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A Study On The Influencing Factors Of Residents' Choice Of Medical Institutions And The Gap Between Willingness And Behavior In Hierarchic Care

Posted on:2021-01-23Degree:MasterType:Thesis
Country:ChinaCandidate:Y GaoFull Text:PDF
GTID:2404330620968071Subject:Business management
Abstract/Summary:PDF Full Text Request
In recent years,with the rapid development of China's economy,medical technology and the steady increase of residents' income,people's demand for health services is also increasing.According to data from the National Health Commission,from January to November in 2019 alone,the number of visits to medical institutions nationwide reached 7.75 billion,up 2.8 percent year-on-year.Although Chinese government departments continue to deepen the reform of the medical system,promote the hierarchical medical system and the construction of integrated care organization,there has been no significant change in patients' medical behavior,the phenomenon of crowded hospitals is still common,and the problems of "difficult to see a doctor","expensive to see a doctor" and "complicated to see a doctor" still trouble the people.The purpose of this article is to identify the problem and help solve it.Only through indepth investigation and analysis of the factors affecting patients' medical decision,can we promote the implementation of hierarchical medical treatment and medical alliance system,so as to promote the formation of a fair,efficient and orderly medical and health service model and realize scientific medical treatment for patients.This article takes the actual implementation effect of the Ruijin-Luwan Regional Medical Organization as the starting point,and uses the main research content of Shanghai residents' medical treatment behaviors to comprehensively investigate and analyze the reasons that influence patients to choose different levels of hospitals.Regression equations are used to find out the factors of the patient's choice of basic medical treatment and the gap between willingness and behavior in hierarchic care.This article first combs existing domestic and foreign theories and literatures,and builds a model of influencing factors for medical treatment behaviors of Shanghai residents by referring to the Anderson model.Based on pre-investigation,the author went to 7 medical institutions in the Ruijin-Luwan Regional Medical Organization to conduct field surveys.It is found that residents' perceptions of the system are not very optimistic,that they feel less sick,complicated medical procedures,and unable to spare time are the main reasons why patients do not go to the hospital for medical treatment.Secondly,the data shows that 41.2% and 28.4% of patients have received upward or downward referral services respectively and most of the patients have the highest satisfaction with the two measures: purchase third-level hospital medicines near the primary hospital,and the consultation information can be shared and mutually recognized in the hospitals of the medical association.This paper uses Logistic regression and decision tree algorithms to find out the specific factors that influence patients to choose different levels of hospital treatment.The results show that the medical treatment behavior is affected to varying degrees by personal attributes,health factors,hospital characteristics,and promotion conditions.In addition,the Logit model of employee medical insurance,resident medical insurance(including NCMS patients)choosing hospital level is different,which is mainly due to the different medical expenses after medical insurance reimbursement and the different importance of recommendation from relatives and friends.The factors of habit and risk aversion have a moderating effect on the willingness of patients to follow the hierarchical medical system and their actual behaviors.Finally,this article combines the pre-survey interview content and empirical analysis results,and proposes countermeasures from three aspects: government agencies,medical institutions at all levels,and ordinary residents.
Keywords/Search Tags:Hospital selection, Integrated care organization, Hierarchical medical system, Logistic regression, Decision tree
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