BackgroundQuality of health care needs to be improved in rural China. The Chinese government, based on the 1999 Law on Physicians, started implementing the Rural Doctor Practice Regulation in 2004 to increase the percentage of certified physicians among village doctors. Special exam-targeted training for rural doctors therefore was launched as a national initiative. This study examined these rural doctors’ perceptions of whether that training helps them pass the exam and whether it improves their skills.MethodsThree counties were selected from the 4 counties in Changzhou City in eastern China, and 844 village doctors were surveyed by a questionnaire in July 2012. Chi-square test and Fisher exact test were used to identify differences of attitudes about the exam and training between the rural doctors and certified (assistant) doctors. Longitudinal annual statistics (1980–2014) of village doctors were further analyzed.ResultsEight hundred and forty-four village doctors were asked to participate, and 837 (99.17%) responded. Only 14.93% of the respondents had received physician (assistant) certification. Only 49.45% of the village doctors thought that the areas tested by the certification exam were closely related to the healthcare needs of rural populations. The majority (86.19%) felt that the training program was “very helpful” or “helpful” for preparing for the exam. More than half the village doctors (61.46%) attended the “weekly school”. The village doctors considered the most effective method of learning was “continuous training (40.36%)” . The majority of the rural doctors (89.91%) said they would be willing to participate in the training and 96.87% stated that they could afford to pay up to 2000 yuan for it.ConclusionsThe majority of village doctors in Changzhou City perceived that neither the certification exam nor the training for it are closely related to the actual healthcare needs of rural residents. Policies and programs should focus on providing exam-preparation training for selected rural doctors, reducing training expenditures, and utilizing web-based methods. The training focused on rural practice should be provided to all village doctors, even certified physicians. The government should also adjust the local licensing requirements to attract and recruit new village doctors.Electronic supplementary materialThe online version of this article (10.1186/s12909-018-1211-5) contains supplementary material, which is available to authorized users.
Abstract:Debit card business is a very important business, bank debit card and bank users the most on the one hand, so every year the debit card user transaction data is very huge, in what is now the era of big data, data is wealth, we have huge debit card transaction data, you need to use big data technology to deal with the data analysis, found that there were a rule, and conducive to the development of bank data and results are obtained.In this article, through analysis of transaction data of debit card users, debit card users are classified, and the bank large customers and high quality clients and has great potential customers, and puts forward the time were significantly abnormal in the transaction data
Financial industry is facing unprecedented challenges, especially fierce competition between commercial banks, so it is urgent for us to solve a problem of comprehensive analysis and appropriate suggestions for the development of commercial banks. This survey uses a commercial bank's input and output data, provides an overall efficiency ranking of bank branches by calculating through the traditional DEA model(C 2 R), DEA Overlapping Efficiency Model and Weight-restricted DEA model. The experimental results provide the basis for understanding of each branch, which is affiliated to the commercial bank. Keywords:Bank efficiency, DEA model, Input-output efficiency. 1.IntroductionCommercial banks can assess their strengths and weakness by implementing comprehensive performance evaluation of management. To promote commercial banks' competitiveness, analysis of experimental results will provide insights into assigning the limited financial resources scientifically and rationally to decision-maker. As recognized by all economists in the western theory of economics, both the definition and description of bank efficiency are the contrasting relationship between investment and yield in their business activities. With the deepening of reform and opening up, the financial industry is facing unprecedented challenges, especially between interbank market. The question of how to achieve optimal financial resources for a single unit within the bank is a problem that needs to be addressed. Twenty years after Farrell's seminal work,and building on those ideas, Charnes et al. (1978),proposed data envelopment analysis(DEA) [1]. DEA(data envelopment analysis) Model is a commonly used method for evaluating company's operating efficiency [2]. However, the fact is that each decision unit is maximizing its efficiency rating index [3], which tends to use extreme and unreasonable weight distribution for the input and output indices, the traditional DEA method's result is somewhat unsatisfactory and cannot identify strengths and weaknesses between all the DMU. DEA Overlapping Efficiency Model partially compensates for these shortcomings of the traditional DEA method [4]. Traditional DEA model and DEA Overlapping Efficiency Model are too objective for the efficiency evaluation of commercial banks [5]. This paper provide a weight-restricted DEA model, with more subjective factors of decision ideology and value judgement. Evaluation results can be more approximates the real facts by adding the appropriate weights constraint conditions [6]. The rest of this article is organized as follows. Section 2 describes the experimental dataset of a commercial bank. Section 3 explains the models for bank efficiency and how to calculate the efficiency values of bank branches. In section 4, we show the ranking list, compare our approach results and discuss the possible causes for the ranking results. Finally, we give concluding remarks in Section 5. 2.DatasetsWe used seventeen sub-branches' input-output data of a commercial bank , input data includ...
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