A healthcare facility location problem for a multi-disease, multi-service environment under risk aversion

This paper presents a stochastic optimisation model for locating walk-in clinics for mobile populations in a network. The walk-in clinics ensure a continuum of care for the mobile population across the network by offering a perpetuation of services along the transportation lines, and also establishi...

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Bibliographic Details
Published in:Socio-economic planning sciences 2020-09, Vol.71, p.100755, Article 100755
Main Authors: Taymaz, S., Iyigun, C., Bayindir, Z.P., Dellaert, N.P.
Format: Article
Language:English
Subjects:
Clinics
Conditional-value-at-risk
Continuum of care
Facility location with coverage
Health care industry
Health services
Humanitarian logistics
Perpetuation
Quality of care
Risk
Risk aversion
Stochastic models
Stochastic programming
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Summary:This paper presents a stochastic optimisation model for locating walk-in clinics for mobile populations in a network. The walk-in clinics ensure a continuum of care for the mobile population across the network by offering a perpetuation of services along the transportation lines, and also establishing referral systems to local healthcare facilities. The continuum of care requirements for different diseases is modelled using coverage definitions that are designed specifically to reflect the adherence protocols for services for different diseases. The risk of not providing the required care under different realisations of health service demand is considered. In this paper, for a multi-disease, multi-service environment, we propose a model to determine the location of roadside walk-in clinics and their assigned services. The objective is to maximise the total expected weighted coverage of the network subject to a Conditional-Value-at-Risk (CVaR) measure. This paper presents developed coverage definitions, the optimisation model and the computational study carried out on a real-life case in Africa. •Risk-averse stochastic model to locate clinics for mobile populations is proposed.•Developed novel coverage definitions reflect problem nature's genuine requirements.•Conditional-Value-at-Risk measure allows control over uncertainties in demand.•Empirical evidence supporting the model is provided from real-life African case.
ISSN:0038-0121
1873-6041
DOI:10.1016/j.seps.2019.100755