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Volume 19
Issue 22
10.3390/ijerph192214721
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Article

Improving the Efficiency of Geographic Target Regions for Healthcare Interventions

by
Matthew Tuson
1,*,
Matthew Yap
2,
Mei Ruu Kok
2,
Bryan Boruff
3,4,
Kevin Murray
5,
Alistair Vickery
2,
Berwin A. Turlach
1 and
David Whyatt
2
1
Department of Mathematics and Statistics, The University of Western Australia, Crawley, WA 6009, Australia
2
Medical School, The University of Western Australia, Crawley, WA 6009, Australia
3
UWA School of Agriculture and Environment, The University of Western Australia, Crawley, WA 6009, Australia
4
Department of Geography, The University of Western Australia, Crawley, WA 6009, Australia
5
School of Population and Global Health, The University of Western Australia, Crawley, WA 6009, Australia
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2022, 19(22), 14721; https://doi.org/10.3390/ijerph192214721
Submission received: 26 September 2022 / Revised: 2 November 2022 / Accepted: 7 November 2022 / Published: 9 November 2022
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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 does consider logistical factors, it also suffers from several limitations, including, but not limited to, the requirement to apply two separate software tools, which is burdensome. Given these results, we suggest that the STA could reasonably be applied to help prevent inefficiencies arising due to targeting of interventions using currently available approaches.
Keywords: geographic target regions; healthcare interventions; targeting efficiency; logistical factors; Marxan; MinPatch; Spatial Targeting Algorithm geographic target regions; healthcare interventions; targeting efficiency; logistical factors; Marxan; MinPatch; Spatial Targeting Algorithm

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MDPI and ACS Style

Tuson, M.; Yap, M.; Kok, M.R.; Boruff, B.; Murray, K.; Vickery, A.; Turlach, B.A.; Whyatt, D. Improving the Efficiency of Geographic Target Regions for Healthcare Interventions. Int. J. Environ. Res. Public Health 2022, 19, 14721. https://doi.org/10.3390/ijerph192214721

AMA Style

Tuson M, Yap M, Kok MR, Boruff B, Murray K, Vickery A, Turlach BA, Whyatt D. Improving the Efficiency of Geographic Target Regions for Healthcare Interventions. International Journal of Environmental Research and Public Health. 2022; 19(22):14721. https://doi.org/10.3390/ijerph192214721

Chicago/Turabian Style

Tuson, Matthew, Matthew Yap, Mei Ruu Kok, Bryan Boruff, Kevin Murray, Alistair Vickery, Berwin A. Turlach, and David Whyatt. 2022. "Improving the Efficiency of Geographic Target Regions for Healthcare Interventions" International Journal of Environmental Research and Public Health 19, no. 22: 14721. https://doi.org/10.3390/ijerph192214721

APA Style

Tuson, M., Yap, M., Kok, M. R., Boruff, B., Murray, K., Vickery, A., Turlach, B. A., & Whyatt, D. (2022). Improving the Efficiency of Geographic Target Regions for Healthcare Interventions. International Journal of Environmental Research and Public Health, 19(22), 14721. https://doi.org/10.3390/ijerph192214721

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