Study on nurses scheduling based on multi-objective integer programming model in COVID-19 pandemic
10.3760/cma.j.cn111325-20210301-00161
- VernacularTitle:基于多目标整数规划模型的新型冠状病毒肺炎疫情期间护理人员排班研究
- Author:
Yalan LIU
1
;
Li YAN
;
Qingjie YI
;
Man MU
;
Yulin XIA
Author Information
1. 重庆大学附属三峡医院/重庆三峡中心医院质控部 404000
- Keywords:
Health manpower;
COVID-19;
Scheduling model;
Multi-objective;
Soft constraints;
Hard constraints
- From:
Chinese Journal of Hospital Administration
2021;37(7):591-594
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish a scientific and reasonable nurse scheduling model for ward nursing during COVID-19, to achieve collaborative and efficient scheduling of manpower and materials, and to provide an algorithm basis for the computerized scheduling as well as references for optimizing manpower scheduling in public health emergencies.Methods:The qualitative interview method was used to learn the challenges in nursing manpower scheduling at designated hospitals. In view of the nursing scheduling in the mild case wards during the pandemic and the premise of meeting the needs of different shift types and patient care, the goal was set as minimizing the consumption of nursing human resources and protective equipments. The objective functions, constraints and corresponding parameters were established. A multi-objective integer programming model was established by MATLAB software for solution by CPLEX solver.Results:Two objective functions, three hard constraints, two soft constraints and corresponding parameters were established. Calculations by the model so established found that a 28-day period requires at least 62 nurses, and at least 52 nurses in the contaminated wards, including 7 nurses in the department of intensive care, the infectious and the respiratory wards respectively. This number could meet in general the needs of epidemic care. In comparison, the manual scheduling of the mild care wards during the pandemic in February 2020 needed at least 69 nurses, and 61 in the contaminated wards, yet with a failure to meet all constraints.Conclusions:The model can solve the scheduling challenges in public health emergencies, namely numerous shift types, different nursing needs in different types of shifts, and complex staff structure.Furthermore, the model can save manpower and materials, serving a useful reference for manpower scheduling.
