Design And Implementation Of Medical Service Performance Evaluation System Based On Fuzzy Evaluation Model

Medical service quality is closely related to people living standards,but there still exist some problems,up to now,in the design of medical service performance evaluation system in our country.Such as not accurate enough to establish the system of evaluation index.The evaluation process,lack of objectivity,is interfered by subjective factors.The imperfect function of performance evaluation system leads to low efficiency.Therefore,this thesis designs and implements a medical service performance evaluation system based on fuzzy evaluation model.This system solves the problems and improve work efficiency.Through reading a large number of domestic and foreign literature in this field of research status is sorted out,then an evaluation index system consisting of three first-level indicators and nine second-level indicators was established by combining Delphi expert consulting method.Entropy weight method,fuzzy comprehensive evaluation model and K-means clustering algorithm were combined as the evaluation model of medical service performance.The first page data of the inpatient medical records of X Hospital in 2019 were collected,and the relevant data sets were obtained through disease grouping and sorting using CN-DRGS(Diagnosis Related Groups).The weights of relevant indexes can be calculated by using the entropy weight method of objective assignment method.The fuzzy comprehensive evaluation model was selected as the evaluation model of the second-level performance indicators.K-means clustering algorithm was used to classify and analyze the results of fuzzy comprehensive evaluation.Finally,the final evaluation level of performance evaluation is obtained.After the evaluation model is determined,Following the software development process,Firstly use UML diagram to analyze the requirements,then use time series diagram to design the system in detail,and finally complete the conceptual structure design and logical structure design of the database.On this basis,finally,the system functions of each module through the use of SSM framework to achieve.The innovation of this thesis is to combine the performance evaluation model with machine learning algorithm and apply it to the medical service performance evaluation system.The evaluation results calculated by this system are more accurate than those calculated manually by hospitals.It not only reflects the real medical service level of the hospital more accurately,but also improves the efficiency of medical service performance evaluation.