TY - JOUR
T1 - A healthcare facility location problem for a multi-disease, multi-service environment under risk aversion
AU - Taymaz, S.
AU - Iyigun, C.
AU - Bayindir, Z.P.
AU - Dellaert, N.P.
PY - 2020/9
Y1 - 2020/9
N2 - 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.
AB - 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.
KW - Conditional-value-at-risk
KW - Continuum of care
KW - Facility location with coverage
KW - Humanitarian logistics
KW - Stochastic programming
UR - http://www.scopus.com/inward/record.url?scp=85088608476&partnerID=8YFLogxK
U2 - 10.1016/j.seps.2019.100755
DO - 10.1016/j.seps.2019.100755
M3 - Article
AN - SCOPUS:85088608476
VL - 71
JO - Socio-Economic Planning Sciences
JF - Socio-Economic Planning Sciences
SN - 0038-0121
M1 - 100755
ER -