Chance-constrained admission scheduling of elective surgical patients in a dynamic, uncertain setting

Publication date: Available online 15 July 2019Source: Operations Research for Health CareAuthor(s): Wim Vancroonenburg, Patrick De Causmaecker, Greet Vanden BergheAbstractIn the present contribution, a chance-constrained scheduling model is presented for determining admission dates of elective surgical patients. The admission scheduling model is defined considering a dynamic, stochastic decision-making environment. The primary aim of the model concerns the minimization of operating theatre costs and patient waiting times, while simultaneously avoiding bed shortages at a fixed certainty level through a chance-constrained formulation. This stochastic model is implemented by means of sample average approximation and is solved by a meta-heuristic algorithm. To illustrate the applicability of the model, the approach is used to implement four admission scheduling policies on this dynamic decision-making setting that are evaluated on different criteria in a computational study using simulation. The results show that the stochastic approach is able to account for the uncertainty in patients’ length of stay and surgical procedure duration, enabling it to avoid bed shortages while still optimizing operating theatre costs and patient waiting times.

Source: Operations Research for Health Care - July 16, 2019 Category: Hospital Management Source Type: research