Are rates of pathology test ordering higher in general practices co-located with pathology collection centres?

David M Studdert, Helena C Britt, Ying Pan, Salma Fahridin, Clare F Bayram and Lyle C Gurrin
Med J Aust 2010; 193 (2): 114-119. || doi: 10.5694/j.1326-5377.2010.tb03819.x
Published online: 19 July 2010


Objective: To determine whether rates of pathology test ordering by general practitioners in general practices co-located with pathology collection centres (PCCs) are higher than those of GPs in practices located apart from PCCs.

Design, setting and participants: We identified all practices in the Melbourne and Sydney metropolitan areas that were co-located with PCCs (same or immediately adjacent suite) and the date co-location was established. This information was merged with the Bettering the Evaluation and Care of Health database to identify samples of GP–patient encounters in co-located practices (n = 31 700) and practices located apart from the nearest PCC (n = 289 700) over the period 2000–2009. Using Poisson regression analysis and logistic regression analysis, we compared GP test-ordering rates across the two types of practices, controlling for a range of potential confounders.

Main outcome measures: Numbers of tests ordered per encounter; likelihood of ordering one or more tests per encounter.

Results: In unadjusted analyses, GPs in co-located practices ordered more pathology tests than GPs in practices located apart from PCCs (40.3 v 37.0 tests per 100 encounters, P = 0.01) and had a higher likelihood of ordering one or more tests (16.8% v 15.5% of encounters, P < 0.01). After adjusting for other predictors of test ordering, however, neither test-ordering rate (rate ratio, 0.98; 95% CI, 0.93–1.05; P = 0.56) nor likelihood of ordering one or more tests per encounter (odds ratio, 1.01; 95% CI, 0.95–1.07; P = 0.79) differed significantly by co-location status. Sub-analyses within specific test groups and types showed few systematic differences.

Conclusions: Pathology test-ordering rates are not higher in practices co-located with PCCs. To the extent inappropriate commercial influences and relationships exist in the pathology sector, GPs’ test-ordering behaviour may be unaffected.

Pathology services currently account for 14%, or $2 billion per annum, of Medicare expenditure.1 Over the past decade, pathology service costs have increased rapidly in Australia and many other developed countries.2 Nearly 70% of public expenditure on pathology services in Australia goes towards tests ordered by general practitioners.3

Outside hospitals, pathology service delivery in Australia is dominated by a few large companies; it is an oligopoly. Specimens are collected from patients at general practices or pathology collection centres (PCCs) and couriered to central laboratories for testing. More than 80% of PCCs are owned and operated by one of the country’s four major pathology companies.4 Pathology companies compete to place PCCs in the most commercially advantageous locations. Commonly, that will be in or adjacent to busy general practices. The pathology companies then strive to secure and maintain the referral allegiance of their GP neighbours.

Regulators have long worried about these arrangements.5-8 The nub of the policy concern is that the structure of pathology markets, coupled with the close professional relationships that exist between doctors and pathology company staff, may stimulate over-testing.7 In 2007, the federal government introduced new rules aimed at curbing inappropriate influences in the delivery of pathology and imaging services,9 including sham commercial relationships, such as landlord–tenant deals, used to mask “kickbacks” to doctors for referrals. Recent media reports suggest a forthcoming federal government taskforce to investigate claims of bribery and kickbacks in the pathology industry,10 and at least one such allegation is currently being litigated.11

If the pathology industry exerts influence, directly or indirectly, over GPs’ test-ordering practices, that influence would logically be stronger in environments where the two are in regular and close working contact. We compared rates of pathology test ordering by GPs in general practices co-located with PCCs with those of GPs in practices located apart from PCCs. Our hypothesis was that test-ordering rates would be higher among GPs in co-located practices.

Definition and identification of co-located practices

We defined a practice as co-located with a PCC if it occupied the same premises as a PCC, either in a shared suite or in an immediately adjacent suite. As the BEACH program does not collect information about the proximity of practices to PCCs, this was determined by other means. From a publicly available list of all Department of Health and Ageing-approved PCCs and their locations,15 we identified all PCCs located within the metropolitan boundaries16 of Melbourne and Sydney. Between December 2008 and February 2009, we telephoned each of these PCCs and asked for the name and location of the nearest general practice. Hospital-based PCCs were dropped from further consideration. For PCCs associated with specialty medical practices, the standard query about location of the nearest general practice applied. The geographical distance between each PCC and its nearest general practice was then verified via online searches of addresses and by using Google Maps ( Next, for all PCCs that shared a suite with or occupied a suite adjacent to a general practice, we obtained the year in which the co-location was established via a telephone call to the PCC staff and/or the general practice manager.

