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In China, emergency room residents (EMRs) generally face high working intensity. It is particularly important to arrange the working shifts of EMRs in a scientific way to balance their work and rest time. However, in existing studies, most of the scheduling models are based on the individual doctor or nurse as a unit, less considering the actuality of operation and management of emergency department (ED) in large public hospitals in China. Besides, the depiction of the hard and soft constraints of EMR scheduling in China is insufficient. So in order to obtain the scientific and reasonable scheduling shifts, this paper considers various management rules in a hospital, physicians’ personal preferences, and the time requirements of their personal learning and living and takes the minimum deviation variables from the soft constraints as the objective function to construct a mixed integer programming model with the doctor group as the scheduling unit. The analytic hierarchy process (AHP) is used to determine the weights of deviation variables. Then, IBM ILOG CPLEX 12.8 is used to solve the model. The feasibility and effectiveness of the scheduling method are verified by the actual case from West China Hospital of Sichuan University. The scheduling results can meet the EMRs’ flexible work plans and the preferences of the doctor teams for the shifts and rest days. Compared with the current manual scheduling, the proposed method can greatly improve the efficiency and rationality of shift scheduling. In addition, the proposed scheduling method also provides a reference for EMR scheduling in other China’s high-grade large public hospitals.

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Operating rooms (ORs) play a key role in hospitals. The purpose is to improve the efficiency of operating room to analyze the surgical process. The results of optimizing the process will greatly improve the utilization of operating room. Considering the operating room involves a variety of resources, simulation has its unique advantage on solving this problem. In this paper, to find out the bottleneck of the operating room and then put forward the improvement opinions in the future. we build a simulation model and take the patient's process as the research target and set up the relevant cost parameters which based on the latest simulation platform-SIMIO. The simulation data and the logic underline are studied, and the case is presented.

This paper studies the problem of appointment scheduling for two CT scanners one of which typically provides service to emergency patients, whose demands are generated during the day and must be served as soon as possible. The other provides service to scheduled outpatients who arrive based on an appointment schedule with some randomness due to no-shows and nonscheduled inpatients which arrive at random. The capacity management problem facing the managers of CT-scanners is to dynamically decide which appointment requests to accept and how to schedule the three kinds of patients on the two pointed facilities to maximize total revenue. So the Markov Decision Process model was built and an appointment rule was put forward in this paper. Keywordsdiagnostic facility; CT-scanner; Markov decision processes; revenue managementI.978-1-4799-3134-7/14/$31.00 ©2014 IEEE