Hierarchical medical system and local medical performance: A quasi-natural experiment evaluation in Shanghai, China

Does the trans-provincial immediate reimbursement reduce health gap between urban and rural floating population? Evidence from China

BACKGROUND

One of the critical components of public health policy globally is to enhance population health and mitigate health disparities. In 2017, China launched the reform of immediate reimbursement for trans-provincial treatments, aimed at increasing healthcare utilization among the floating population. This study aims to evaluate the impact of this policy reform on the health status of the urban-rural floating population.

METHODS

This study utilizes individual-level data from the 2017 and 2018 China Migrants Dynamic Survey (CMDS) and administrative hospital data at the city level. The sample includes 47,803 individuals and 66 cities. Treating the direct reimbursement policy as a quasi-natural experiment, we employ a generalized difference-in-differences model for our quantitative analysis. To control for the effects of urban-rural medical insurance integration-to ensure that both urban and rural residents are covered by the same basic medical insurance policy-our analysis of rural health status from 2016 to 2018 is limited to cities that fully implemented this policy integration before January 1, 2017.

RESULTS

The policy of immediate reimbursement for trans-provincial treatments has a significant positive impact on the health of the urban-rural floating population. The health benefits of trans-provincial treatments are less pronounced than those of trans-urban treatment, with primary hospitals showing the most notable improvements. Increased household income and consumer spending significantly amplify the health benefits of this policy for the floating population. The effects of the policy are especially pronounced in the female floating population, middle-aged and young adults, individuals with lower levels of education, those desiring long-term residency, and the unmarried groups.

CONCLUSION

This paper presents theoretical evidence that the policy of immediate reimbursement for trans-regional treatments narrows the health disparities of the urban-rural floating population and elucidates the mechanisms of this impact for the first time. These results suggest that in order to achieve health equality between urban and rural residents and equitable access to medical services, China is building a more effective medical security system.

The impact of the hierarchical medical system on medical resource allocation in China

The disparity in medical resource distribution across regions poses a significant challenge to healthcare reform in China. To address this, China has introduced the hierarchical medical system (HMS). This study evaluates the HMS's impact on the equitable distribution of medical resources. We employ the Theil index to quantify the equalization of resources among cities within provinces and use a multi-period difference-in-differences model to assess the HMS's influence. Our findings indicate that the HMS has significantly contributed to the equal distribution of medical material resources, although its effect on medical human resources is less pronounced. Additionally, we explore the influencing factors of the HMS from the perspective of supply and demand and find that it is more effective in areas with abundant resources and high demand for high-level medical services. More importantly, the HMS has played an important role in mitigating medical disparities in regions with unbalanced economic statuses. These insights are instrumental for policymakers, guiding the evolution of healthcare reforms and the refinement of the HMS to achieve the objective of universal health coverage.

The current status and influencing factors of diabetes knowledge among non-endocrinology nurses of tertiary general hospitals: a cross-sectional survey study

BACKGROUND

Every year, more than one-third of diabetes patients experience various acute and chronic complications, leading to the presence of diabetes patients in various departments of the hospital. High-quality nursing care can delay the progression of diabetes and effectively reduce the incidence of complications. Therefore, understanding the level of diabetes knowledge and training needs of clinical nurses is of great significance. This survey aims to understand the level of diabetes knowledge and influencing factors of nurses, providing a reference for conducting clinical training.

METHODS

An online cross-sectional survey using a questionnaire and involving 3117 nurses from 9 tertiary general hospitals from Guizhou Province, China were conducted. This questionnaire consists of three parts: a general information survey, self-assessment of diabetes knowledge, and objective assessment of diabetes knowledge. We analyzed the data using SPSS 29.0.

RESULTS

The participants' self-assessment score for diabetes knowledge were (62.27 ± 16.80)(out of 100), objective score for diabetes knowledge were (57.33 ± 25.78)(out of 100). Multiple linear regression analyses indicated that diabetes in-service education, department and the last time they cared for a diabetes patient were the influencing factors of nurses' diabetes knowledge scores (P < 0.05).

CONCLUSION

The knowledge of non-endocrinology nurse' diabetes needs to be improved. There is a gap between non-endocrinology nurses' self-perception of diabetes knowledge and their actual knowledge level. Therefore, nursing managers should prioritize diabetes knowledge training for nurses in non-endocrinology departments, develop practical training programs based on nurses' needs, enhance their diabetes care knowledge, and provide higher quality care services to patients.

