Research On The Methods For Resource Scheduling In Operating Rooms

Operating rooms play decisive role in providing surgical services in hospitals byscheduling various surgical resources. With ever-rising surgery demand nowadays,operating rooms tend to be the bottleneck in the overall surgical process. Scheduling ofoperating room resources has significant impact on the quality and cost of surgicalservices. Operating room scheduling is complicated in practice due to the considerableuncertainty with respect to surgery durations and emergency surgeries, as well as theneed to coordinate the use of multiple surgical resources. Therefore, operating roomscheduling problem is of great importance, both theoretically and practically. Operatingroom scheduling can be divided into two specific problems that are solved sequentiallyin practice: surgical nurse rostering problem; elective surgery and surgical nursescheduling problem. These two problems are studied in depth in this research.Different from deterministic rostering methods, this research considers theuncertainty involved in surgical nurse rostering problem, and accordingly proposes astochastic rostering model that is in the form of stochastic programming. Specifically,the model takes into account the uncertain demand for surgical nurses and incorporatesvarious practical constraints regarding surgical nurse rostering. An almost exact methodis developed to solve the stochastic model by using Monte Carlo simulation and integerprogramming. The convergence property of the method is proved theoretically anddemonstrated numerically. The results of the numerical experiments reveal that betteruse of surgical nurses can be achieved using the stochastic rostering model givenuncertain demand for surgical nurses.In contrast to the two-stage method that schedules elective surgeries and surgicalnurses separately, this research takes into consideration the strong interactions betweenthe surgery and nurse scheduling processes and proposes an exact method and aheuristic method to integrate the scheduling processes. The exact method relies on a0-1integer programming model that schedules elective surgeries and surgical nursessimultaneously and considers multiple important constraints. For large probleminstances, an efficient heuristic method is developed that generates surgery schedulesusing a fast heuristic algorithm and solves the corresponding nurse scheduling problem to global optimality. The heuristic method adopts an iterative structure, in which severalheuristic search procedures are developed to facilitate the search for a good solution.The performance of the exact and heuristic methods is demonstrated through numericalexperiments.The applicability of the proposed methods for operating room scheduling isvalidated using real-life data obtained from general hospitals. Specifically, in order toreduce variability in surgery durations, the sources of variability are studied using amulti-factor analysis of variance, knowledge of which may ultimately be used toimprove elective surgery and surgical nurse scheduling. Besides, the empiricalprobability distribution of the demand for surgical nurses is deduced from real-life datathat further validates the proposed stochastic rostering model.