Data-Driven Hospital Surgery Scheduling Optimization

Abstract

With the deepening reform of the medical system, major hospitals have begun to pay attention to the research on the optimization of medical resource allocation, and seek ways to improve patient satisfaction and reduce hospital operating costs. This paper takes data as the center, collects data through on-site investigation, and analyzes the scheduling problem of the current hospital operating room by using surgical scheduling knowledge and business flow chart. Combining the constraints and the actual situation of the hospital, a multi-objective mixed integer programming model with the lowest operating room operating cost and the highest patient satisfaction was established, and the optimal solution was obtained using Lingo software. The optimization results were verified by FlexsimHC simulation software, and the effects before and after the optimization of the surgical scheduling were compared. The research results provided a basis for optimizing the operation schedule, reducing the operating cost of the operating room and improving patient satisfaction, and established an event data-driven analysis paradigm for operating room scheduling optimization.