T. Case Mix Index: nursing's new management tool. Nurs Manage 1996; 27(9): 31. McKinley S. Casemix update: Australian critical care costs and service weights. Part 2. Aust Crit Care 1996; 9(2): 56-59. Kelleher C. Validated indexes: key to nursing acuity standardization. Nurs Econom 1992; 10: 36. Zander K. Physicians, care maps and collaboration. The new definition. Boston, Mass: Centre for Case Management, 1992; 7(1): 2-4. Ferguson L. Casemix issues for nursing. Med J Aust 1994; 161 Suppl Sep 5: S37-S39. Authors' details Royal Adelaide Hospital, Adelaide, SA. Lesley E Long, RGN, BAppSci(Nsg), PhD, MHA Nursing Director, Cancer Centre. Rosemary Mann, RGN, BA, GradDipOrthoNsg, Project Nurse, Nursing Administration. Reprints will not be available from the authors. Correspondence: Dr L E Long, Nursing Administration, Royal Adelaide Hospital, North Terrace, Adelaide, SA 5000. E-mail: llongATcancer.rah.sa.gov.au

Synopsis Casemix has given allied health professionals the opportunity to review their approaches to patient care, contribute to reducing inpatient costs and improve quality of care. The National Allied Health Casemix Committee was formed in 1993 to advance allied health participation in casemix. The Committee has taken the first step in establishing cost weights for allied health through the Australian Allied Health Activity Classification, which defines allied health inputs in terms of clinical care, clinical service management, teaching and training, and research. Work is being done on generic classification of allied health inputs, and studies are examining what allied health activities are accounted for by DRGs and ICD-9-CM. Allied health has taken up the challenge of casemix, but better access to information technology will enhance its continued contribution. Introduction The advent of casemix in Australia has provided allied health practitioners and managers with an opportunity to review their approaches to patient care, contribute to organisational goals of reducing inpatient costs, maximise reimbursement within funding rules, and improve the quality of patient care. Significant achievements have been made at local, State and national levels, despite deficiencies in both the systems and the technology supporting casemix implementation. National Allied Health Casemix Committee (NAHCC) The NAHCC was formed in 1993 to advance allied health participation in casemix. There are 14 professional member organisations of the NAHCC. Allied health casemix groups in all States and Territories are also represented. NAHCC has successfully completed major projects by focusing on areas of commonality, rather than difference. This has also occurred at the State level; for example, in South Australia cooperation between allied health, the South Australian Health Commission and information services staff led to agreement on the requirements for an allied health information management system. The Reference Standards Project1 undertaken by the NAHCC is the first step in developing Australian cost weights for allied health. The lack of appropriate infrastructure, including an agreement on what constitutes inputs and outputs of allied health services, has so far precluded their development. The allied health weights applied in AN-DRGs are a version of the Maryland weights (Maryland [USA] Health Services Cost Review Commission, 1993) crudely modified for Australian use and not reflecting Australian allied health practice. Australian Allied Health Activity Classification2 The Australian Allied Health Activity Classification was an important outcome of the Reference Standards Project. The classification broadly defines inputs in terms of clinical care, clinical services management, teaching and training, and research. More specifically, clinical care is defined as all activities which can be attributed to an individual patient, group or community, thus eliminating the inappropriate notions of "direct" and "indirect" care. This approach was taken up by other classification studies, including the Sub-Acute and Non-Acute Patient Casemix Classification Study. The Reference Standards Project identified that occasions of service alone are not a satisfactory method of measuring outputs of allied health, and that further work in this area needs to be done. Allied health procedure codes In consultation with individual professional bodies and the NAHCC, the National Coding Centre (now the National Centre for Classification in Health [NCCH]) has identified discipline-specific interventions. The previous description of interventions within the ICD-9-CM procedures listing was extremely limited. Several disciplines submitted intervention codes and these were included in the July 1996 revision of ICD-9-CM. These codes have been refined and others added to the procedure listing in the recently developed Australian modification of ICD-10 (ICD-10-AM) (see Roberts et al). Future revision of the codes by the professions and the NCCH will ensure their adequacy in describing allied health inputs and their consistency in cross- discipline application. Coding challenges Projects by various allied health