Impact of China's primary healthcare reforms on utilisation, payments and self-reported health: a quasi-experimental analysis of a middle-aged and older cohort 2011-2018

Background

Comprehensive health reforms aimed at strengthening primary healthcare (PHC) are infrequently adopted and often poorly evaluated in low-income and middle-income countries. China launched a system-wide PHC reform with a staggered roll-out between 2014 and 2018 with multiple components: (1) gatekeeping via tiered reimbursement, (2) a family physician scheme and (3) a two-way referral system between PHC facilities and hospitals. This study examines the reform impacts on health service utilisation, out-of-pocket expenditures, health outcomes and health inequalities.

Methods

The staggered roll-out of the reforms in 125 cities across China was identified using web-scraping. Using longitudinal data (2011-2018) from the China Health and Retirement Longitudinal Study (a cohort aged ≥45), this study adopted a difference-in-differences method to assess the reform's impacts on: (1) visits to PHC facilities, (2) hospitalisation, (3) out-of-pocket expenditures (OOPEs) and (4) self-reported health. Subgroup analyses were conducted by rural/urban populations and wealth quartiles.

Results

The reform had small and short-lived impacts-a 7.8% increase in the probability of visiting PHC facilities (95% CI 0.3 to 15.2), a 10.2% increase in reporting good health (95% CI 0.6 to 19.8) and an 873.9 Chinese Yuan (US$129.1) increase in average annual OOPEs (95% CI 57.9 to 1689.9) in the first year of reform implementation. There was no impact on hospitalisation. Increases in PHC utilisation were only found in rural and lower-income populations.

Conclusions

China's PHC reforms had some modest, temporary impacts on increasing primary care utilisation and self-reported health. However, further interventions are needed to transition away from the hospital-centric health system and to increase financial protection and health equity in China.

Sociodemographic factors impacting the spatial distribution of private dental clinics in major cities of Peoples Republic of China

OBJECTIVES

Investigate the geographical distribution of private dental practices in major Chinese cities and analyze the variables influencing this distribution.

METHODS

This study used Python to extract various types of Point of Interest (POI) data spanning from 2016 to 2022 from the AutoNavi map. A 1km*1km grid was constructed to establish the study sample. Additional spatial pattern data, including nighttime lighting, population, and air quality data, were integrated into this grid. Global Moran's I index was used to analyze the spatial autocorrelation. The spatial lag model was used to explore the influencing factors of private dental practice distribution.

RESULTS

This study reveals a specific clustering pattern for private dental practices in major Chinese cities. The primary influencing factors include nighttime lights, population density, and housing prices, suggesting that dental practices are typically concentrated in highly developed regions with dense populations and high housing costs. Additionally, we discovered that patterns vary across different metropolises, with the most pronounced clustering patterns and substantial inequalities found in the most developed areas.

CONCLUSIONS

This study establishes that factors such as regional development and population density positively correlate with private dental practice. Additionally, it reveals a strong mutual correlation in the clustering of dental practices, which does not show a substantial correlation with public resources. Finally, it suggests that the spatial heterogeneity pattern implies a rising necessity to tackle inequality issues within urban areas as economic development progresses.

Has China's hierarchical medical system improved doctor-patient relationships?

BACKGROUND AND OBJECTIVE

Developing harmonious doctor-patient relationships is a powerful way to promote the construction of a new pattern of medical reform in developing countries. We aim to analyze the effects of China's hierarchical medical system on doctor-patient relationships, thus contributing to China's medical and health system reform.

METHODS

With panel data on prefectural-level cities in China from 2012 to 2019, we used a time-varying difference-in-differences model to evaluate the effect of hierarchical medical treatment policy.

RESULTS

Hierarchical medical treatment policies can significantly improve doctor-patient relationships, and this conclusion is supported by various robustness tests. And improving doctor-patient relationships can be indirectly realized by the optimization of resource allocation and saving of medical costs. In addition, the marginal effect of the pilot policy on doctor-patient relationships decreased with age within the city population. In focal cities and cities with high levels of fiscal spending on health care, the effect of the pilot policy on doctor-patient relationships was stronger.

CONCLUSION

While reinforcing the literature on the doctor-patient relationship, this study also provides a reference for further exploration of the pilot policy of hierarchical medical treatment and the development of new medical and health system reform in developing countries.

Effectiveness of hierarchical medical system and economic growth: based on China's urban vs. rural health perspectives

Background

The hierarchical medical system is an important measure to promote equitable healthcare and sustain economic development. As the population's consumption level rises, the demand for healthcare services also increases. Based on urban and rural perspectives in China, this study aims to investigate the effectiveness of the hierarchical medical system and its relationship with economic development in China.

