Letters

To the Editor: Roe and McDermott recently noted that the health benefits of swimming pools demonstrated by Silva and colleagues1 may be more modest than reported.2 Our initial observations from a remote South Australian Aboriginal community support this observation, but there are also many difficulties with study implementation that may introduce biases. A swimming pool was constructed during 2007 as a result of a community-led initiative. With ethics approval, trachoma screening was performed before the pool opening (November 2007) and 6 and 18 months after the pool was opened. Rates of middle ear infections, skin infections and antibiotic prescriptions among children aged 1–15 years were assessed using a retrospective analysis of clinic records between May 2007 and April 2009. A questionnaire regarding the benefits of and barriers to swimming pool use in the community was administered to key persons, such as community health workers and school teachers in April 2009. We aimed to examine every child in the community aged 1–10 years; 45/56 (80%), 46/62 (74%) and 59/64 (92%) children were examined at each of the three visits. The proportion of children with follicular trachomatous inflammation remained low and unchanged at the three time points (7%, 7% and 8%). The clinic records of 166 children showed a trend of increasing rates of infection and antibiotic prescriptions for the period. With hypoendemic rates of trachoma and possible confounding factors, including a small sample size, population mobility, reporting bias and a high turnover of health personnel, we were unable to demonstrate health benefits of pool usage. Our findings highlight the importance of avoiding complacency once a single intervention, such as a swimming pool, has been put in place. Long-term maintenance and supervision are needed to ensure efficacy of a pool. Aspects such as housing, sanitation, nutrition, education and substance misuse should also be high priorities when trying to address health conditions for which low socioeconomic conditions are major risks.3,4 Although we found no specific health benefits of having a pool, interviewees reported that the pool benefited the community in other ways, including providing an opportunity for exercise and recreational activity for otherwise unoccupied children, and creating an incentive to attend school, owing to a “no school, no pool” policy. The pool is a “public good”2 that cannot be denied based on lack of health benefits. Ongoing investigation is planned to monitor the effects of the pool in this community, and it may be too early to draw final conclusions concerning the health benefits of swimming pool use.

Anu A Mathew · Collin J McDonnell · Jill Benson · Hugh R Taylor

To the Editor: Li and colleagues analysed avoidable hospitalisation rates for Aboriginal and non-Aboriginal people in the Northern Territory, examined trends over time, and assessed “the implications for future primary care interventions”.1 Their study results confirmed that Aboriginal Australians in the NT experience significantly higher rates of avoidable hospitalisations than non-Aboriginal people. They also report a widening gap between avoidable hospitalisation rates of Aboriginal and non-Aboriginal people during the study period, 1998–99 to 2005–06. Avoidable hospitalisation rates are used nationally and internationally as an indicator of primary health care effectiveness and accessibility. However, debate continues about which conditions to include as “avoidable”, and the potential for errors in allocating and coding the primary diagnosis. Furthermore, serious methodological issues remain regarding the use of avoidable hospitalisation rates as an indicator of primary health care effectiveness and accessibility. The outcome measure “avoidable hospitalisation” is affected by more than just primary health care. This is acknowledged by Li et al,1 who identify other factors that affect hospitalisation, including disease prevalence and severity, and geographical remoteness.2 If these factors are not controlled for, it is not possible to attribute differences in hospital admissions to differences in quality of primary care. This would only be possible if Indigenous and non-Indigenous populations were similar in health status and residential location (and other important respects). Aboriginal people in the NT experience far higher rates of diabetes than non-Aboriginal Australians and the age of onset is far younger. For example, there is a 10% prevalence of diabetes in Aboriginal people aged 25–34 years residing in remote areas of the NT. This is 19.5 times the rate of diabetes in a sample of the Australian population of the same age (which will be close to the non-Indigenous rate in the NT), using data from the AusDiab study.3 This young Aboriginal population is also 18 times more likely to have multiple chronic conditions than the AusDiab group of the same age.3 Hospitalisation rates of a population with this health profile should be high, particularly if the primary care system is performing well. Even though Li and colleagues recognise the complexity of measuring primary health care effectiveness and access,1 they still attribute higher rates of avoidable hospitalisations to Aboriginal people’s lack of access to effective primary care. This simply cannot be deduced from their analysis, as it fails to adjust for the high and increasing incidence, prevalence and severity of chronic diseases in the NT Aboriginal population compared with the non-Aboriginal population. This type of misinterpretation of data is serious, given the potential policy implications. We agree that the research question is important, but it warrants a sophisticated analysis that properly adjusts for the most important confounders.

Odette R Gibson · Leonie Segal

In reply: The national and international use of avoidable hospitalisations as an indicator of accessibility and overall effectiveness of primary care1 has included reporting differences in hospital admissions for different ethnic populations and across different geographical regions to highlight inequities in access to primary care. Avoidable hospitalisation rates are also routinely reported for the Aboriginal and Torres Strait Islander population.2 Currently, there is no “gold standard”, but compared with other indicators, such as self-reported data from population surveys, avoidable hospitalisation rates are regarded as an objective and robust measure of primary care.3 Despite the established use, there are well recognised limitations in the interpretation of avoidable hospitalisations, which are outlined in our article,4 and also raised in the letter by Gibson and Segal. What our article highlights, using well identified data sources, is the difference in avoidable hospitalisation rates between the Northern Territory Aboriginal and non-Aboriginal populations, as well as the very different trends. There are expectations that current reforms in the delivery of primary care for Aboriginal Australians can be directly monitored by improvements in avoidable hospitalisation rates. Our results highlight the need for caution in interpreting changes in these rates, and the substantial risks associated with unrealistic performance benchmarks.

