Flexible Appointment Decision Research With Density Load Arrival

With the rapid society development and the living quality improvement,the health care needs increase as well.In healthcare services,people’s medical service needs cannot be met fully due to the imbalanced matching between demands and resources.This problem is more serious because of unscientific management.In most medium-sized cities in China,the hospitals generally have morning rush hour and patients have to wait long time for service.It all of which is a huge hit to hospital service quality.When the density load exceeds the server processing capacity,the next periods’ load will be squeezed,which may cause chain reaction and lead to large number loads waiting for a long time.It is the root of patient queuing problem.This paper puts forward the solution with theoretical model based on industrial engineering.The research work of this paper is summarized as follows:(1)Firstly,the simulation study on appointment decision considering density arrival load is explored and the appropriate appointment strategy is studied under different scenarios.The scenarios data are collected through field survey and historical data statistics.Totally 33 groups experiment with 9 appointment rules,3 difference density loads and 11 groups of walk-in/appointment rates are set in the simulation.The average patient waiting time is set as the major evaluation index.The coupling relationship among appointment rule-dense loads-appointment rate are analyzed and studied,and the optimal solution in each scenario is obtained.At last,the basic cognition and improvement suggestions on the appointment system design and the determining of appointment rules under dense arrival load are summarized.(2)Secondly,the idea of load balancing is introduced and a multi-objective optimization of flexible outpatient scheduling decision-making method is proposed especially for current domestic medical institutions normally facing dense arrival.According to the actual load distribution,the flexible appointment can allocate loads more balanced by adjusting the total load in each period.The optimal scheduling scheme under each application scenario is determined by the multi-objective grey target decision model.The approach is compared to others research with numerical experiments.The results show this model can effectively reduce the waiting time by as much as 77.2%.In application analysis,this model can improve the effective resource utilization rate by 66.7% and reduce the resource sensitivity.(3)Lastly,the proposed flexible appointment decision approach is verified by the simulation application to target hospital.The discrete event simulation model is built based on the historical data collected in the target cooperated hospital.The multiple experimental groups and the evaluation indexes are explored to verify the effectiveness of the proposed flexible appointment decision approach.The calculated optimal appointment strategy decision for each experiment is evaluated and compared with hospital data.The experimental results show,the flexible appointment model can effectively improve hospital operation,and improve resource utilization and patient’s satisfaction.In summary,the appointment problem under dense arrival load is studied in this paper.The load balancingbased flexible appointment model is put forward for domestic hospitals normally with mixed service demand.The simulation experiments are used to test the proposed model.The research finding can provide the case and theoretical support for the hospital management decisions,and especially can give certain reference for other similar systems also with dense load.