Research On Optimization Of Medical Technology Inspection Schedule In Large Hospitals

In the various diagnosis and treatment services of the hospital,the examination of the patients through various medical equipment is an indispensable link in the process of treatment of the patients’ condition.The urgency of different types of patients for medical resources is obviously different.At present,large-scale tertiary hospitals in China generally use the traditional mode of medical technical examination,and draw up examination lists from doctors after receiving patients.Then they check register at the examination department,confirm the payment and perform the examination,check the examination in the inspection section,wait for the result of the examination.Finally,the patients return to the doctor’s office for consultation.This traditional examination method does not reasonably consider the inspection process and scheduling problems.The opaque information of appointment queue leads to very low working efficiency of doctors,which affects the efficiency of the use of medical resources in hospitals,and the patient’s long waiting time is common in the experience of seeking medical treatment.In addition,the patient does not know exactly the check-up period and the current queue length.Therefore,the traditional way of appointment examination has been unable to meet the increasing demands on the quality of medical service.It is difficult to improve the efficiency of the use of medical resources because of the late or renegade behavior of miscellaneous patients and the increase of the patients’ demands to do a number of examinations.In order to solve the problems,this thesis proposes the classification of different examination items of out-patient and inpatients based on the actual medical technical examination reservation data and queuing pattern of a large-scale tertiary class A hospital in Tianjin.To obtain the optimal check queuing strategy,based on M/M/1and M/H＿2/1 queueing service models,this thesis aims to minimize the patients’ total waiting cost by introducing the patient’s sense of fairness.The optimization models of segmented reservation mode and mixed reservation mode are constructed and the corresponding optimal scheduling rules are derived and compared with the total waiting time and total waiting cost of patients in the traditional random reservation mode.The results show that the patients’ total waiting time and total waiting costcould be reduced by using piecewise reservation mode or mixed reservation mode under certain conditions.Then,the actual medical technology inspection appointment data of a large-scale top three hospital in Tianjin was selected,and the data was tested by the goodness of fit method.The theoretical results were verified by the actual data,and the segmentation reservation in the reservation check queue model was obtained.Mode and mixed mode patient wait time is lower than random arrival mode.When the patient has a higher degree of perception of unfairness,the segmentation reservation mode can reduce the patient waiting time compared with the hybrid reservation mode,and the hybrid reservation mode is more than the segmentation reservation mode when the patient’s perception of unfairness is low.It is more effective in reducing patient waiting time.Through research and analysis,the hospital administrator can improve the efficiency of the medical technology inspection department.When the number of patients received per day is within the service capacity and the medical resources of the hospital are limited,the patient can be improved by adjusting the order of the patient examination items and queuing problems.The purpose of the average queue time.Solving the problem of long waiting time for patients makes the allocation of resources in the examination department more reasonable.It is instructive for the follow-up study to comprehensively consider the path selection strategy of checking the real-time status of departments and patients,and improving the medical experience of patients and improving the utilization rate of medical facilities in hospitals.