Shu Q Li · Natalie J Gray · Steve L Guthridge · Sabine L M Pircher

To the Editor: Duckett rightly points out that community knowledge and expectations of the delivery of medical services have increased in recent years, and that the “baby boomers” of today will not accept the hospitals of yesteryear.1 He claims that the Australian health system has responded to technological change, but not to sociological change. Although the introduction of new medical technologies — a process largely driven by clinicians — has helped ensure that Australians still have access to quality health care, the same claim can not be made for the other kinds of technologies necessary to support delivery and review of good-quality care; notably, health information technology lags lamentably behind other sectors. In addition, we have not been “adept in responding to technological change”, because we have not figured out how we are to pay for it. The sociological changes that Duckett is concerned with are well recognised by many working in the public health sector. He states that macro- and provider-level reforms set the context for the interaction between the patient and clinician. He seems inclined to view this interaction as the final frontier — resistant to change and responsible for what he characterises as an ongoing lack of responsiveness in hospitals and health facilities. However, his outdated and stereotypical characterisation of doctors working in the public health sector must call into question his knowledge of what actually goes on in modern health care settings, in addition to pointing to a tendency to underestimate the difficulties of working in these austere and pressured environments. The conversation that privileged baby boomers actually need to have is one that forms part of a public debate about how much health care costs and how we should be thinking about rationing its delivery, or else paying more for it, as Queensland Health has perhaps finally learned. It is disappointing that, despite Duckett’s long years of experience in the public health sector, he fails to address the real implications of the changes, both technological and sociological, to which he alludes in his opening paragraph — how exactly are we going to manage the ever-increasing demand for increasingly expensive treatments by an ageing population?

Heather J Cleland

To the Editor: The next challenge for medicine in Australia, in Duckett’s opinion, will be the need to provide for the “very different expectations . . . and a greater sense of entitlement” of baby boomers, as they reach old age and have more need for health services, in and out of hospital.1 They will not meekly wait for care — but how will waiting lists for appointments and elective surgery be abolished? They will not accept “cattle class” in outpatient departments — but who will pay for the replacement of wooden benches with easy chairs? They will not accept whatever is on offer — but who will provide what is not on offer at a time of need? They will expect frank discussion of choices, risks and outcomes — but which cardiac surgeon or registrar will have the time to go into the 40 different possible complications of coronary artery bypass, an operation with usually excellent results? And if nurse practitioners or podiatrists become leaders of the medical team, will they be professionally and legally responsible when outcomes are unsatisfactory or disastrous? People with visions of the ideal medical service should keep in mind a basic principle, expressed by Enoch Powell 42 years ago.2 Even in prosperous times, limited resources (trained staff, facilities and money) will never meet unlimited demands. Duckett’s baby boomers may have expectations, but they must be measured against reality. With the unceasing growth of knowledge, technology and pharmacology, medicine is not about to become cheaper.

Derek H Meyers

In reply: Notwithstanding the differences in tone, Cleland and Meyers make the same substantive point: that a challenge I ignored in my short piece was the costs of meeting the different expectations of baby boomers. Regardless of the changed expectations I discussed in my article, health costs over the next few decades are predicted to increase from just over 9% of gross domestic product to over 12%.1 Economists recognise that societies appear willing to devote more spending to health care as they get wealthier, perhaps to avoid confronting the difficult choices involved in some rationing decisions.2 But should we immediately jump to the conclusion that more rationing is inevitable? What other choices are there? First, we — policymakers and clinicians alike — need to address the waste and inefficiency inherent in the current system;3 and, second, change the health system so that it is better suited to respond to changing needs4 and potentially “bend the trend” of health cost projections. Third, we need to recognise that rationing — or, to use a less emotive term, priority setting — is already part of our health system. Australia leads the world in terms of formal processes before listing new drugs on the Pharmaceutical Benefits Scheme or items on the Medicare Benefits Schedule, but here too, improvements are needed. Clinicians are already involved in rationing choices, but different clinicians appear to have different thresholds of when (and what) treatment should be recommended. These differences may be cultural,5 and addressing these unexplained variations in practice patterns remains a policy work in progress. Thus, we in the health system have a lot of work to do in putting our house in order so that any rationing debate can occur knowing that alternative strategies have already been pursued.

Stephen J Duckett

To the Editor: Italiano and colleagues described a 49-year-old woman with prolonged vaccine viraemia, associated with hepatitis, streptococcal toxic shock syndrome and poststreptococcal reactive arthritis following routine varicella vaccination.1 The woman, initially seronegative for varicella zoster virus (VZV), was stated to be immunocompetent, possibly because she was previously well and produced varicella IgG following vaccination. It is not clear whether other aspects of her immune status were investigated. Although VZV IgG was detected after vaccination, indicating appropriate adaptive immune activation, this does not necessarily exclude a defect in the innate immune system. Natural killer (NK) cells, which comprise 10%–15% of total lymphocytes, are part of the innate immune system and play an important role in the suppression of VZV replication via direct cell killing and production of γ-interferon.2,3 A smaller population of lymphocytes, known as NKT cells, which express both NK cell surface markers and T-cell receptors, also appear be important in controlling VZV infection in humans.2 The role of these cells in the immune response to varicella vaccine is unclear. In children, NK cell cytotoxicity increased after wild-type VZV infection but not after vaccine administration.4 However, disseminated life-threatening VZV infection was observed after varicella vaccination in a child with NKT cell deficiency.2 Primary isolated deficiencies and functional defects in NK function have been reported in children and adolescents with severe, life-threatening wild-type VZV infection.5 Some of these patients were previously well and came to medical attention only after VZV exposure. It is not clear how many had prior varicella vaccination, but at least one patient had previously received VZV vaccine with no adverse consequences and developed disseminated disease only with the wild-type virus. Acquired defects in NK immunity have also been reported. Severe transient depressions of NK and CD8 cell numbers and NK cell function have been documented in children at the time of severe VZV infection, with return of immune competence following convalescence.3 This phenomenon may be due to initial CD8 and NK cell exhaustion or redistribution of these cells from the circulation into inflamed peripheral tissue under the influence of chemokines.3 It has been suggested that an NK cell defect should be considered in unexplained severe herpesvirus infections.5 It would therefore be of interest to determine NK cell number and function and NKT cell number in the patient reported by Italiano and colleagues.

