A simulation-optimization approach for the surgery scheduling problem: a case study considering stochastic surgical times

Abstract

This work studies the scheduling of elective procedures, with stochastic durations, in surgery rooms. Given a set of rooms with limited availability and a set of procedures, it must be decided in which room and when each procedure will be performed. The problem's objectives are to maximize the use of the operating rooms and to minimize the delays in starting the scheduled surgeries. A simulation-optimization approach is proposed. First, procedures' durations are modeled as random variables and a set of test percentiles (i.e. it is assumed that all surgeries will last as many minutes as the 75th percentile of its probability density function) is selected. Subsequently, using these durations as a parameter, a greedy randomized adaptive search procedure (GRASP) is run. Consequently, as many solutions as selected test percentiles are generated. Finally, a Monte Carlo simulation is used to estimate three indicators: i) rooms utilization, ii) percentage of surgeries that had delays, and iii) average delay time of scheduled surgeries. The technique was tested by solving the elective procedures scheduling problem in a high-complexity hospital in Bogota. This hospital has 19 operating rooms and 35,000 surgeries performed annually. Currently, the scheduling process is manual. The simulation-optimization proposed approach allowed to determine the relation between utilization rate and delays in the service. As the occupation percentage increases, delay times also augment, implying a reduction of the service level. An average reduction of 5% in delay times entails a reduction between 3% and 9% of operating room occupancy.

Operating Room Scheduling Optimization Based on a Fuzzy Uncertainty Approach and Metaheuristic Algorithms

“…Constraint (15) completes constraints (7) and (8). Constraint (16) states that if patient i' receives treatment sooner than patient i and patient i is in the queue before patient i', the time of receiving treatment for patient i is longer than patient i', and constraint (17) is in contradiction to constraint (16). In constraint (18), considering the non-linearity of the model, it is required to transform the variable to make the model linear.…”

“…Scheduling surgical operations, including sequencing surgeries, allocating resources, and determining start times, is a complicated task for the medical center manager [15]. The problem of operating room planning and scheduling seeks to propose a solution to reduce costs, increase the efficiency of operating room utilization, and attain other related goals [16]. Moreover, one of the main applications of operations research in health systems management is the improvement of resources allocation mechanism [17].…”

Opportunities for Simulation-Based Optimization in a Hospital Environment

“…Therearemanyresearcherswhohavedealtwiththesimulation-basedoptimizationofhospitalsand operating rooms. Díaz-López et al (2018)…”

A multi-criteria decision-making integrated approach for identifying and ranking factors affecting the quality of cosmetic surgery clinic services

“…Each hospital and specialized medical clinic has a different ability to provide medical services due to the difference in the type of medical equipment and the ability of its treatment staff (Samartzis and Talias, 2020). Additionally decision-making processes in healthcare services have become more complex due to the balance and harmony between quality and efficiency (Brailsford and Vissers, 2011, Hulshof et al, 2012. and Díaz-López et al, 2018 .…”