Materials and methods

The study analyses panel data collected from Chinese government authorities, covering the period from 2009 to 2022. According to China's regional development policy, China is divided into the following regions: Eastern, Middle, Western, and Northeastern. Urban and rural component factors were downscaled using principal component analysis (PCA). The factor score formula combined with Urban-rural disparity rate (ΔD) were utilized to construct models for evaluating the effectiveness of the hierarchical medical system from an urban-rural perspective. A Vector Autoregression model is then constructed to analyze the dynamic relationship between the effects of the hierarchical medical system and economic growth, and to predict potential future changes.

Results

Three principal factors were extracted. The contributions of the three principal factors were 38.132, 27.662, and 23.028%. In 2021, the hierarchical medical systems worked well in Henan (F = 47245.887), Shandong (F = 45999.640), and Guangdong (F = 42856.163). The Northeast (ΔDmax = 18.77%) and Eastern region (ΔDmax = 26.04%) had smaller disparities than the Middle (ΔDmax = 49.25%) and Western region (ΔDmax = 56.70%). Vector autoregression model reveals a long-term cointegration relationship between economic development and the healthcare burden for both urban and rural residents (βurban = 3.09, βrural = 3.66), as well as the number of individuals receiving health education (β = -0.3492). Both the Granger causality test and impulse response analysis validate the existence of a substantial time lag between the impact of the hierarchical medical system and economic growth.

Conclusion

Residents in urban areas are more affected by economic factors, while those in rural areas are more influenced by time considerations. The urban rural disparity in the hierarchical medical system is associated with the level of economic development of the region. When formulating policies for economically relevant hierarchical medical systems, it is important to consider the impact of longer lags.

Risk management and empirical study of the doctor-patient relationship: based on 1790 litigation cases of medical damage liability disputes in China

BACKGROUND

Compensation for medical damage liability disputes (CMDLD) seriously hinders the healthy development of hospitals and undermines the harmony of the doctor-patient relationships (DPR). Risk management in the DPR has become an urgent issue of the day. The study aims to provide a comprehensive description of CMDLD in China and explore its influencing factors, and make corresponding recommendations for the management of risks in the DPR.

METHODS

This study extracted data from the China Judgment Online - the official judicial search website with the most comprehensive coverage. Statistical analysis of 1,790 litigation cases of medical damage liability disputes (COMDLD) available from 2015 to 2021.

RESULTS

COMDLD generally tended to increase with the year and was unevenly distributed by regions; the compensation rate was 52.46%, the median compensation was 134,900 yuan and the maximum was 2,234,666 yuan; the results of the single factor analysis showed that there were statistically significant differences between the compensation for different years, regions, treatment attributes, and trial procedures (P < 0.05); the correlation analysis showed that types of hospitals were significantly negatively associated with regions (R=-0.082, P < 0.05); trial procedures were significantly negatively correlated with years (R=-0.484, P < 0.001); compensat- ion was significantly positively correlated with years, regions, and treatment attributes (R = 0.098-0.294, P < 0.001) and negatively correlated with trial procedures (R=-0.090, P < 0.01); regression analysis showed that years, treatment attributes, and regions were the main factors affecting the CMDLD (P < 0.05).

CONCLUSIONS

Years, regions, treatment attributes, and trial procedures affect the outcome of CMDLD. This paper further puts forward relevant suggestions and countermeasures for the governance of doctor-patient risks based on the empirical results. Including rational allocation of medical resources to narrow the differences between regions; promoting the expansion and sinking of high-quality resources to improve the level of medical services in hospitals at all levels; and developing a third-party negotiation mechanism for medical disputes to reduce the cost of medical litigation.

Quality and Dependability of ChatGPT and DingXiangYuan Forums for Remote Orthopedic Consultations: Comparative Analysis

BACKGROUND

The widespread use of artificial intelligence, such as ChatGPT (OpenAI), is transforming sectors, including health care, while separate advancements of the internet have enabled platforms such as China's DingXiangYuan to offer remote medical services.

OBJECTIVE

This study evaluates ChatGPT-4's responses against those of professional health care providers in telemedicine, assessing artificial intelligence's capability to support the surge in remote medical consultations and its impact on health care delivery.

METHODS

We sourced remote orthopedic consultations from "Doctor DingXiang," with responses from its certified physicians as the control and ChatGPT's responses as the experimental group. In all, 3 blindfolded, experienced orthopedic surgeons assessed responses against 7 criteria: "logical reasoning," "internal information," "external information," "guiding function," "therapeutic effect," "medical knowledge popularization education," and "overall satisfaction." We used Fleiss κ to measure agreement among multiple raters.

