Introducing health gains in location-allocation models: A stochastic model for planning the delivery of long-term care

Mini EURO Conference on Improving Healthcare: new challenges, new approaches

物理学;医药卫生

Cardoso, T.^1 ; Oliveira, M.D.^1 ; Barbosa-Póvoa, A.^1 ; Nickel, S.^2

Centre for Management Studies, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal^1

Institute of Operations Research, Karlsruhe Institute of Technology, Karlsruhe, Germany^2

关键词: Conflicting objectives;    Cost-effective investment;    Epsilon-constraint method;    Health-care system;    Location allocation;    Location-allocation models;    Mixed integer linear programming model;    Multiservice network;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/616/1/012007/pdf
DOI  :  10.1088/1742-6596/616/1/012007

学科分类：卫生学

来源: IOP

【 摘 要 】

Although the maximization of health is a key objective in health care systems, location-allocation literature has not yet considered this dimension. This study proposes a multi-objective stochastic mathematical programming approach to support the planning of a multi-service network of long-term care (LTC), both in terms of services location and capacity planning. This approach is based on a mixed integer linear programming model with two objectives - the maximization of expected health gains and the minimization of expected costs - with satisficing levels in several dimensions of equity - namely, equity of access, equity of utilization, socioeconomic equity and geographical equity - being imposed as constraints. The augmented Ε-constraint method is used to explore the trade-off between these conflicting objectives, with uncertainty in the demand and delivery of care being accounted for. The model is applied to analyze the (re)organization of the LTC network currently operating in the Great Lisbon region in Portugal for the 2014-2016 period. Results show that extending the network of LTC is a cost-effective investment.