disciplines examining the extent to which their activities are accounted for by DRGs and the ICD-9-CM classification have shown considerable lack of agreement between classifications. A study of the intensity of social-work time in an acute hospital3 found it to be more related to a patient's presenting psychosocial problems, but that these were influenced by diagnosis and complexity. A study for the Dietitians Association of Australia found that most, but not all, of the diagnostic terms used by dietitians in describing patient care matched with terms in ICD-9-CM.4 Items which could not be matched related to risk of malnutrition, risk of side effects of treatment or disease, or lack of diagnostic specificity of a particular disease. This study also established that dietitians, like many allied health practitioners, may see patients for reasons other than the principal reason for admission. Despite limitations of existing casemix classifications to take allied health inputs into account, clear examples exist of allied health's contribution to casemix-funded organisations. In strategically managing occupational therapy services, an approach integrating DRGs with cost-benefit analysis was successful in decreasing average length of stay and improving quality of care.5 Community-based services developed by a rehabilitation team resulted in earlier discharge, improved continuity of care and a high level of patient satisfaction.6 Unfortunately, this service was not continued past the initial funding period, because hospital reimbursement would have been reduced if the alternative outpatient service continued. By contrast, dietitians7 have shown that coding malnutrition as a comorbidity can alter DRG assignment and increase casemix reimbursement. More importantly, diagnosing malnutrition provides an opportunity to give appropriate and timely care, thus reducing the associated costs and length of stay.8 Benchmarking Emphasis is often placed on the use of casemix as a budgeting tool, which overlooks its original use for measuring quality of clinical care.9 Casemix allows clinicians to compare inputs and outputs and measure outcomes in terms of quality, value and resource utilisation. A step towards this was the Best Practice in the Health Sector Program10 to promote international best practice standards of care and workplace organisation throughout the health sector. The program case studies provide an overview of the factors influencing the growth of allied health in Australia, in the context of principles of best practice. In 1997, the Central Sydney Area Health Service established the National Allied Health Benchmarking Consortium. Its task was to identify methods of best practice by comparing allied health resource utilisation. The Consortium currently comprises seven teaching hospitals (three in New South Wales, and one each in Victoria, the Australian Capital Territory, Tasmania and South Australia). The objectives are to establish benchmarks of allied health resources at a national level, and to develop a framework to link benchmarks with inputs, processes and outcomes of allied health services and activities. In Phase I, baseline data were collected and are currently being analysed. Phase II, which will be conducted in close association with the NAHCC, will investigate the highest volume AN-DRGs with allied health inputs and selected outcomes. Future directions Allied health has taken up the challenge of casemix, but better access to information technology will enhance its continued contribution. Many allied health departments still rely on manual data collection to guide decision making. Access to hardware must be extended, and allied health information management systems interfacing with hospital decision support systems must be developed. Moreover, consistent application of classifications, such as the Australian Allied Health Activity Classification, will improve understanding of allied health inputs at the local, State and Territory, and national level. This will provide a platform for costing of allied health, and for developing allied health service weights. In addition, improved information systems will also support the allied health service structures that best manage human resources, meet the needs of smaller referring clinical units, maintain an appropriate skill mix of practitioners, and support training of undergraduates. Interest in casemix among allied health practitioners has been steadily growing. The development of new classifications, such as the Australian National Sub-Acute Non-Acute Patient (AN-SNAP) Casemix Classification (see Lee et al) and the Mental Health Classification and Service Costs (MH-CASC), have further involved allied health professionals working in rehabilitation, mental health and other settings outside acute care. Moreover, community practitioners are becoming casemix-aware with the development of the Community Health Information Management Enterprise (CHIME), which is responsible for the National Codeset Project for community-based health services. References The National Allied Health Casemix Committee. Report to the