Statistical analyses

Analyses were conducted at the GP–patient encounter level. The main outcome variables were test-ordering rates (number of pathology tests ordered per encounter, ranging from 0 to 5) and the likelihood of test ordering (a binary variable with a value of 0 if no test was ordered in an encounter and 1 if one or more tests were ordered in an encounter). The independent variable of interest was co-location, a binary variable that distinguished encounters in co-located practices from encounters in practices located apart from PCCs. The relationship between the independent variable and the outcome variables was estimated using Poisson regression analysis (test-ordering rates) and logistic regression analysis (likelihood of test ordering).

In unadjusted analyses, we regressed both outcome measures on the co-location variable and a range of practice, GP, patient and encounter characteristics. To probe the co-location predictor further, we repeated these regressions within each MBS group and test type. Adjusted analyses re-estimated the relationship between each of the outcome variables and co-location in regression models that controlled for all other covariates found to have a significant association with the outcome variables in unadjusted analyses.

Standard error calculations incorporated the single-stage clustered study design according to Kish’s formula.17 We used the statistical software package SAS 9.1.3 (SAS Institute, Cary, NC, USA) for descriptive analyses and Stata 11.0 (Stata Corp, College Station, Tex, USA) for univariate and multivariate analyses.


There were 367 PCCs in Melbourne and 340 PCCs in Sydney, 251 of which were co-located with general practices (126 in Melbourne, 125 in Sydney). The data-matching process identified 317 GPs from co-located practices (31 700 encounters) and 2897 GPs from practices located apart from PCCs (289 700 encounters) from among BEACH participants.

Unadjusted analyses
Co-location with PCC

GPs in co-located practices had higher rates of pathology test ordering than GPs in practices located apart from PCCs (40.3 v 37.0 tests per 100 encounters; P = 0.01) (Box 3). The difference stemmed from a higher probability of ordering one or more tests at encounters in co-located practices (16.8% v 15.5% of encounters; P < 0.01), not from larger numbers of tests when one or more tests were ordered in an encounter (mean of 2.4 tests in both groups; P = 0.35).

Other variables

All of the other variables shown in Box 2 were either significantly associated (P < 0.05), or had one or more categories that were significantly associated, with both test-ordering rates and the likelihood of ordering one or more tests in encounters. Hence, all were included as covariates in the adjusted analyses. In addition, test-ordering rates increased sharply over the study period in both co-located practices and practices located apart from PCCs (Box 4), so dummy variables for each BEACH survey year were included in the adjusted analyses.

Adjusted analyses
Test-ordering rates

The significant association observed in unadjusted analyses between co-location and number of pathology tests ordered per encounter did not hold in an adjusted analysis (rate ratio [RR], 0.98; 95% CI, 0.93–1.05) (Box 5). However, several other GP and practice variables were significantly associated with test-ordering rates, after adjusting for patient characteristics, encounter characteristics and survey year. Test-ordering rates were higher in accredited practices (RR, 1.12; 95% CI, 1.07–1.18), practices with 5–9 and 10–14 GPs, among female GPs (RR, 1.12; 95% CI, 1.08–1.17) and among GPs who worked 11 or more sessions per week (RR, 1.09; 95% CI, 1.01–1.17). On the other hand, test-ordering rates were lower in Sydney than Melbourne (RR, 0.90; 95% CI, 0.86–0.94) and among GPs in age groups above 44 years relative to GPs younger than 35 years.


We found that, although several practice characteristics (location, size, accreditation) and practitioner characteristics (sex, age, sessions per week) were associated with variation in GPs’ pathology test-ordering rates, the existence of a PCC within or beside a general practice was not. Thus, our hypothesis proved incorrect. Regulators who are concerned that undue influences and conflicts of interest in the pathology sector may be skewing GPs’ test-ordering behaviour should draw some comfort from this result.

To our knowledge, this is the first published study of whether doctors who have high levels of daily exposure to private pathology businesses are heavier users of the laboratory services of those businesses. The question has particular salience in the Australian health care system, where the pathology sector is much more heavily for-profit and more tightly integrated into primary care than in countries such as the United Kingdom and Canada.

An analogous body of research is relevant. Many studies have shown that doctors’ contact with the pharmaceutical industry can influence their clinical decision making.18 Repeated visits by sales representatives,19-22 the availability of free drug samples,23,24 and relationships forged through conferences, educational events and consultancy arrangements25,26 have been linked to prescribing patterns. The hypothesised mechanism of action is, of course, the same as the pharmaceutical industry’s rationale for spending vast sums27 on marketing campaigns directed at doctors — namely, doctors who are regularly exposed to information, people, money and events associated with a particular product are more likely to incorporate that product into their clinical activities.