Sam S Mehr · Andrew S Kemp

To the Editor: The introduction of non-invasive prenatal testing will revolutionise the practice of prenatal diagnosis. One of the many potential applications of non-invasive prenatal diagnosis (NIPD) is to determine fetal RHD status in pregnant Rhesus (Rh) D-negative women, and the feasibility of such testing was aptly demonstrated by Hyland and colleagues1 and commented on by Cole and Savoia.2 It is clear that once the technical problems of indeterminate results and gene variants are resolved, NIPD for RHD status will have improved clinical utility over current invasive testing, thus reducing the need for invasive procedures and prophylactic treatment of all RhD-negative women. The assay developed by Hyland et al can also be used to determine fetal sex, indicating a potential additional use in women at risk of carrying a fetus with a sex-linked disorder, so as to halve the number of chorionic villus sampling (CVS) tests being performed. However, it is worth noting that the number of CVS tests currently performed for this indication is extremely small. In Victoria, the complete population-based dataset on prenatal diagnosis for 2007 shows that there were only eight invasive tests for sex-linked disorders.3 The most significant impact of NIPD technology will be for pregnant women who request prenatal testing for Down syndrome. If NIPD testing for Down syndrome becomes available, it is anticipated that current testing based on chromosome analysis (karyotyping) of a sample obtained by CVS or amniocentesis will become redundant. However, replacing karyotyping — a genome-wide test — with a targeted NIPD test for Down syndrome will mean that many of the other chromosome abnormalities currently detected by CVS or amniocentesis will no longer be detected.4 We do not know whether this is important to women or not. Before implementing any NIPD test, we suggest that each application needs a separate investigation, including a careful comparison of clinical utility between current tests and the proposed replacement technology.

Marleen R Susman · David J Amor · Jane L Halliday

To the Editor: The authors of the recent MJA article “Making cars and making health care: a critical review”1 have misunderstood the importance of process design in a service as complex as health care delivery. They state that the Toyota “lean thinking” model has been “accepted somewhat uncritically” in health.1 In fact, the opposite is true. Work practices and roles in conservative institutions such as public hospitals have changed minimally over many years. Cutting-edge medical technology is delivered within an archaic work practice model that fosters inefficiency, frustration and unnecessary expense. Inefficient work practices give skilled clinicians less time with their patients — not more. Like Winch and Henderson, let’s take an example from the surgical field. Years ago, when public hospital beds were relatively accessible, many patients were admitted for “work-up” and spent days in their pyjamas in hospital before planned surgery. The application of the “just in time” principle has led to the huge turnaround to day-of-surgery and day-only admissions — freeing up beds and saving enormous cost as well as many unproductive days for patients. This is only one small example. Lean thinking is just one model for improving the way in which complex processes are coordinated.2 Far from being “highly stylised and simplistic”, lean thinking is about removing redundant steps and reducing duplication, waiting times and errors. It’s about investing in the talent and skill of trained staff, by maximising the value they add to whatever process they are working on and minimising the extraneous tasks they have to do.3 Managed properly, this can result in faster and better care delivered by happier staff, with more time to “cure and comfort”.1

Susan Ieraci

In reply: Our article highlighted issues with the uncritical adoption of car-making processes into health care planning — specifically, the regulation and splintering of the human element of a care pathway. While day-of-surgery admission speeds patients through the system, the capacity for error remains and relates to our original arguments. For example, one assumption commonly made is that the patient or carer has the literacy level to understand the presurgical procedures, such as fasting, taking particular preparations or completing health history forms. Yet the Australian Bureau of Statistics reported in 2003 that 37% of the population met only the minimum literacy standard (Level 3) required to function in a complex society such as ours in Australia.1 Forty-six per cent fell below this benchmark. For health literacy specifically, 35% of the population met only Level 3 standard, with about 60% falling below this standard. This indicates that some of the work we have happily “outsourced” to the patient may be poorly understood and cause problems further down the line. It also highlights another key difference between cars and people: baseline control of the beginning raw material is difficult to achieve.

Sarah Winch · Amanda J Henderson

To the Editor: Eslick and Eslick believe that the television program The Simpsons causes children to smoke.1 What they gloss over is that in this show, only “losers” smoke. The characters Patty and Selma are old, ugly, mean-tempered, sexually frustrated sisters working in deadening jobs at the motor vehicle licensing office. They don’t just smoke, they chain-smoke — a well established television trope for sleaze and disease — and then they cough, hack, and wheeze. Krusty the Clown, if the name doesn’t tell you already, is a beaten-up, ageing, balding guy. He’s nasty, neurotic, and estranged from his father for abandoning his orthodox Jewish roots for the sinful life of television. Mrs Krabappel, the schoolteacher, is old, divorced, ugly, hates her job, hates her life, and hates children. It may be that children watch The Simpsons. I don’t know, and Eslick and Eslick cite no data that show they do. The questions, though, are: Do children understand what a loser is? Do they emulate losers, or shun them? Eslick and Eslick cite studies showing that any portrayal of smoking causes children to smoke.1 If this is so, why bother to differentiate between “neutral”, “positive” and “negative” portrayals of smoking? And what, precisely, do these labels mean? If, as they say, the “most notable characters” who smoke are these four loser characters, it is strange that they have coded most smoking instances as neutral rather than negative. Even if the authors have a valid labelling system, and even if neutral portrayals cause children to smoke, the question then becomes: is this effect greater than any countervailing effects, such as, perhaps, that of discouraging adults (and adults who are parents) from smoking, or that of creating a broad cultural association between smoking, social failure, and sickness? The logic of the argument put by Eslick and Eslick is that smoking should not be depicted at all in television programs that children watch. Given that children see people smoking in real life, and presumably look around them for some guidance as to whether they should do it too, it seems to me that it is actually commendable to tell them that only losers smoke. Strong evidence and argument that this approach does more harm than good would be very valuable.

