Evidence map›Paper›PMID 34852021›Full record

ArticlePloS one2021

Examining area-level variation in service organisation and delivery across the breadth of primary healthcare. Usefulness of measures constructed from routine data.

D C Butler, L R Jorm, S Larkins, J Humphreys, J Desborough, K J Korda

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In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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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

6 authors.

D C ButlerResearch School of Population Health, Australian National University, Canberra, Australia.ORCID 0000-0003-4870-4544
L R JormCentre for Big Data Research in Health, University of New South Wales, Kensington, Australia.
S LarkinsAnton Breinl Research Centre for Health Systems Strengthening, James Cook University, Townsville, Australia.ORCID 0000-0002-7561-3202
J HumphreysSchool of Rural Health, Monash University, Melbourne, Australia.
J DesboroughResearch School of Population Health, Australian National University, Canberra, Australia.
K J KordaResearch School of Population Health, Australian National University, Canberra, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAustralia has a universal healthcare system, yet organisation and delivery of primary healthcare (PHC) services varies across local areas. Understanding the nature and extent of this variation is essential to improve quality of care and health equity, but this has been hampered by a lack of suitable measures across the breadth of effective PHC systems. Using a suite of measures constructed at the area-level, this study explored their application in assessing area-level variation in PHC organisation and delivery.

methodsRoutinely collected data from New South Wales, Australia were used to construct 13 small area-level measures of PHC service organisation and delivery that best approximated access (availability, affordability, accommodation) comprehensiveness and coordination. Regression analyses and pairwise Pearson's correlations were used to examine variation by area, and by remoteness and area disadvantage.

resultsPHC service delivery varied geographically at the small-area level-within cities and more remote locations. Areas in major cities were more accessible (all measures), while in remote areas, services were more comprehensive and coordinated. In disadvantaged areas of major cities, there were fewer GPs (most disadvantaged quintile 0.9[SD 0.1] vs least 1.0[SD 0.2]), services were more affordable (97.4%[1.6] bulk-billed vs 75.7[11.3]), a greater proportion were after-hours (10.3%[3.0] vs 6.2[2.9]) and for chronic disease care (28%[3.4] vs 17.6[8.0]) but fewer for preventive care (50.7%[3.8] had cervical screening vs 62.5[4.9]). Patterns were similar in regional locations, other than disadvantaged areas had less after-hours care (1.3%[0.7] vs 6.1%[3.9]). Measures were positively correlated, except GP supply and affordability in major cities (-0.41, p < .01). IMPLICATIONS: Application of constructed measures revealed inequity in PHC service delivery amenable to policy intervention. Initiatives should consider the maldistribution of GPs not only by remoteness but also by area disadvantage. Avenues for improvement in disadvantaged areas include preventative care across all regions and after-hours care in regional locations.

Indexed as

AdolescentAdultAgedCervix UteriChronic DiseaseFemaleGeographyHealth Services AccessibilityHumansMiddle AgedNew South WalesOrganizationsPrimary Health CareRegression Analysis

Identifiers

PMID34852021
PMCPMC8635352

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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.