In recent years, there are many studies on scheduling methods of patient flow, nurse scheduling, bed allocation, operating room scheduling and other problems, but there is no report on the research methods of how to plan ward allocation from a more macroscopic perspective.
The obstetric wards are divided into observation ward, cesarean section ward and natural delivery ward according to lean thinking. CPLEX is used to solve the mixed integer programming problem of ward allocation. In R software, multivariate GLM regression model is used to analyze the influence of each factor on patient flow.
The maximum patient flow of each case was obtained by CPLEX, which was 19-25% higher than which of patients without refinement, stratification and planning. GLM regression analysis was carried out on the above data, and the positive and negative correlation factors were obtained.
According to lean thinking, obstetric wards are divided into three types of wards. Obstetricians and midwives work more efficiently and get more rest time. Pregnant women also enjoy more detailed medical services. By modeling the delivery ward allocation problem as a mixed integer programming problem, we can improve the capacity of the service in obstetric hospitals from a macro perspective. Through GLM regression model analysis, it is conducive to improve the obstetric hospital capacity from the perspective of positive and negative correlation factors.