RESULTS

Initially, consultation records for a cumulative count of 8 maladies (equivalent to 800 cases) were gathered. We ultimately included 73 consultation records by May 2023, following primary and rescreening, in which no communication records containing private information, images, or voice messages were transmitted. After statistical scoring, we discovered that ChatGPT's "internal information" score (mean 4.61, SD 0.52 points vs mean 4.66, SD 0.49 points; P=.43) and "therapeutic effect" score (mean 4.43, SD 0.75 points vs mean 4.55, SD 0.62 points; P=.32) were lower than those of the control group, but the differences were not statistically significant. ChatGPT showed better performance with a higher "logical reasoning" score (mean 4.81, SD 0.36 points vs mean 4.75, SD 0.39 points; P=.38), "external information" score (mean 4.06, SD 0.72 points vs mean 3.92, SD 0.77 points; P=.25), and "guiding function" score (mean 4.73, SD 0.51 points vs mean 4.72, SD 0.54 points; P=.96), although the differences were not statistically significant. Meanwhile, the "medical knowledge popularization education" score of ChatGPT was better than that of the control group (mean 4.49, SD 0.67 points vs mean 3.87, SD 1.01 points; P<.001), and the difference was statistically significant. In terms of "overall satisfaction," the difference was not statistically significant between the groups (mean 8.35, SD 1.38 points vs mean 8.37, SD 1.24 points; P=.92). According to how Fleiss κ values were interpreted, 6 of the control group's score points were classified as displaying "fair agreement" (P<.001), and 1 was classified as showing "substantial agreement" (P<.001). In the experimental group, 3 points were classified as indicating "fair agreement," while 4 suggested "moderate agreement" (P<.001).

CONCLUSIONS

ChatGPT-4 matches the expertise found in DingXiangYuan forums' paid consultations, excelling particularly in scientific education. It presents a promising alternative for remote health advice. For health care professionals, it could act as an aid in patient education, while patients may use it as a convenient tool for health inquiries.

Deep Learning-Based Computer-Aided Diagnosis for Breast Lesion Classification on Ultrasound: A Prospective Multicenter Study of Radiologists Without Breast Ultrasound Expertise

BACKGROUND. Computer-aided diagnosis (CAD) systems for breast ultrasound interpretation have been primarily evaluated at tertiary and/or urban medical centers by radiologists with breast ultrasound expertise. OBJECTIVE. The purpose of this study was to evaluate the usefulness of deep learning-based CAD software on the diagnostic performance of radiologists without breast ultrasound expertise at secondary or rural hospitals in the differentiation of benign and malignant breast lesions measuring up to 2.0 cm on ultrasound. METHODS. This prospective study included patients scheduled to undergo biopsy or surgical resection at any of eight participating secondary or rural hospitals in China of a breast lesion classified as BI-RADS category 3-5 on prior breast ultrasound from November 2021 to September 2022. Patients underwent an additional investigational breast ultrasound, performed and interpreted by a radiologist without breast ultrasound expertise (hybrid body/breast radiologists, either who lacked breast imaging subspecialty training or for whom the number of breast ultrasounds performed annually accounted for less than 10% of all ultrasounds performed annually by the radiologist), who assigned a BI-RADS category. CAD results were used to upgrade reader-assigned BI-RADS category 3 lesions to category 4A and to downgrade reader-assigned BI-RADS category 4A lesions to category 3. Histologic results of biopsy or resection served as the reference standard. RESULTS. The study included 313 patients (mean age, 47.0 ± 14.0 years) with 313 breast lesions (102 malignant, 211 benign). Of BI-RADS category 3 lesions, 6.0% (6/100) were upgraded by CAD to category 4A, of which 16.7% (1/6) were malignant. Of category 4A lesions, 79.1% (87/110) were downgraded by CAD to category 3, of which 4.6% (4/87) were malignant. Diagnostic performance was significantly better after application of CAD, in comparison with before application of CAD, in terms of accuracy (86.6% vs 62.6%, p < .001), specificity (82.9% vs 46.0%, p < .001), and PPV (72.7% vs 46.5%, p < .001) but not significantly different in terms of sensitivity (94.1% vs 97.1%, p = .38) or NPV (96.7% vs 97.0%, p > .99). CONCLUSION. CAD significantly improved radiologists' diagnostic performance, showing particular potential to reduce the frequency of benign breast biopsies. CLINICAL IMPACT. The findings indicate the ability of CAD to improve patient care in settings with incomplete access to breast imaging expertise.