Nicholas Jefferson-Lenskyj

To the Editor: The article by Eslick and Eslick1 caught my attention, as the sophisticated parodying of the tobacco industry on The Simpsons has been a much discussed topic among my tobacco-control colleagues. In the introduction to the article, the authors ask if the smoking and tobacco industry portrayals in this program are “just satire, or does the repetitive nature of characters smoking on The Simpsons have an influence on young children watching?” The study design employed cannot answer this question. I was surprised then that the authors concluded that the portrayals of smoking on The Simpsons negatively influence young children. The study results indicate that positive portrayals of smoking on the show are, in fact, extremely rare. It could equally be the case that the more numerous negative portrayals of smoking on this popular and subversive comedy reach young viewers in a way no government-sanctioned health promotion campaign can. Health education messages presented through social satire may not be politically correct, but this does not mean they are ineffective in communicating antismoking sentiments.2 The two most prominent smokers in The Simpsons, Patty and Selma Bouvier, are not characters that any teenager would aspire to be like — disgruntled, middle-aged sisters who live together, work in depressing jobs at the local Department of Motor Vehicles, Selma constantly bemoaning her lack of a husband and fantasising about 1980s heart-throb MacGyver, and Patty best known for her utter joylessness and cynicism. Surely these grim stereotypes would cause most young people to turn away from smoking, and not towards it? Tobacco-control policies themselves were recently lampooned in The Simpsons, with the Simpson family opening a pub in Ireland that illegally allowed patrons to smoke. Much mayhem ensues, and the Simpsons are eventually deported back to the United States for breaking the Irish antismoking laws.3 I am delighted that tobacco control has such universal momentum that it can be parodied on a pop-culture phenomenon like The Simpsons.

Becky Freeman

To the Editor: I read with interest the recent case report by Lim and colleagues on Chromobacterium violaceum endocarditis.1 References to the article do not include a report of a similar case published 20 years ago, also in the MJA.2 Perhaps reference searches can be enhanced — otherwise, identifying such similar cases falls to recollected experience (I was the initial treating doctor in the 1988 case) or an improbably capacious memory in the author or reader. What saved the patient in February 19882 were two new antibiotics that were not generally available at the time but were held at Royal Brisbane Hospital — imipenem and ciprofloxacin. Imipenem is a β-lactam antibiotic of the carbapenem subgroup, derived from Streptomyces cattleya, that was developed in 1985.3 Imipenem and other carbapenems including meropenem, as used to treat the patient in the article by Lim et al,1 are now available in Australia but restricted to intravenous use in hospitals. The oral antibiotic ciprofloxacin became generally available with a Pharmaceutical Benefits Scheme authority benefit soon after the 1988 case. I recall a discussion at that time with the late Dr Richard Kemp (then Director of Infectious Diseases at Royal Brisbane Hospital), who told me that C. violaceum infection in humans had been described in the world medical literature only about 10 times, and there had been no eventual survivors. From a general practitioner’s perspective, there was a lesson to be learned from the case: take the time to swab an abscess. The one in question was unusual — volcanic in appearance, indurated and not productive of pus on incision.

Richard N Pearson

To the Editor: Nordin and colleagues raised important issues about prescribing for osteoporosis.1 We agree that the Pharmaceutical Benefits Schedule guidelines for therapy are imperfect, but they do not necessarily lead, as Nordin et al claim, to inappropriate prescribing. For historical reasons, osteoporosis is held to be synonymous with vertebral fractures, but this misrepresents the epidemiology of fractures. Non-vertebral fractures account for 80% of all fractures and 90% of the loss of quality of life and economic costs. Vertebral fractures contribute only 20% of the burden.2 Most fractures arise in the large population at moderate risk with osteopenia — the “bell” of the Gaussian bone mineral density (BMD) distribution, not its “tail”, which comprises those with osteoporosis (defined by a bone densitometry T-score less than – 2.5). Concentrating on vertebral fractures and screening for osteoporosis with bone densitometry, as recommended by Nordin et al, is no solution to this public health problem. Nutritional change and exercise are appealing because they are safe and cost-effective approaches for early intervention, but are supported only by level D evidence (expert opinion).3 Although these approaches are plausible, no trials demonstrate their antifracture efficacy. There are no means of early identification of individuals who will sustain a fracture. Densitometry is neither sensitive nor specific for fracture; most people with osteoporosis do not sustain a fracture, and most fractures arise in people without osteoporosis, who would, paradoxically, be excluded from treatment by screening.4 Bone densitometry should be more accessible for case finding, but its use for screening does not reduce the fracture burden because of this screening paradox. However, Medicare reimbursement for densitometry is available for high-risk individuals (those with premature menopause, other illnesses or who are taking corticosteroids), not just for those aged over 70 years or those with fractures. Restricting treatment on the basis of BMD results is not advocated by the Australian and New Zealand Bone and Mineral Society precisely because it excludes this moderate-risk group from treatment, particularly those with fractures and osteopenia. There is level A evidence (meta-analysis of multiple randomised trials)5 for the antifracture efficacy of bisphosphonates in patients with osteoporosis, and evidence based on single trials6 of their antifracture efficacy in those with osteopenia and prevalent fractures, whose fracture risk is similar to that of people with osteoporosis and no prevalent fracture. There is limited evidence of antifracture efficacy of bisphosphonates in individuals with osteopenia alone.6 Preventing the first fracture is important, and guidelines are deficient in this way. Case finding to estimate absolute risk is the best approach available at this time, using risk factors, remodelling markers and, more recently, microstructural analysis to improve sensitivity and specificity. Rather than inappropriate or overprescribing, evidence suggests underutilisation of drug therapy for osteoporosis.7,8 Osteoporosis remains underdiagnosed, underinvestigated and undertreated, and limiting access to bone densitometry is not supported by the Australian and New Zealand Bone and Mineral Society.

