Choice-driven location-allocation model for healthcare facility location problem

Kyosang Hwang (), Tooba Binte Asif () and Taesik Lee ()
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Kyosang Hwang: KAIST
Tooba Binte Asif: KAIST
Taesik Lee: KAIST

Flexible Services and Manufacturing Journal, 2022, vol. 34, issue 4, No 9, 1040-1065

Abstract: Abstract Improving access to care in medically under-served areas (MUA) is an important task for public health policy in many countries. A lack of access to care in MUAs is often addressed by establishing new service providers, which improves the accessibility in those regions in a geographic sense. However, the geographic accessibility is only a necessary condition for relieving the regions from being under-served; new service providers must be sufficiently attractive for care consumers to use so that the new establishment effectively translates to actual improvement in accessibility to care in the MUAs. In this paper, we first develop a location-allocation model for healthcare facilities that incorporates a choice model to represent care consumers’ preferences and choice decisions on the care facilities. Then we expand the model such that some of the attribute variables in the consumer utility function can be handled as decision variables in the location-allocation optimization. Thus, the proposed model determines the attributes variables of open facilities as well as their locations. Utility of the proposed model is demonstrated by using the Korea’s MUA support program for perinatal care.

Keywords: OR in health services; Facility location problem; Discrete choice model; Perinatal care service network (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10696-021-09441-8

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