Commonwealth Department of Health and Family Services on the development of National Reference Standards for allied health disciplines -- clinical terms and minimum data set. Melbourne: The National Allied Health Casemix Committee, 1997. Australian Allied Health Classification System: Version 1. Melbourne: The National Allied Health Casemix Committee, 1997. Badger J, Cleak H, Haywood M. Factors affecting the intensity of social work time in an acute hospital. Allied health and casemix: towards 2000. Melbourne: The National Allied Health Casemix Committee, 1996; 23-27. Barrington V. The development and classification of dietetic diagnoses and interventions. Allied health and casemix: towards 2000. Melbourne: The National Allied Health Casemix Committee, 1996: 20-22. Brandis S. An AN-DRG approach to planning occupational therapy services. Allied health and casemix: towards 2000. Melbourne: The National Allied Health Casemix Committee, 1996: 11-14. Brandis S. The frustration of rehabilitation -- why quality doesn't pay. Proceedings of the Ninth Casemix Conference in Australia; 1997 Sep 7-10; Brisbane. Canberra: Commonwealth Department of Health and Family Services, 1997. Ferguson M, Capra S, Bauer J, Banks M. Coding for malnutrition enhances reimbursement under casemix-based funding. Aust J Nutr Diet 1997; 54: 102-108. Funk KL, Ayton CM. Improving malnutrition documentation enhances reimbursement. J Am Diet Assoc 1995; 95: 468-475. Fetter RB. The history and development of diagnosis-related groups. Proceedings of the Eighth Casemix Conference in Australia; 1996 Sep 16-18; Sydney. Canberra: Commonwealth Department of Health and Family Services, 1996. Commonwealth Department of Health and Family Services. Australian health organizations taking up the best practice challenge: the Best Practice in the Health Sector Program: case studies of the funded projects. Canberra: AGPS, 1996. Authors' details National Allied Health Casemix Committee, Melbourne, VIC. Annette L Byron, BSc, BND, MBA, Chairperson, NAHCC; Chief Clinical Dietitian, Nutrition and food Services, Royal Adelaide Hospital, Adelaide, SA. Helen C F McCathie, PhD, Executive member, NAHCC; Area Director of Psychology, Central Sydney Area Health Service, Concord Repatriation General Hospital, Sydney, NSW 2139. Reprints: Ms A L Byron, Nutrition and food Services, Royal Adelaide Hospital, North Terrace, Adelaide, SA 5000. E-mail: abyronATnadmin.rah.sa.gov.au

Synopsis All private hospitals and clinics must now supply de-identified data, using AN-DRG classification, on all admitted patients to the Private Hospitals Data Bureau. Contracts between health funds and hospitals must also be described on the basis of AN-DRGs, which will enable funds to undertake hospital variance analysis. These data provide the foundation for nationally developed clinical pathways and utilisation reviews which could modify clinical practice, improve standards and reduce health costs. Clinicians must understand and participate in these changes, and adequate safeguards are needed to protect them against loss of their clinical integrity, and against inappropriate discretionary control by private hospitals, healthcare corporations and health insurers. Introduction From February 1998, the Health Legislation (Private Health Insurance Reform) Amendment Act 1995 (Cwlth) requires all private hospitals to supply to the Private Hospitals Data Bureau de-identified data on all admitted patients. The data must include hospital charges and use the AN-DRG classification as part of the Hospital Casemix Protocol.1 Because of the impact this could have on clinicians and the delivery of healthcare in the private sector, it is essential that doctors understand and participate in decisions about use of AN-DRGs by private hospitals and health insurers, particularly in regard to healthcare finance and assessment of variance from predetermined healthcare protocols. Healthcare finance Public hospital costing differs from that in the private sector, mainly because of the medical salaries component, making direct comparison impossible. Current Australian private hospital financing includes a profit margin, but remuneration for medical services comes from the government, health insurance funds and patients. Casemix funding in the private sector would affect payment of doctors if the Commonwealth Medicare Benefits Schedule was altered to describe rebated services as casemix-based episodes of care (including pre- and postadmission care as described in expanded DRGs).2 Payment of doctors would also be affected if the government legislated for health funds to receive Medicare rebates for members' medical services and to incorporate these in AN-DRG-based payments to hospitals. The hospitals would accordingly be allowed to pay clinicians, perhaps under the terms of Hospital-Practitioner Agreements or other employment contracts. These are contracts required by legislation if a private hospital is to receive payments from a health benefit organisation and then pay the practitioner for services rendered to a member of that organisation. Increasing public health sector privatisation