Ego Seeman · Mark A Kotowicz · Peter T Nash · Philip N Sambrook

In reply: Seeman and colleagues agree that most patients with minimal trauma fractures do not have osteoporosis. The figures are clear: only 13% of patients with a peripheral fracture have a hip bone mineral density (BMD) T-score less than or equal to − 2.5 and only 25% have a score less than or equal to − 1.5. The corresponding figures for vertebral fractures are 25% and 38%, respectively.1 We do not argue that the − 2.5 T-score threshold for defining osteoporosis is sacrosanct, but simply that some bone density threshold be defined for subsidised therapy, for which virtually all the supporting evidence is based on treatment of patients with established osteoporosis. Osteopenia is an artificial concept with an arbitrary definition, but we agree that the T-score threshold for subsidised therapy need not be as low in those with prevalent adult fracture as in those without — perhaps − 1.5, which is the threshold recently adopted for patients receiving corticosteroid therapy. We disagree about the predictive power of bone densitometry; it is comparable to that of blood cholesterol level for heart attacks and blood pressure for stroke.2 It therefore makes sense to measure BMD in all women at menopause and all men at age 60 years to identify those with osteoporosis before they sustain fractures, as well as those with normal but negative T-scores, who have a fracture risk twice that of those with positive T-scores.3 Those with proven osteoporosis could receive subsidised therapy, and those with low normal values could be advised on lifestyle measures, such as calcium supplementation (which significantly delays or prevents bone loss in postmenopausal women).4 People with positive T-scores can be reassured. To suggest that no trials have demonstrated the antifracture efficacy of nutritional measures is to argue against three large meta-analyses showing significant prevention of fractures with vitamin D and calcium supplementation.5-7 The additional cost of confirming low bone density before providing subsidised therapy in fracture cases is likely to be more than offset by the savings from reduced inappropriate therapy; bone densitometry costs about $80 per test, but bisphosphonate therapy costs about $50 a month for each patient. The extra cost of bone densitometry for every woman at menopause and every man at age 60 years could be $20 million a year, but even with subsidised therapy for those without fracture but proven osteoporosis (with a T-score less than or equal to − 2.5, for instance), the cost is also likely to be more than offset in the long term by reducing the enormous cost of osteoporotic fractures ($8 billion annually8). We find it hard to understand why any of our colleagues would not support proposals that would transfer treatment from those who do not need it to those who do.

B E Christopher Nordin · Michael Horowitz

To the Editor: The ASPREE (ASPirin in Reducing Events in the Elderly) study may provide useful data on the benefits and risks of aspirin therapy in patients aged ≥ 70 years, as described by Woods and colleagues.1 However, the decision to allow general practitioner co-investigators to “help decide whether the patient is a suitable candidate for the placebo-controlled trial” introduces a source of selection bias that may limit the generalisability of the results. Without pre-specified objective selection criteria, it is likely that primary-prevention patients assessed by GP co-investigators as being at high vascular risk will be excluded because the GPs believe they should be taking antiplatelet agents. Similarly, those at low risk may be thought inappropriate participants because the risks of random allocation to this therapy might outweigh the perceived benefits, as has been shown in previous meta-analyses.2,3 ASPREE may end up with a disproportionate number of intermediate-risk patients. In the case of diabetes, a recent observational study from our group highlighted patients with diabetes and retinopathy and those taking a sulfonylurea as being at increased risk of complicated peptic ulcer disease.4 By contrast, we did not find that aspirin use, positive serological results for Helicobacter pylori, or the interaction of these two factors predicted complicated peptic ulcer disease. If GP co-investigators were aware of these findings, they might also influence the screening and recruitment of patients with diabetes to ASPREE. According to the trial registration details (ISRCTN83772183), patients with diabetes were eligible for recruitment to ASPREE from late February 2009, even though the trial started 6 years ago.5 Given this delayed eligibility, the fact that a substantial proportion of patients with diabetes older than 70 years will already have vascular disease, and the expected total sample size of 19 000,1 the trial might include fewer than 1000 patients with diabetes and thus have insufficient statistical power to assess the risks and benefits of aspirin for primary prevention in this important subgroup. We question why subjective assessment forms part of patient selection for a potentially important study such as ASPREE, and also what steps the investigators are taking to determine whether the sample they recruit is representative. In addition, details of planned statistical analyses involving diabetic participants in this non-superiority trial would be reassuring.

