Simulation Based Optimization For Staffing And Allocation Problem In Emergency Department

As well known that, emergency department (ED) is a complex unit of a hospital, which has many characteristics, such as many patients in it and having a heavy rescue. The patients who walk in the ED always want to get the treatment in time. However, most hospital ED budgets did not catch up with the demand for ED services made by growing populations. So the reorganization plan needs to first address staffing issues such as determining the correct size of the workforce and its work shift allocation. The quality of ED services has a close relationship with all the medicals’ operations. Because of the traditional nurse allocation model has been difficult to catch up with the patients demand, and patient overcrowding can not only affect the patients’ psychological of treatment, but also can reduce medicals’ quality of services. So, adding additional working capacity to some needy areas has been one of the most important problems in the field of health care.In this paper, firstly, a survey and a depth analysis of ED overall operations have been established, and then established a patient-centered simulation model, which took all the ED medical staffs on as the object used ServiceModel simulation software. It simulated the patients’ length of stay (LOS) in the ED system under different work shift allocations of ED medical staffs. After that, we used the radial basis function neural network to find the relationship between the configuration parameters of the ED resources and the performance. Our main work here was to help the ED managers to design the optimal configuration of resources with the objective minimize patients LOS and minimize the overall costs separately.Then in terms of its limitation, namely it could not satisfy the objective of minimize the patients’ length of stay (LOS) in the ED system and leveling the resource utilization as much as possible within the limited resources, an iterative heuristic algorithm called simulation work shift allocation algorithm (SWSAA) combined simulation and optimization models that scheduled the work shifts of the ED resources were established. To accomplish the above works, firstly, the definition of delay factor was proposed in order to select the bottleneck resource. And then a work shift allocation optimization model which designed by me was used to the bottleneck resource. It was used to determine the starting time of each of the work shifts of the bottleneck resources in an attempt to reduce the gaps between the required number of resource units and the available number of resource units. In addition, according to the multi-skilled scene, an improved algorithm which called simulation multi-skilled work shift allocation algorithm (SMWSAA) was established, which allowed transfer of time blocks within similar groups of resources.