Research on outpatient capacity planning combining lean thinking and integer linear programming

Author:

hua Li,Dongmei Mu,Xinyu Yang,Xinyue Zhang,Shutong Wang,Dongxuan Wang,Hao Peng,Ying Wang

Abstract

Abstract Background The size and cost of outpatient capacity directly affect the operational efficiency of a whole hospital. Many scholars have faced the study of outpatient capacity planning from an operations management perspective. Objective The outpatient service is refined, and the quantity allocation problem of each type of outpatient service is modeled as an integer linear programming problem. Thus, doctors’ work efficiency can be improved, patients’ waiting time can be effectively reduced, and patients can be provided with more satisfactory medical services. Methods Outpatient service is divided into examination and diagnosis service according to lean thinking. CPLEX is used to solve the integer linear programming problem of outpatient service allocation, and the maximum working time is minimized by constraint solution. Results A variety of values are taken for the relevant parameters of the outpatient service, using CPLEX to obtain the minimum and maximum working time corresponding to each situation. Compared with no refinement stratification, the work efficiency of senior doctors has increased by an average of 25%. In comparison, the patient flow of associate senior doctors has increased by an average of 50%. Conclusion In this paper, the method of outpatient capacity planning improves the work efficiency of senior doctors and provides outpatient services for more patients in need; At the same time, it indirectly reduces the waiting time of patients receiving outpatient services from senior doctors. And the patient flow of the associate senior doctors is improved, which helps to improve doctors’ technical level and solve the problem of shortage of medical resources.

Funder

the education department of Jilin Province

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Health Policy,Computer Science Applications

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