Timothy M E Davis · Brett A Sillars · Wendy A Davis

In reply: Recruitment to clinical trials through general practice is representative of the population, as a high proportion of all Australians regularly attend their general practitioners.1 GP co-investigators are appropriate to decide whether their patients are suitable for the ASPREE (ASPirin in Reducing Events in the Elderly) study because their assessment includes objective inclusion and exclusion criteria that must be satisfied before enrolment in the study (clinical trial registration number ISRCTN83772183),2 as well as patient-specific potential risks with using aspirin, and known medical factors likely to influence patient survival during the trial. These include the risk of complicated peptic ulcer disease in patients with diabetes treated with a sulfonylurea.3 GP co-investigators support participation in ASPREE by eligible patients because of aspirin’s therapeutic equipoise for primary prevention in older patients4 and in those with diabetes.5 Because of age alone, ASPREE participants will be at least at intermediate risk of cardiovascular disease and also at increased risk of bleeding. Determining the aspirin balance underpins the importance of collecting more data in older people, who have been under-represented in previous primary prevention trials. ASPREE is a superiority trial with pre-specified subgroup analyses, including for the subgroup with diabetes.2 The study is powered to address the primary question reliably in the total cohort rather than subgroups. To date, fewer than 500 participants have been randomly allocated, with recruitment slowed subject to National Institutes of Health funding deliberations. Recruitment will be reinvigorated in late 2009, and will continue to include people with diabetes.

Robyn L Woods · Mark R Nelson · Andrew M Tonkin · Christopher M Reid

To the Editor: Wiseman and colleagues reported the 9-month virological follow-up of babies born to pregnant women attending urban antenatal clinics who tested positive for hepatitis B surface antigen (HBsAg).1 Evaluation of outcomes is vital to determine implementation and effectiveness of current policy. The authors state that hepatitis B immunoglobulin (HBIG) and hepatitis B virus (HBV) vaccine were delivered within 12 hours of birth to all infants of HBsAg-positive mothers. Nine months after birth, transmission was documented in only four infants, all of whom were born to mothers who were positive for hepatitis B “e” antigen (HBeAg) and had very high HBV DNA levels (> 108 copies/mL). Yet one of the four infected infants had inadvertently not received the “routinely offered” HBIG. Whether any other babies (even if not infected) also failed to receive timely active and passive immunisation was not explicitly reported. The other three infected infants completed HBIG injection and HBV vaccination according to the “recommended schedule”. Given that the Australian immunisation handbook states that [t]he first dose of monovalent hepatitis B vaccine should be given at the same time as HBIG ... as soon as possible — preferably within 24 hours of birth, and definitely within 7 days,2 the exact time is unclear. Potentially, a delay of many hours to many days could occur. Yet, for all infectious diseases for which post-exposure prophylaxis is given, administration as soon as possible after exposure is universally recommended to prevent transmission.3 For babies born to known HBeAg-positive mothers, particular effort is warranted to ensure that they receive HBIG and HBV vaccine immediately after delivery, and certainly within hours of birth. There are many difficulties in achieving high rates of follow-up in this group, and only 66% of babies in the study by Wiseman and colleagues had virological follow-up results available. Unfortunately, the authors did not make the important distinction between babies lost to follow-up and those who were not yet 9 months old at the time of follow-up. This is in spite of the fact that the study included many South-East Asian women, who have markers of high HBV replication and whose follow-up is suboptimal.4 Evaluation of HBV vaccination policy requires that studies report fully on outcomes, including loss to follow-up. Also, given that delay in administration of HBIG and HBV vaccine after delivery may be a critical source of variation in outcome, future studies should specifically report this information separately for all births to HBsAg- and HBeAg-positive mothers, and for any cases in which transmission does occur.

Sandra C Thompson

In reply: We thank Thompson for her comments. We endeavoured to contact women by phone, by letter, or through their local doctor (if known). With respect to the 69 infants lost to follow-up, five of the mothers declined assessment, four had moved interstate or overseas with their families, five had infants who had not reached 9 months of age, and the remaining mothers were uncontactable. Follow-up of a cohort of this kind is difficult, for reasons that include language barriers and high rates of mobility. Furthermore, at the time of the study, testing the babies was not standard practice and not enthusiastically received by all mothers. We are not a public health unit and are not resourced to pursue follow-up beyond the measures described. Nevertheless, through strong engagement with the mothers, who were referred on the basis of their hepatitis B virus (HBV) infection, we achieved follow-up for a large number of babies. The data stand as valuable but not perfect. As mentioned in our article,1 vaccination practice for babies born to infected mothers is for hepatitis B immunoglobulin and the first HBV vaccine dose to be given (in opposite thighs) within 12 hours of birth. The babies’ vaccination records were checked by consulting the “blue book”, a standardised medical record for infants, and, for those infected, by cross-checking with the hospital medication chart.

Miriam T Levy · Elke Wiseman

To the Editor: I was interested to read the results of Sweidan and colleagues’ study of drug interaction alerts in prescribing and dispensing software.1 I believe their use of the terms “sensitivity” and “specificity” differ from the standard definitions, which are usually: Sensitivity = true positives ÷ (true positives + false negatives) Specificity = true negatives ÷ (true negatives + false positives)2 To test sensitivity and specificity, one requires a dataset that includes positives and negatives. I do not view “minor interactions” as a complete set of negatives, because a complete set of negatives should include a statistically valid number of randomly chosen drug sets without interactions. Minor interactions do not meet my criteria for “negatives” because, to me, a minor interaction is still an interaction that may sometimes be clinically significant. A true negative should meet the test of “never clinically significant”. Some reported minor interactions would meet that test and some would not. I believe sensitivity and specificity data should be reported for both major and minor interaction alerts. I also believe there should be some alignment of definitions between “drug interaction” research and “adverse drug event” research.3 Bates and colleagues talked about “adverse drug events” and “preventable adverse drug events” in 1995.4 Of most clinical interest are the preventable adverse drug events, which could be minimised by the use of appropriate decision support.5,6 Certainly, there is a need for independent assessment of the quality of electronic prescribing decision support systems. A robust assessment methodology is required to permit potential government regulation of such resources, which are of national and community importance.

Ian R Cheong

To the Editor: As the former Clinical Information Specialist Manager for the MIMS DrugAlert knowledgebase (from 2003 to 2005), I write in response to the study by Sweidan and colleagues examining the quality of drug interaction alerts in prescribing and dispensing software.1 The authors point out that the success of any knowledgebase in providing clear, correct and specific alerts at the point of care is subject to the quality of its technical integration into decision support software. I would like to add that the sensitivity of drug interaction decision support is determined largely by the knowledgebase, while the specificity of the system is subject to the intelligence of the software in which it is employed. I would be interested to know if the low specificity that Sweidan et al found for the MIMS DrugAlert database was due to lack of use of the severity or level of evidence settings, or having these set at inappropriate levels. The MIMS DrugAlert knowledgebase was in some ways a unique decision support database, written by Australian staff for use in Australia and New Zealand. It soon became one of the largest commercially available databases of drug interaction information in the world, covering over 4600 drug-class and individual drug interactions. Its writing alone was a remarkable feat, being completed in a matter of months and further expanded over a subsequent 18-month period. There are significant variations in practical advice between American and European sources of drug interaction information. In writing the MIMS DrugAlert database, we sought to communicate “the right information, at the right time, in the right way” to local professionals. The foundations of MIMS DrugAlert were based on a clear understanding that we would be representing relatively simple pharmacological principles through the structure and content of a relational database. This meant creating interacting drug classes reflective of the pharmacological properties of groups of drugs, rather than simply grouping drugs based on their chemical families alone. Sweidan and colleagues should be congratulated on highlighting the need for comprehensive, accurate and useful information that can reduce medication error and save lives at the point of care. What is lacking is a clinical outcomes-based study focusing on the real-world benefits that can be achieved if the right system can be implemented in the right way, at the right price. Perhaps this type of research would then build on the excellent, basic foundational research carried out by Sweidan et al.

Bryan W Tan

In reply: Cheong notes that the terms “sensitivity” and “specificity” have a slightly different meaning in our study compared with the usual definitions. This was intentional, and the definitions we used are clearly described in our article.1 Our definitions for sensitivity and specificity were based on two important practical considerations. First, an electronic prescribing system should alert the clinician to potentially clinically significant drug interactions (“true positives” by our definition); and second, a system should not inundate clinicians with alerts containing irrelevant or unhelpful information about minor or clinically unimportant interactions (“false positives” by our definition). We know that these latter alerts can cause “alert fatigue” and are a subject of complaint for doctors and pharmacists. We are not aware of there being any problem with prescribing systems producing alerts for pairs of drugs that do not interact at all; hence, we did not investigate this group. Tan questions whether the low specificity we found for the MIMS DrugAlert database may have been due to inappropriate severity level settings. Although it might seem appealing to reduce the number of alerts by allowing users to “switch off” drug interaction alerts that are classified as low severity, there are difficulties in doing this because of a lack of evidence for the application of severity ratings to drug interactions. Severity ratings are subjective — studies have shown there is little consensus on such ratings between major reference sources.2,3 This is not surprising, given that there is little evidence available on adverse clinical outcomes resulting from drug interactions, and also because the clinical outcome is context-dependent according to variables such as patient characteristics and drug dosage. We believe that, rather than relying on software vendors or users to switch off some alerts, drug interaction knowledgebases should include only potentially clinically significant interactions. We tested all systems at the lowest severity setting (if available) for consistency, and to maximise detection of drug interaction alerts. For minor interactions, the rating was based on both presence of the alert and quality of the information — if a minor interaction was either not detected or was detected and provided appropriate information indicating it was minor, then it was a “pass”.

Michelle Sweidan · James F Reeve · Jo-anne E Brien · Pradeep Jayasuriya · Jennifer H Martin · Graeme M Vernon

To the Editor: Francis and colleagues revealed a significant 29-minute decrease in the median emergency department (ED) length of stay and reductions in mean turnaround times for full blood count requests following the redesign of pathology processes.1 Laboratory performance and clinician satisfaction are intrinsically bound up with the timeliness of test results, not least because of their effects on patient diagnosis and treatment. The association between test turnaround times and ED length of stay is difficult to decipher. The reasons for this, as pointed out by Francis et al, include the many potential variables that contribute to patient length of stay in EDs. Turnaround times can also vary dramatically according to laboratory operating procedures and work processes. Nevertheless, there is a strong imperative to monitor these indicators as contributors to designing effective interventions to improve the quality and outcomes of patient care. Our research has also revealed that pathology test turnaround times are a significant contributor to ED length of stay at a major teaching hospital in Sydney. Using regression analysis to account for a number of contributing length-of-stay variables (eg, triage category, patient age, number of tests ordered), we produced a model that accounted for 25.4% of the variance in ED length of stay, of which pathology test turnaround time was a significant contributor.2 Further, studies of the effects of electronic test-ordering systems on test turnaround times in five Australian hospitals have shown that introduction of these systems in each instance was associated with significant declines in test turnaround times.2-4 Thus, there appears to be converging evidence of a relationship between efficient test ordering and processing and reduced ED length of stay.5 In addition to the types of interventions described by Francis et al, electronic test ordering should be considered as a system-wide intervention that may contribute to improved efficiency and patient outcomes. Decision support within such systems provides an added ability to provide alerts and guidance in the test-ordering process.

