BackgroundVillage doctors (VDs) in China undertook arduous primary healthcare missions. However, they received little attention in comparison to doctors in urban public secondary and tertiary hospitals. There is an urgent need to explore the overall situation of turnover intention and job burnout among VDs to evaluate and adjust current health manpower policy.MethodsIn this study, seven databases like PubMed, EMBASE, Web of Science (WOS), WanFang, China Science and Technology Journal Database (VIP), Chinese BioMedical Literature Database (CBM), and China National Knowledge Infrastructure (CNKI) were systematically searched, relevant experts were consulted, and empirical research on job burnout and turnover intention among VDs in international publications was evaluated. Therefore, we evaluated the prevalence of job burnout among VDs in general, across all dimensions and different severity levels, as well as the scores of each category. For turnover intention, we assessed the prevalence of different groups and their overall situation and also identified significant contributors.ResultsIn this study, we integrated 20 research evidences on job burnout and turnover intention among 23,284 VDs from almost all provinces in China, and the prevalence of turnover intention among VDs in China was as high as 44.1% [95% confidence interval (CI): 34.1–54.2], which was two to four times that of primary health workers in high-income countries, but not much different from some developing countries. Simultaneously, VDs with the highest risk of turnover intention were men [odds ratio (OR): 1.22 (1.05–1.43)], those with a monthly income below USD 163.4 [OR: 0.88 (0.78–0.98)], those with a high educational level [OR: 0.88 (0.78–0.98)], and those

We collected a structured ophthalmic database of 5,000 patients with age, color fundus photographs from left and right eyes and doctors diagnostic keywords from doctors (in short, ODIR-5K). This dataset is ‘‘real-life’’ set of patient information collected by Shanggong Medical Technology Co., Ltd. from different hospitals/medical centers in China. In these institutions, fundus images are captured by various cameras in the market, such as Canon, Zeiss and Kowa, resulting into varied image resolutions. Patient identifying information will be removed. Annotations are labeled by trained human readers with quality control management. They classify patient into eight labels including normal (N), diabetes (D), glaucoma (G), cataract (C), AMD (A), hypertension (H), myopia (M) and other diseases/abnormalities (O) based on both eye images and additionally patient age. The publishing of this dataset follows the ethical and privacy rules of China. Table 1 shows one record from ODIR-5K dat

BackgroundPrevious studies have reported a relatively low utilization of family doctor contract services (FDCS) in China, while the associated factors are unknown. The current study aimed to explore the factors associated with the utilization of FDCS, and then developed and validated a predictive model based on these identified factors.MethodsWe conducted a nationwide cross-sectional study using an online questionnaire, from March 2019 to April of 2019. Routinely collected variables in daily practice by family doctors were used to develop a derivation model to determine the factors associated with FDCS utilization, and then the external performance of the model was tested.ResultsA total of 115,717 and 49,593 participants were included in the development and validation datasets, respectively. Nearly 6.8% of the participants who signed a contract with FDCS received healthcare services from family doctors in China. Factors associated with the utilization of FDCS included age, male sex, self-reported household income, education attainment, insurance status, self-reported health status, smoking, drinking, self-reported physical activity status, chronic disease, walking distance from the nearest community center, and illness in the last 2 weeks, with an area under the receiver operating characteristic curve (AUC) of 0.660 [95% confidence interval (CI), 0.653–0.667] and good calibration. Application of this nomogram in the validation dataset also showed acceptable diagnostic value with an AUC of 0.659 (95% CI, 0.649–0.669) and good calibration.ConclusionTwelve easily obtainable factors in daily practice of family doctors were used to develop a model to predict the utilization of FDCS, with a moderate performance.

BackgroundPatient satisfaction survey serves as a pivotal tool in evaluating the quality of healthcare services. China’s nationwide standard patient satisfaction measurement tool was introduced in 2019. This study aimed to assess the model fit of the national standard outpatient satisfaction questionnaire in a tertiary hospital and evaluate the outpatient satisfaction levels using this tool.MethodA cross-sectional survey using the national outpatient satisfaction questionnaire was conducted via message links to all hospital outpatients who registered between April and July 2022. The data collected underwent descriptive analysis, comparative analysis, and confirmatory factor analysis (CFA).ResultsA total of 6,012 valid responses were received and analyzed during this period, with 52.9% of the participants being women. The confirmatory factor analysis (CFA) model showed a good fit and identified doctor communication as having a positive effect and environmental factors as having a negative effect on outpatients’ satisfaction, with standardized regression weights of 0.46 and 0.42, respectively. Despite the remarkably high satisfaction levels, patients’ recommendation for using the services of this hospital surpassed the overall evaluation and total satisfaction scores.ConclusionA disparity was identified between the expectations and real experiences of outpatients, leading to some extent of dissatisfaction. To enhance satisfaction levels, the hospital should improve the communication skills of all clinical staff, simplify the environment layout for first-time visitors, and manage patient overloads.