Evidence map›Paper›PMID 36429437›Full record

ArticleInternational journal of environmental research and public health2022

Improving the Efficiency of Geographic Target Regions for Healthcare Interventions.

Matthew Tuson, Matthew Yap, Mei Ruu Kok, Bryan Boruff, Kevin Murray, Alistair Vickery, Berwin A Turlach, David Whyatt

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Trial
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

8 authors.

Matthew TusonDepartment of Mathematics and Statistics, The University of Western Australia, Crawley, WA 6009, Australia.ORCID 0000-0002-3135-3672
Matthew YapMedical School, The University of Western Australia, Crawley, WA 6009, Australia.ORCID 0000-0002-5097-3893
Mei Ruu KokMedical School, The University of Western Australia, Crawley, WA 6009, Australia.
Bryan BoruffUWA School of Agriculture and Environment, The University of Western Australia, Crawley, WA 6009, Australia.ORCID 0000-0001-6693-0671
Kevin MurraySchool of Population and Global Health, The University of Western Australia, Crawley, WA 6009, Australia.ORCID 0000-0002-8856-6046
Alistair VickeryMedical School, The University of Western Australia, Crawley, WA 6009, Australia.
Berwin A TurlachDepartment of Mathematics and Statistics, The University of Western Australia, Crawley, WA 6009, Australia.ORCID 0000-0001-8795-471X
David WhyattMedical School, The University of Western Australia, Crawley, WA 6009, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Appropriate prioritisation of geographic target regions (TRs) for healthcare interventions is critical to ensure the efficient distribution of finite healthcare resources. In delineating TRs, both 'targeting efficiency', i.e., the return on intervention investment, and logistical factors, e.g., the number of TRs, are important. However, existing approaches to delineate TRs disproportionately prioritise targeting efficiency. To address this, we explored the utility of a method found within conservation planning: the software Marxan and an extension, MinPatch ('Marxan + MinPatch'), with comparison to a new method we introduce: the Spatial Targeting Algorithm (STA). Using both simulated and real-world data, we demonstrate superior performance of the STA over Marxan + MinPatch, both with respect to targeting efficiency and with respect to adequate consideration of logistical factors. For example, by design, and unlike Marxan + MinPatch, the STA allows for user-specification of a desired number of TRs. More broadly, we find that, while Marxan + MinPatch

Indexed as

Conservation of Natural ResourcesHealth FacilitiesDelivery of Health Caregeographic target regionshealthcare interventionslogistical factorsMarxanMinPatchSpatial Targeting Algorithmtargeting efficiency

Identifiers

PMID36429437
PMCPMC9691133

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.