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Improving the efficiency of scale-up and deployment of community health workers in Mali: A geospatial analysis
Optimising the scale and deployment of community health workers (CHWs) is important for maximizing geographical accessibility of integrated primary health care (PHC) services. Yet little is known about approaches for doing so. We used geospatial analysis to model optimised scale-up and deployment of...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021816/ https://www.ncbi.nlm.nih.gov/pubmed/36962591 http://dx.doi.org/10.1371/journal.pgph.0000626 |
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author | Oliphant, Nicholas P. Sy, Zeynabou Koné, Brehima Berthé, Mohamed Beebe, Madeleine Samake, Moussa Diabaté, Mamoutou Tounkara, Salimata Diarra, Borodjan Diarra, Amadou B. Diawara, Cheickna H. Yakimova, Tsvetana Florisse, Sonia Jackson, Debra Ray, Nicolas Doherty, Tanya |
author_facet | Oliphant, Nicholas P. Sy, Zeynabou Koné, Brehima Berthé, Mohamed Beebe, Madeleine Samake, Moussa Diabaté, Mamoutou Tounkara, Salimata Diarra, Borodjan Diarra, Amadou B. Diawara, Cheickna H. Yakimova, Tsvetana Florisse, Sonia Jackson, Debra Ray, Nicolas Doherty, Tanya |
author_sort | Oliphant, Nicholas P. |
collection | PubMed |
description | Optimising the scale and deployment of community health workers (CHWs) is important for maximizing geographical accessibility of integrated primary health care (PHC) services. Yet little is known about approaches for doing so. We used geospatial analysis to model optimised scale-up and deployment of CHWs in Mali, to inform strategic and operational planning by the Ministry of Health and Social Development. Accessibility catchments were modelled based on travel time, accounting for barriers to movement. We compared geographic coverage of the estimated population, under-five deaths, and plasmodium falciparum (Pf) malaria cases across different hypothetical optimised CHW networks and identified surpluses and deficits of CHWs compared to the existing CHW network. A network of 15 843 CHW, if optimally deployed, would ensure that 77.3% of the population beyond 5 km of the CSCom (community health centre) and CSRef (referral health facility) network would be within a 30-minute walk of a CHW. The same network would cover an estimated 59.5% of U5 deaths and 58.5% of Pf malaria cases. As an intermediary step, an optimised network of 4 500 CHW, primarily filling deficits of CHW in the regions of Kayes, Koulikoro, Sikasso, and Ségou would ensure geographic coverage for 31.3% of the estimated population. There were no important differences in geographic coverage percentage when prioritizing CHW scale-up and deployment based on the estimated population, U5 deaths, or Pf malaria cases. Our geospatial analysis provides useful information to policymakers and planners in Mali for optimising the scale-up and deployment of CHW and, in turn, for maximizing the value-for-money of resources of investment in CHWs in the context of the country’s health sector reform. Countries with similar interests in optimising the scale and deployment of their CHW workforce may look to Mali as an exemplar model from which to learn. |
format | Online Article Text |
id | pubmed-10021816 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-100218162023-03-17 Improving the efficiency of scale-up and deployment of community health workers in Mali: A geospatial analysis Oliphant, Nicholas P. Sy, Zeynabou Koné, Brehima Berthé, Mohamed Beebe, Madeleine Samake, Moussa Diabaté, Mamoutou Tounkara, Salimata Diarra, Borodjan Diarra, Amadou B. Diawara, Cheickna H. Yakimova, Tsvetana Florisse, Sonia Jackson, Debra Ray, Nicolas Doherty, Tanya PLOS Glob Public Health Research Article Optimising the scale and deployment of community health workers (CHWs) is important for maximizing geographical accessibility of integrated primary health care (PHC) services. Yet little is known about approaches for doing so. We used geospatial analysis to model optimised scale-up and deployment of CHWs in Mali, to inform strategic and operational planning by the Ministry of Health and Social Development. Accessibility catchments were modelled based on travel time, accounting for barriers to movement. We compared geographic coverage of the estimated population, under-five deaths, and plasmodium falciparum (Pf) malaria cases across different hypothetical optimised CHW networks and identified surpluses and deficits of CHWs compared to the existing CHW network. A network of 15 843 CHW, if optimally deployed, would ensure that 77.3% of the population beyond 5 km of the CSCom (community health centre) and CSRef (referral health facility) network would be within a 30-minute walk of a CHW. The same network would cover an estimated 59.5% of U5 deaths and 58.5% of Pf malaria cases. As an intermediary step, an optimised network of 4 500 CHW, primarily filling deficits of CHW in the regions of Kayes, Koulikoro, Sikasso, and Ségou would ensure geographic coverage for 31.3% of the estimated population. There were no important differences in geographic coverage percentage when prioritizing CHW scale-up and deployment based on the estimated population, U5 deaths, or Pf malaria cases. Our geospatial analysis provides useful information to policymakers and planners in Mali for optimising the scale-up and deployment of CHW and, in turn, for maximizing the value-for-money of resources of investment in CHWs in the context of the country’s health sector reform. Countries with similar interests in optimising the scale and deployment of their CHW workforce may look to Mali as an exemplar model from which to learn. Public Library of Science 2022-10-19 /pmc/articles/PMC10021816/ /pubmed/36962591 http://dx.doi.org/10.1371/journal.pgph.0000626 Text en © 2022 Oliphant et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Oliphant, Nicholas P. Sy, Zeynabou Koné, Brehima Berthé, Mohamed Beebe, Madeleine Samake, Moussa Diabaté, Mamoutou Tounkara, Salimata Diarra, Borodjan Diarra, Amadou B. Diawara, Cheickna H. Yakimova, Tsvetana Florisse, Sonia Jackson, Debra Ray, Nicolas Doherty, Tanya Improving the efficiency of scale-up and deployment of community health workers in Mali: A geospatial analysis |
title | Improving the efficiency of scale-up and deployment of community health workers in Mali: A geospatial analysis |
title_full | Improving the efficiency of scale-up and deployment of community health workers in Mali: A geospatial analysis |
title_fullStr | Improving the efficiency of scale-up and deployment of community health workers in Mali: A geospatial analysis |
title_full_unstemmed | Improving the efficiency of scale-up and deployment of community health workers in Mali: A geospatial analysis |
title_short | Improving the efficiency of scale-up and deployment of community health workers in Mali: A geospatial analysis |
title_sort | improving the efficiency of scale-up and deployment of community health workers in mali: a geospatial analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021816/ https://www.ncbi.nlm.nih.gov/pubmed/36962591 http://dx.doi.org/10.1371/journal.pgph.0000626 |
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