Evidence map›Paper›PMID 24005003›Full record

ArticleBMC health services research2013

General practitioner (family physician) workforce in Australia: comparing geographic data from surveys, a mailing list and medicare.

Soumya Mazumdar, Paul Konings, Danielle Butler, Ian Stewart McRae

Abstract readComparative Study
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
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  5. Article
  6. Article
  7. Identifying the Uncertainty in Physician Practice Location through Spatial Analytics and Text Mining.International journal of environmental research and public health · 2016
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Soumya MazumdarAPHCRI, Australian National University, Building 63, Cnr Mills and Eggleston Rds, Canberra, ACT 0200, Australia. soumyamazumdar@yahoo.com.
Paul Konings
Danielle Butler
Ian Stewart McRae

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AustraliaGeneral PractitionersGeographyHealth Care SurveysHealth Services AccessibilityHumansNational Health ProgramsPostal ServiceRural Population

Identifiers

PMID24005003
PMCPMC3766700

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.