ArticleBMC health services research2013
General practitioner (family physician) workforce in Australia: comparing geographic data from surveys, a mailing list and medicare.
Article in BMC health services research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
9 citing papers in PubMed.
- Impact of family doctor system on diabetic patients with distinct service utilisation patterns: a difference-in-differences analysis based on group-based trajectory modelling.BMJ global health · 2024Article
- Rural general practitioners have different personal and professional trajectories from those of their urban colleagues: a case-control study.BMC medical education · 2023Article
- Association of individual-socioeconomic variation in quality-of-primary care with area-level service organisation: A multilevel analysis using linked data.Journal of evaluation in clinical practice · 2023Article
- Impact of the family doctor system on the continuity of care for diabetics in urban China: a difference-in-difference analysis.BMJ open · 2023Article
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- Article
- Identifying the Uncertainty in Physician Practice Location through Spatial Analytics and Text Mining.International journal of environmental research and public health · 2016Article
- Sociodemographic and health characteristics, rather than primary care supply, are major drivers of geographic variation in preventable hospitalizations in Australia.Medical care · 2015Article
- A brief report on Primary Care Service Area catchment geographies in New South Wales Australia.International journal of health geographics · 2014Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGood quality spatial data on Family Physicians or General Practitioners (GPs) are key to accurately measuring geographic access to primary health care. The validity of computed associations between health outcomes and measures of GP access such as GP density is contingent on geographical data quality. This is especially true in rural and remote areas, where GPs are often small in number and geographically dispersed. However, there has been limited effort in assessing the quality of nationally comprehensive, geographically explicit, GP datasets in Australia or elsewhere.Our objective is to assess the extent of association or agreement between different spatially explicit nationwide GP workforce datasets in Australia. This is important since disagreement would imply differential relationships with primary healthcare relevant outcomes with different datasets. We also seek to enumerate these associations across categories of rurality or remoteness.
methodWe compute correlations of GP headcounts and workload contributions between four different datasets at two different geographical scales, across varying levels of rurality and remoteness.
resultsThe datasets are in general agreement with each other at two different scales. Small numbers of absolute headcounts, with relatively larger fractions of locum GPs in rural areas cause unstable statistical estimates and divergences between datasets.
conclusionIn the Australian context, many of the available geographic GP workforce datasets may be used for evaluating valid associations with health outcomes. However, caution must be exercised in interpreting associations between GP headcounts or workloads and outcomes in rural and remote areas. The methods used in these analyses may be replicated in other locales with multiple GP or physician datasets.
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