Elective surgery scheduling under uncertainty in demand for intensive care unit and inpatient beds during epidemic outbreaks.

ABSTRACT: Amid the epidemic outbreaks such as COVID-19, a large number of patients occupy inpatient and intensive care unit (ICU) beds, thereby making the availability of beds uncertain and scarce. Thus, elective surgery scheduling not only needs to deal with the uncertainty of the surgery duration and length of stay in the ward, but also the uncertainty in demand for ICU and inpatient beds. We model this surgery scheduling problem with uncertainty and propose an effective algorithm that minimizes the operating room overtime cost, bed shortage cost, and patient waiting cost. Our model is developed using fuzzy sets whereas the proposed algorithm is based on the differential evolution algorithm and heuristic rules. We set up experiments based on data and expert experience respectively. A comparison be

SUBMITTER: Dai Z 

PROVIDER: S-EPMC9742073 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature