Research On The Application Of Multiple Linear Regression And Bayesian Network To The Analysis And Prediction Of The Medical Service Index

Recent-year is a very critical period of the healthcare reform in our country.To persist in the medical reform policy of public welfare nature is clearly put forward by our country.Improving the quality of medical services is an important measure to solve the doctor-patient contradiction and promote the public healthcare experience.The "big quality" idea in the medical services is an inevitable result of the establishment of the new medical model.Humanization,individualization and socialization are the specific requirements of the "big quality" idea in the medical services.There are some limitations and service restrictions in the development of the medical science,which may cause some unpredictable service defects in medical treatment.Therefore,it is an urgent and important problem to offset and break these service defects.With the development of the society and the progress of science and technology,many hospitals have very advanced medical facility and top medical technology,but they can't provide the satisfying medical service and the medical environment which are matching the strength they have.We can see from this point that the medical service is not only reflected by the medical technology,it is a system.The accumulation of time and space is the key to improve the quality of medical service,which means that the extension of time and the expansion of space are reflected on the improvement and progress of the service details.This accumulation inevitably demands that every service,step and process is normative.The norm of the medical service system should be built on the requirements and satisfaction of the patients.It is supported by relative data with the ultimate goal of completing the medical services.Prediction is a usual method in data mining.It is helpful to formulate the specific service system and measures,to construct the hardware and software managements,to improve the quality,efficiency and satisfaction of the medical service by predicting the outpatient numbers,average stay in hospital,queuing time for consultation and other medical service indexes.This paper mainly compares the application features between Multiple Linear Regression and Bayesian Network Inference by introducing these two methods and taking the application in the prediction of the average stay in hospital as examples,which can provide the rational methods and suggestions to the study of the medical service index.