is attracting the interest of large healthcare corporations.3 They are looking to build, own and operate institutions, or to provide healthcare contracted out from established public hospitals. Use of the AN-DRG classification would facilitate comparison and allow comparable payments to be made by government for services between the two sectors. Public hospital AN-DRG funding is supplemented by other government budgetary allocations, but private sector institutions are dependent on health funds, which pay only for hospital services rendered to fund members -- they receive no other subsidies. Even the most efficient of these private institutions would be vulnerable if public AN-DRG costings were applied, or if any new costing methods were inaccurate or inadequate. These factors are beyond their control and are potential faults of casemix funding. This vulnerability would be compounded if a health insurer arbitrarily reduced either the prospectively determined price or the accepted length of stay of a given DRG in an effort to reduce fund expenditure. Clinical pathways could provide protection against such funding decisions and justify the clinical necessity of the length of stay or the hospital charge, and would thus force funds to provide supporting data. Assessment of variance from predetermined healthcare standards Of increasing interest to health insurers are methods of measuring and ensuring adherence to quality standards. If standards are inadequate, length of stay and readmissions may increase. This would mean rises in fund outlays and premiums, which in turn would have adverse effects on fund viability and membership. To establish comparable standards and clinical protocol guidelines, uniform case classification is required, enabling comparison between clinicians, hospitals and regions. This is now facilitated nationally by reporting of all admissions according to AN-DRGs. The two recognised ways of measuring standards and quality are the use of clinical pathways and utilisation reviews. Clinical pathways Clinical pathways are standardised protocols for given episodes of care, rather than compulsory recipes for clinical management. They improve efficiency of patient management by avoiding delays caused by lack of coordination and communication, and reduce average length of stay and costs without compromising quality.4 With innovations in care, clinical pathways provide a basis for proper comparison with current treatments. Clinical pathways are becoming widespread, not only because of quality issues but because of the profession's increasing awareness of the need for cost effective allocation of finite health resources. Clinicians have acknowledged concerns about clinical pathways: They are concerned that inappropriate protocols may be developed by clinicians with inadequate insight into practice or by health managers who favour cost control over quality; They question standardisation of care because of the inherent variability of patients, their diseases and their responses to treatment; and As responsible clinicians they must often make individual judgements, and they are concerned that lack of adherence to clinical pathways may expose them to litigation if their management results in an adverse outcome. The Health Legislation Act also requires contracts between health funds and hospitals to be described on the basis of AN-DRGs. This will enable fund managers to undertake hospital variance analysis. They can then ask hospital managers to investigate cost variability of particular AN-DRGs. Clinical pathways can provide reasons for variance and empower management to redress the system. Analysis of individual clinician variance could possibly result in suggestions for changes in care, economic punitive action (such as withdrawal of accreditation), or demands that a clinical pathway be adhered to as a condition of future accreditation or agreement between clinician and hospital. With accurate knowledge of hospital costs for AN-DRGs and reasons for interhospital variance, purchasers (health insurers) and providers (hospitals) can undertake properly based negotiations and establish appropriate payments. Hospital use and utilisation review of clinical pathways will be increasingly relevant in the negotiations for Hospital Purchaser-Provider Agreements, which a health benefit organisation may choose to enter into with a hospital for the provision of services to its members. The financial viability of private hospitals is dependent on these agreements. Utilisation review Utilisation review is defined as "A set of information activities which support, monitor and evaluate decisions concerning the allocation of healthcare resources to previous and current patients and potential recipients. The aim is to ensure that resultant allocations are cost-effective and equitable."5 It can be prospective (checking, then approving, modifying or rejecting a proposed management), concurrent (assessing and modifying current care) or retrospective (assessing previous decisions, considering their appropriateness, then acting by providing educational resources, denying