Optimizing community healthcare coverage in remote Liberia

Abstract

Purpose The purpose of this paper is to present a case study describing a collaboration with Last Mile Health, a non-governmental organization, to develop a framework to inform its community healthcare networks in remote Liberia. Design/methodology/approach The authors detail the process of using the unique problem setting and available data to inform modeling and solution approaches. Findings The authors show how the characteristics of the Liberian setting can be used to develop a two-tier modeling framework. Given the operating constraints and remote setting the authors are able to model the problem as a special case of the location-routing problem that is computationally simple to solve. The results of the models applied to three districts of Liberia are discussed, as well as the collaborative process of the multidisciplinary team. Originality/value Importantly, the authors describe how the problem setting can enable the development of a properly scoped model that is implementable in practice. Thus the authors provide a case study that bridges the gap between theory and practice.

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

“…This is more effective than the original variable generation technique proposed by Von Achen et al. (). Using the non‐dominated cycle variables, the supervisor assignment and routing problem is then solved using CPLEX.…”

“…Then, we compare the impact of Model 1 with a generalized version of the two‐step heuristic proposed by Von Achen et al. (2016). Finally, we conduct sensitivity analyses on the key parameters.…”

“…To the best of our knowledge, other than Von Achen et al. (), the LRCP has not been previously studied. Some variants (the LRP and CTP) have been studied and are presented in sections 2.1 and 2.2.…”

Location‐routing problem: a classification of recent research

“…Ceselli et al (2014) presented a double-channel distribution model for drug distribution, while Rabbani et al (2017) discussed the implementation of a MOLRP for the blood supply chain, in order to maximize the potential amount of collected blood and minimize the operational cost. Lastly, VonAchen et al (2016) presented a case study of the community healthcare system, which aimed to develop an LRP model for maximizing the coverage of the healthcare system in remote Liberia. Considering the importance of optimizing the healthcare logistics system, it is expected that more LRP research contribute to this issue by developing and implementing the LRP approach into a relevant case in healthcare logistics.…”

Assessing the factors for humanitarian logistics digital business ecosystem (HLDBE) using a novel integrated correlation coefficient and standard deviation - combined compromise solution (CCSD-CoCoSo) method

“…Thus, complementing each other's effort to address challenges they face. Notable issues not limited to optimisation, sustainability, risks, communication, and decision making employment tools are addressed in such engagements (Bag et al, 2020;Chari et al, 2020;Dufour et al, 2018;Ittmann, 2020;Munyaka & Yadavalli, 2021;Mutebi et al, 2020;Rancourt et al, 2015;Sabri et al, 2019;Taymaz et al, 2020;Villa et al, 2017;VonAchen et al, 2016). Although collaborations are beneficial to their operational success, such motivations are sometimes based on intrinsic or extrinsic benefits the actors gain from such efforts.…”