Reducing patient-flow delays in surgical suites through determining start-times of surgical cases

•We model a surgery-scheduling system for multiple operating rooms.•We determine surgery starting times under service time uncertainties.•Patient waiting times, idling of OR, and completion times are used for evaluation.•A fuzzy logic based flexible job shop scheduling with time-lag model is used.•Appropriate ratio of operating rooms and PACU resources is examined. A scheduling strategy to determine starting times of surgeries in multiple operating rooms (OR) is presented. The constraints are resource limit of a downstream facility, post-anesthesia care unit (PACU), and the service time uncertainties. Given sets of surgeries that need to be done on a day, this problem is formulated as a flexible job shop model with fuzzy sets. Patient-waitings in the process flow, clinical resource idling, and total completion times are considered for evaluation. This multi-objective problem is solved by a two-stage decision process. A genetic algorithm is used for determining relative order of surgeries in the first stage and definite starting times for all the surgical cases are obtained by a decision-heuristic in the second stage. The resultant schedule is evaluated by a Monte-Carlo simulation. The performance is shown to be better than our previous approach, a simulation based scheduling which already outperforms simple scheduling rules in regional hospitals. Additionally, the ratio of PACU to OR is examined using the proposed scheduling strategy.