Our analysis found no evidence of such effects arising out of the close relationships between GPs and pathology companies in Australia. One possible explanation for this result is that, in Australia, pathology markets differ from pharmaceutical markets in important respects. Pathology companies sell a defined set of services; those services are relatively homogeneous from company to company; and prices are basically fixed and mostly paid by government (although this may be changing28). This combination of economic factors may make doctors’ demand for pathology services fairly inelastic; it may also force pathology companies to compete on the basis of socially desirable attributes such as test quality, reliability, speed and convenience. In sum, the nature of pathology markets, however aggressive, may not carry the same risks of supplier-induced demand that exist in markets for other health care products, such as pharmaceuticals.

The GP and practice characteristics found to be associated with test-ordering rates in this study largely echo those detected in earlier Australian research. A 1994 study of Medicare data found that rates of test ordering were higher among female GPs and varied according to year of graduation from medical school.29 Previous analyses of BEACH data showed higher rates of test ordering among female GPs and in larger practices, and lower rates among older GPs.30,31 To those recognised associations, our study adds practice accreditation and high workload (11 + sessions per week) as positive predictors; we also found that test-ordering rates were about 10% higher in Melbourne than in Sydney.

A strength of our study is that we used BEACH data, which have important advantages over Medicare data for measuring rates of pathology test ordering. Most notably, the federal government’s “coning” rule for reimbursement confines Medicare data to the three most expensive pathology items ordered in any GP–patient episode of care. The reliability and validity of the BEACH methods have been tested and described elsewhere.32

A limitation of our study is that we used co-location as a marker of the closeness of relationships between GPs and pathology companies and, by inference, the scope for illegal or unethical commercial relationships. This is an excellent marker in theory, but the extent to which it is so in practice is unknown. In addition, we measured the number of pathology tests that GPs ordered, not the clinical appropriateness of those tests.

In summary, we found no evidence that co-location of general practices and PCCs affects GPs’ test-ordering behaviour. From a policy perspective, the result suggests that the convenience of PCC co-locations for patients, particularly patients who have ambulatory problems or lack access to transportation, is not gained at the expense of undue influences on pathology test-ordering behaviour. However, our findings do not close the book on questions about the structure of pathology services in Australia generally, or over-testing in particular. Several recent trends are noteworthy, namely: the spread of GP Super Clinics, portending further integration of primary care and diagnostic services;33 the discontinued agreement between the federal government, pathologists and pathology companies over caps on the growth of pathology services;34 the federal government’s loosening of PCC licensing rules;35 and the looming prospect of larger out-of-pocket pathology costs for patients.28 Together, these developments suggest that the need to better understand drivers of variation in test-ordering behaviour, and what constitutes cost-effective use of pathology services, is even more pressing today than it was when Deeble and Lewis-Hughes sounded the call two decades ago.5

2 Characteristics of study sample (3214 GPs and 321 400 GP–patient encounters)*

General practices

Co-located with pathology collection centre










2–4 GPs


5–9 GPs


10–14 GPs


15 + GPs








< 35 years


35–44 years


45–54 years


55 + years


Sessions per week

< 6




11 +


Country of graduation



United Kingdom, Ireland, New Zealand




Fellow of the RACGP






< 25 years


25–44 years


45–64 years


65 + years


New patient to practice


Health Care Card holder


Repatriation Health Card holder


GP–patient encounters

Medicare item level

Level A


Level B


Level C


Level D


New problems§


Chronic problems§


Type of problem§







General and unspecified






Endocrine, metabolic, nutritional




Female genital






Pregnancy, family planning






Blood, blood forming


Male genital




GP = general practitioner. RACGP = Royal Australian College of General Practitioners. MBS = Medicare Benefits Schedule. * Data are percentage unless otherwise indicated. Total of percentages is greater than 100% due to rounding. Total of percentages is less than 100% due to MBS items not covered by levels and non-MBS funded encounters. § Rate per 100 encounters. Analysed by International Classification of Primary Care (ICPC-2) chapter level.13

  • David M Studdert1
  • Helena C Britt2
  • Ying Pan2
  • Salma Fahridin2
  • Clare F Bayram2
  • Lyle C Gurrin1

  • 1 Melbourne School of Population Health, University of Melbourne, Melbourne, VIC.
  • 2 Family Medicine Research Centre, School of Public Health, University of Sydney, Sydney, NSW.



We thank Adrian Minson and April Mori for research assistance. Paul Monagle and Marie Pirotta helped conceive the study idea and provided valuable comments on an earlier draft of the manuscript. We also thank the GPs who participated in the BEACH program.

Competing interests:

Helena Britt, Ying Pan, Salma Fahridin and Clare Bayram have conducted analysis of problems involving pathology testing on behalf of the Australian Association of Pathology Practices.

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