Stochastic Programming Based Research On Planning And Scheduling For Day Surgery Units

The mode of Day Surgery has been developed among the large hospitals due to its benefits to decrease the length of stay of patients and improve the operational efficiency under the background that the demand for medical service increases rapidly.However,according to our survey,quite few attention was paid to the management of Day Surgery.On one hand,few quantitative analysis has been done so that the planned capacity doesn't match the demand and causing the waste of resource or the lack of capacity.On the other hand,the negative performance,like the idle time,overtime and waiting time,which are influenced by the uncertainty couldn't be controlled.Regarding the issue above,this thesis focus on the multi-level planning and scheduling of the critical resource in day surgery process considering several kinds of uncertainty,aiming to decrease the waste of resource and improve the efficiency.First of all,the optimal process design and optimal layout design were studied based on the Day Surgery Center construction background of a large hospital in Shanghai.The clinical pathway,as well as the outpatient process and management process were considered in the process design.While in the layout design,the objective is to decrease the walking distance of the doctors,nurses and patients.These results were adopted by the hospital.In addition,the data analysis for the duration of candidate surgery was studied by hypothesis testing as the results are important selection criteria for surgery admission and also the foundation of other studies in this thesis.Based on the research above,the resource planning and capacity allocation are studied for the critical facilities of day surgery process.Considering that the planning and allocation are two integrated decision,a joint optimization model was proposed in the form of stochastic optimization to determine the optimal decisions of capacity planning,allocation,and the surgery planning in order to maximize the net rewards under the uncertainty of patients' arrival and surgery duration.In the calculation aspect,the Monte Carlo simulation is used to describe the uncertainty of surgery time and patient arrival.A heuristic algorithm is proposed for the large-scale optimization problem.Numerical results show the efficiency of the proposed model and solution algorithm.Sensitivity analysis is carried out to discuss how the different resource costs,overtime penalties and surgery rewards would affect the optimal decisions.A further study was then performed on the appointment scheduling of day surgery with the purpose of decreasing the waiting time,improving the patients' satisfaction,as well as optimizing the utilization of surgery facilities and decreasing the doctors' overtime.The relative decision,which are surgery allocation,surgery order and surgery start time,were jointly optimized by a stochastic model.The Monte Carlo simulation was then proposed to transfer it to a linear optimization model in order to make it solvable.In addition,a model based on Genetic Algorithm was designed to improve computational efficiency for the large-scale optimization problem.Numerical results show a good property on both accuracy and computational efficiency.The influence of the penalty parameters and surgery quantity on the optimal solution was studied by the sensitivity analysis.At last,the surgery setup and preferences were taken into consideration to reflect the actual situation.Numerical test reveals how they affect the optimal decision.This thesis is based on the actual situation of a large hospital graded 3A in Shanghai.The results and conclusion are then valuable for other hospitals to perform the planning and scheduling of day surgery.