Day surgery appointment scheduling with patient preferences and stochastic operation duration

• Published in: Technology and health care Vol. 29; no. 4; pp. 697 - 708
• Main Authors: Wu, Qianyun, Xie, Naiming, Shao, Yuting
• Format: Journal Article
• Language: English
• Published: Netherlands IOS Press BV 01.01.2021
• Subjects: Algorithms; Genetic algorithms; Hospitals; Multiple objective analysis; Patients; Preferences; Scheduling; Stochastic models; Stochastic programming; Stochasticity; Surgery; Patient preferences; multi-objective genetic algorithm; stochastic operation duration; surgery scheduling; stochastic programming
• ISSN: 0928-7329; 1878-7401
• DOI: 10.3233/THC-192086

Due to its fast service and high utilization, day surgery is becoming more and more important in the medical system. As a result, an effective day surgery scheduling can reasonably release the supply and demand pressure. This paper aims to investigate the day surgery scheduling problem with patient preferences and limited operation room for the sake of increasing operation efficiency and further decreasing surgery costs. A multiple objective stochastic programming model is constructed to seek a satisfactory surgical scheduling for both patients and hospitals under different scenarios. Multi-objective genetic algorithm is designed to solve the model and different scales of scenarios are utilized to test the effectiveness of the algorithm and modeling process. Results show that the proposed model and algorithm can provide a feasible solution for maximizing individual preference of surgeons with surgery date and operation room utilization as well. Patient preference is proposed to be incorporated into day surgery scheduling, and the variability of surgery duration considered to seek a satisfactory surgery scheduling scheme for both patients and hospitals is more in line with the actual hospital situation.