Andrew Georgiou · Johanna I Westbrook

In reply: A recent report on the state of Australian public hospitals highlights figures of 320.6 emergency presentations per 1000 weighted population, with 88% of presentations being triage categories 1–4, and 66% of patients not admitted.1 In our experience, pathology tests are performed on more than 50% of patients in these triage categories who present to emergency departments, and decisions regarding patient care are delayed pending availability of test results. In addition to the initiatives that we described,2 Georgiou and Westbrook describe other initiatives that deliver significant, sustained improvements in health care efficiency. Many have emphasised the need to improve efficiency in the health care system by utilising evidence-based best practice. However, a recently published discussion paper highlights the challenges associated with ensuring that health care workers have access to, and actually use, evidence-based processes and protocols that have been shown to benefit patients.3 Similarly, delays in care may contribute to patient harm, and decisions about resource allocation and organisational systems do not always explicitly take this risk into consideration.3 These challenges may be partly related to the different funding arrangements in the Australian health care system. Apart from the obvious federal–state dichotomy, diagnostics, such as pathology services, and the associated information technology are often funded separately to the hospitals and health care professionals relying on these services. As a result, one of the challenges of implementing initiatives that improve efficiency relates to current and historical allocative funding arrangements, where costs may be borne by one cost centre, and benefits are delivered to patients and other elements of the health care system (ie, other health care providers and departments). It is essential that the Productivity Commission4 considers all of these elements in its review to identify significant efficiency improvements within the hospital system. Effectiveness, allocative efficiency and dynamic efficiency are just as important as simple economic efficiency. Unnecessary delays in the health care system are not only associated with capital costs — they are also associated with an array of direct and indirect costs related to caring for patients who endure an unnecessarily protracted journey through the health care system. It will take courage and commitment to implement and achieve appropriate use of evidence-based care (perhaps via mandates3) and appropriately fund all elements of patient care, so that improvements in care and overall cost savings are not hindered by historical funding constraints.

Andrew J Francis · Michael J Ray · Mary C Marshall

To the Editor: Grayson and Johnson’s editorial of 17 June1 and Eizenberg’s viewpoint article of 1 July2 both betray blind spots regarding Victoria’s laboratory response to pandemic influenza (H1N1) 2009 (“swine flu”) and the role of the Victorian Infectious Diseases Reference Laboratory (VIDRL). Grayson and Johnson incorrectly suggest that Victoria’s swine flu infection case definition represented a barrier to laboratory testing and detection of disease spread. Between 18 April 2009 (when the second case was identified in the United States) and 18 May 2009 (when the first case was identified in Victoria), VIDRL tested more than 500 specimens for respiratory viruses. All 16 influenza viruses detected were seasonal influenza strains. Swine flu testing was appropriately reserved for cases with a high pre-test probability of being positive, and even in this at-risk population, no positive cases were detected. The same authors highlight VIDRL’s prominent role in public hospital testing for viral diseases, but mistakenly conflate this with public health laboratory support of infectious disease outbreaks, as if concentration of diagnostic virology at VIDRL were a matter of policy. VIDRL’s diagnostic service is available to Victorian health care institutions for as long as they elect to refer specimens. There is no barrier to decentralising this capacity through access to appropriate new technology and scientific expertise. Nevertheless, centralisation of laboratory capability with optimised specimen transport and reporting offers an arguably more efficient model, and is widely used for this reason. On the other hand, VIDRL’s public health role in supporting the Victorian Department of Human Services’ (DHS’s) outbreak response capability represents a deliberate centralisation of capacity — for good reasons. Public health laboratory testing needs enormous surge capacity — on 1 June 2009, for example, we processed 1004 specimens requiring 1401 swine flu polymerase chain reaction (PCR) tests in a laboratory normally doing 100 respiratory tests daily. Public health laboratories also require expertise to develop, validate and perform essential tests during the early high-pressure phase of an outbreak, while also working closely with the DHS to manage the large patient data flows that underpin public health actions. There is nothing visionary about frittering away this crucial response capacity by devolving responsibility to a series of small nodes, each below critical mass. Both Grayson and Johnson and Eizenberg make misleading generalisations about test turnaround times and refer to non-existent backlogs. On 1 June, the most demanding day of the swine flu outbreak, the mean turnaround time for the 1401 PCR tests performed was 24 hours, with 90% of samples being tested within 32 hours of receipt. There are several reasons outside VIDRL’s control why occasional delays might have occurred. Firstly, transport from point of collection to VIDRL was often slow (1–3 days, with few if any public hospitals achieving faster times). Secondly, more than 10% of samples arrived with missing or incorrect information regarding addresses for reports. Eizenberg should note the high number of general practitioners completing a private pathology provider’s request form but sending the specimen directly to VIDRL, causing delay while results went to the apparent referring laboratory. More than 200 specimens arrived with no request forms at all. Finally, many organisations had no mechanism in place for receipt of large numbers of test results late in the evening, when VIDRL was continuing to work. With Victoria’s move to the “Sustain” phase of the pandemic influenza plan on 3 June, test capacity was directed to defined clinically at-risk patients.3 Many hundreds of samples not meeting the criteria for testing continued to arrive each day. Between 5 and 16 June, these were stored but not tested, and an immediate report went to the sender saying so, and explaining why. Although the capacity to test approved samples was never under threat, stocks of key PCR reagents were transiently sufficiently limited in Australia to preclude testing of samples classified as not meriting a laboratory test in the first place. It may be this scenario that Eizenberg tries inaccurately to describe. It is disappointing to be drawn into exchanging correspondence in these pages rather than having a constructive debriefing together at the end of this outbreak. No criticism by us of laboratory colleagues is intended, as we know there is a shared sense of the logistic challenges with which we have grappled, and can improve together. However, the record still needs to be put straight for a small number of physicians with a more limited grasp of the issues.

Michael G Catton · Julian D Druce · Chris J Birch