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Community Healthcare Network in Underserved Areas: Design, Mathematical Models, and Analysis

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  • Marilène Cherkesly
  • Marie‐Ève Rancourt
  • Karen R. Smilowitz

Abstract

In community health programs implemented in underserved areas, community healthcare workers (CHWs) prevent, diagnose, and treat the most common diseases. To ensure continuous in‐service training of CHWs, some countries have mentored highly skilled CHWs to become supervisors. Designing a network in such a context implies determining the number of CHWs and supervisors, as well as the routing of the supervisors. This can be defined as a location‐routing covering problem (LRCP), a variant of the location‐routing and the covering tour problems. To solve the LRCP, we propose set‐partitioning formulations and a procedure to generate only non‐dominated variables without losing optimality, which also allows to break the symmetry between variables. Finding the most appropriate mathematical model is important to solve real‐life instances, improve the quality of the solution, and reduce the total computation time. Therefore, we develop tools to assist with the design and analysis of a community healthcare network in order to increase health coverage for underserved areas. Results are presented for an application in Liberia, including sensitivity analyses on various parameters and managerial insights.

Suggested Citation

  • Marilène Cherkesly & Marie‐Ève Rancourt & Karen R. Smilowitz, 2019. "Community Healthcare Network in Underserved Areas: Design, Mathematical Models, and Analysis," Production and Operations Management, Production and Operations Management Society, vol. 28(7), pages 1716-1734, July.
    • Handle: RePEc:bla:popmgt:v:28:y:2019:i:7:p:1716-1734
    DOI: 10.1111/poms.13008
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    Cited by:

    1. Arslan, Okan & Kumcu, Gül Çulhan & Kara, Bahar Yetiş & Laporte, Gilbert, 2021. "The location and location-routing problem for the refugee camp network design," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 201-220.
    2. Seokjun Youn & H. Neil Geismar & Michael Pinedo, 2022. "Planning and scheduling in healthcare for better care coordination: Current understanding, trending topics, and future opportunities," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4407-4423, December.
    3. Vatsa, Amit Kumar & Jayaswal, Sachin, 2021. "Capacitated multi-period maximal covering location problem with server uncertainty," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1107-1126.
    4. Imran Ali & Devika Kannan, 2022. "Mapping research on healthcare operations and supply chain management: a topic modelling-based literature review," Annals of Operations Research, Springer, vol. 315(1), pages 29-55, August.
    5. De Boeck, Kim & Decouttere, Catherine & Jónasson, Jónas Oddur & Vandaele, Nico, 2022. "Vaccine supply chains in resource-limited settings: Mitigating the impact of rainy season disruptions," European Journal of Operational Research, Elsevier, vol. 301(1), pages 300-317.
    6. Harwin De Vries & Lisa E. Swinkels & Luk N. Van Wassenhove, 2021. "Site Visit Frequency Policies for Mobile Family Planning Services," Production and Operations Management, Production and Operations Management Society, vol. 30(12), pages 4522-4540, December.
    7. Jon M. Stauffer & Manoj Vanajakumari & Subodha Kumar & Theresa Mangapora, 2022. "Achieving equitable food security: How can food bank mobile pantries fill this humanitarian need," Production and Operations Management, Production and Operations Management Society, vol. 31(4), pages 1802-1821, April.

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