Abstract
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.
Highlights
In China, emergency room residents (EMRs) generally face high working intensity
As a research-oriented hospital, the EMRs of West China Hospital of Sichuan University (WCH) take on the tasks of scientific research, teaching, and instructing students. erefore, the emergency department (ED) in the most of the large public hospitals in the metropolis of China, represented by WCH, is often one of the most stressful, challenging, and high Journal of Healthcare Engineering turnover departments in such hospitals [1, 4]. erefore, in order to reduce the work pressure of EMRs and balance the work and rest time, it is important to arrange the working time of emergency physicians in a scientific way. e effective arrangements for EMRs are helpful to improve the quality of medical service, optimize the management mechanism of the hospital, and alleviate the conflicts between doctors and patients [5]
In the existing research, 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 large public hospitals in China
Summary
In China, emergency room residents (EMRs) generally face high working intensity. It is important to arrange the working shifts of EMRs in a scientific way to balance their work and rest time. 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. 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. Azaiez and Al Sharif [16] established a 0-1 programming model based on the constraints of the hospital regulations (nurses’ skills and numbers) and the nurses’ preferences (arranging night shifts and weekend shifts and avoiding the isolated rest days). Bruni and Detti [18] proposed a mixed integer linear programming model that met the requirements of medical services, management rules, and personal preferences. e Branch-and-Cut procedure was used to obtain the minimization of the number of total shifts and dissatisfied shifts
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