Health service network design under epistemic uncertainty

Abstract

If a health system wants to achieve its strategic goal known as “reducing health inequalities”, making health services available and accessible to all people is an essential prerequisite. Health service network design (HSND) is known as one of the most critical strategic decisions that affects performance of health systems to the great extent. Important decisions such as location of health service providers (i.e. clinics, hospitals, etc.), allocation of patient zones to health service providers and optimal designing of patients flow via the network are some of the main strategic and tactical decisions that should be made when configuring a health service network. On the other hand, coping with uncertainty in data is an inseparable part of strategic and tactical problems. More specifically, the complex structure of health service networks alongside the volatile environment surrounding the health systems would impose a higher degree of uncertainty to the decision makers and health network designers. Among different methods to cope with uncertainty, possibilistic programming approaches are well-applied methods that can handle epistemic uncertainty in parameters.