This study innovatively took hospital management as the cut-in point; based on the perspectives of doctors and patients as well as disease-related factors, we analyzed information from 561 medical disputes that occurred in Shanghai over a three-year period (January 2018 to December 2020), as extracted via multistage sampling. Specifically, we analyzed the high-risk factors for disputes and conducted a correlation test to determine which influencing factors were likely to further escalate disputes.
We initially employed multistage sampling to collect information on 561 medical disputes that occurred in two Class A tertiary hospitals, two Class A secondary hospitals, and four community hospitals in Shanghai over a three-year period (2018 to 2020). The Class A tertiary hospital aims to diagnosis and treat the difficult and critical diseases. The Class A secondary hospital aims to diagnosis and treat the common diseases. The community hospital aims to treat and manage the chronic diseases. Of these, 41 cases were removed due to incomplete information, resulting in 520 cases with complete information for analysis (pass rate of 92.69%).
As previously developed by the current research team, this study used the Questionnaire on Medical Dispute Case Analysis , which is comprised of six dimensions covering 23 items, including demographic indicators (six items), medical factors (four items), patient factors (two items), disease factors (four items), communication factors (two items), and dispute handling factors (five items).
The demographic indicators include gender, age, native place, occupation, education, marriage. The medical factors include attending doctor, medical quality, expert opinion, non-technical factor. The expert opinions of medical factors include violation of diagnosis and treatment regulation, belated diagnosis and treatment, imperfect operation, low technical level and so on. The patient factors include medical insurance and non-error medical disputes factors. The non-error medical disputes factors of patient factors include misunderstanding of medical behavior, bad attitude, mistrust, inadequate medical knowledge and so on. The communication factors include doctor’s factors and patient’s factors. The doctor’s factors of communication factors include critical behavior to patients, insufficient communication and others. The patient’s factors of communication factors include bad attitude, patient’s speech threatened the door and so on. The dispute handling factors include dispute level, amount of compensation, handling time, violent conflict and so on. The dispute level include Level1, Level2, Level3, Level4.The amount of compensation include above one million REN MIN BI, between 500,000 and one million REN MIN BI, between 100,000 and 500,000 REN MIN BI, below 100,000 REN MIN BI. This classification method comes from the research that was conducted by Yonghai Bai about influencing factors of medical disputes in Class A tertiary hospital in Shanghai .
We conducted a retrospective analysis and processed documents related to the obtained cases. Prior to the investigation, we requested that the hospital president in charge of medical disputes help communicate with the director of reception office and we trained the investigators. The researcher introduced the plan, the purpose, the method of the research, the situation related to the questionnaire to all the investigators, so that the investigators can have an overall understanding of the project, and we explains the steps, requirements, time arrangement, workload and other specific issues of the questionnaire. We trained the investigators to make them clear about all the contents of the questionnaire, the way of filling and the items need to be concerned of the questionnaire. According to the requirements and steps of the formal investigation, we conduct a simulation investigation and let each investigator practice from beginning to end. Then, we summarized the problems in the simulation investigation and solved these problems through discussion or explanation. The discussion or explanation include that organizational management measures, guidance and supervision measures, review and inspection measures, summary and exchange system.
Then we went to the hospital medical office of the hospital and the director of the dispute office helped find the case files of medical disputes from January 2018 to December 2020. The investigators first read and analyzed the medical dispute cases, and then according to the questions in the questionnaire, he extracted information about doctors, patients and diseases from the medical cases. At the same time, he filled in the questionnaire timely. In the questionnaire, there is an option for the amount of compensation for medical disputes. In the medical disputes files, there is the amount of compensation for disputes. We extracted the amount of compensation information from the case of medical disputes and filled in the questionnaire. Once one questionnaire was filled out, another investigator performed strict double-check task. During this process, all questions that we asked were answered timely by the director of the dispute office. After the investigation in one hospital, we carried out the same investigation in another hospital, and a total of eight hospitals were investigated.
The data collected thereby collected were recorded via Microsoft Excel and processed using IBM SPSS18. Diseases were divided into four categories in line with the principle of case classification ; this included simple general cases, simple emergent cases, complex intractable cases, and complex critical cases. Medical disputes were classified into one of four levels, including level 4 (compensation below 100,000 REN MIN BI), level 3 (compensation between 100,000 and 500,000 REN MIN BI), level 2 (compensation between 500,000 and one million REN MIN BI), and level 1 (compensation above one million REN MIN BI) . Taking the disease-related, doctor-related, and patient-related factors as independent variables and the dispute levels as dependent variables, we conducted a one-way ANOVA to more thoroughly analyze the medical dispute levels. The results were then substituted into a multiple logistic regression model to obtain the indicators of high-risk factors for medical disputes (significance at 0.05).
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