payment, threatening or undertaking withdrawal of business). Utilisation review can be used to develop clinical pathways, assess resource allocation, or assess compliance with a stated clinical pathway. It allows comparison of hospitals and practitioners, particularly with regard to resource use (particularly bed-days) in the management of individual AN-DRGs. In managed care in the United States, utilisation review addressed overservicing and cost-cutting. Compulsory management protocols had to be fulfilled to enable prospective fund approval; non-compliant management led to retrospective denial of payments.5 The Australian health insurance industry is concerned about an increase in private hospital utilisation in spite of a decrease in insurance numbers. The industry is also concerned that the growth in day surgery has not decreased overall costs or services in the private sector (Mr R Schneider, Australian Health Insurance Association, paper presented to a Health Summit organised by Australian Investment Conferences, Sydney, 24 March 1997). Health insurers could establish compulsory protocols they regard as being within the scope of accepted clinical practice by AN-DRGs and as a condition of Medical Purchaser-Provider Agreements. These are contracts a health benefit organisation may enter into with medical practitioners to address the provision of services and the legally rebatable fees that can be paid by the organisation to the practitioners. Current and potential funding pathways for applying AN-DRG casemix in the private sector are shown in the Box. Implications for clinicians The two most relevant aspects of casemix for clinicians in the private sector are funding and assessment of adherence to quality criteria. The latter has significant ramifications for resource allocation and control of clinicians' practice and independence. It is unlikely that the medical component of private health costs will be incorporated into AN-DRG funding, but the hospital component could be based on finite bed-day allocation for each DRG (instead of the current open per diem payment) or as a case-based payment. Clinicians should be involved in these decisions. The collection and reporting of admission data based on AN-DRGs by private hospitals (as required by the Health Legislation Act) provide the foundation for nationally developed clinical pathways and utilisation reviews to modify clinical practice, improve standards and reduce health costs. The use of AN-DRG data could result in loss of clinicians' professional independence and make them vulnerable to punitive economic measures by hospitals and funds. These institutions could become de facto arbiters of which doctors are suitable to practise in the private sector. Until now the professional freedom of medical practitioners has been decided by ethics, the law, and standards of clinical care, as judged by the community and the profession itself. Economic management could become the new criterion upon which doctors will be judged by health insurers and private hospitals, regardless of practice standards. This must be fully appreciated and carefully considered by all sectors of the Australian community. The practical application of casemix could have a positive impact on the viability of the private health sector and a beneficial effect on clinical management of patients, but its degree of success will depend on the trust and involvement of clinicians. Health insurance funds are currently in fiscal crisis and one method of addressing this is to reduce fund outlays. The private sector relies on a viable health insurance industry and clinicians need to be aware of the cost implications of their management decisions. However, adequate safeguards are needed to protect clinicians against loss of their clinical integrity and inappropriate discretionary control by hospital owners, healthcare corporations and health insurers. References Commonwealth Department of Health and Family Services. Private Hospitals Bureau -- data flow requirements. 3 December 1997. (Circular HBF No. 513 and PH No. 288.) Health Solutions International. Expanded DRGs. An episode approach. Prepared for the Classification and Payments Branch, Department of Health and Family Services. 1997. (Available from Health Solutions International, East Melbourne, VIC.) Hurst J. Year of health carve up. The Australian Financial Review 1998; 2 Jan: 36. Private Sector Casemix Unit. Clinical pathways: a background for private hospitals and private insurers. 1997. (Available from the Private Sector Casemix Unit, Canberra.) Hindle D. Utilisation review. A discussion paper. Private Sector Casemix Unit. 1997. (Available from Private Sector Casemix Unit, Canberra.) Authors' details Australian Casemix Clinical Committee, Melbourne, VIC. Chris N Maxwell, FRCOG, FRACOG, Senior Obstetrician and Gynaecologist, and Director of Clinical Services Obstetrics, Gynaecology and Paediatrics, The Northern Hospital, Melbourne, VIC. Reprints will not be available from the author. Correspondence: Dr C N Maxwell, Northpark Medical Centre, PO Box 1080, Bundoora, VIC 3083. E-mail: cmaxwellATtnh.vic.gov.au