The Unmet Medical Demand among China's Urban Residents

Inequalities in Unmet Needs for Healthcare Services Among Middle-Aged and Older Adults in China

Unmet needs for healthcare services are widely recognized as an indicator of inequalities in healthcare access and utilization. This study estimated inequalities in unmet needs for healthcare services as well as their contributing factors and reasons among middle-aged and older adults in China. Results indicated that 30.47% and 5.69% of the middle-aged and older population in China reported unmet needs for outpatient and inpatient services, respectively. Mostly pro-poor inequalities concerned unmet needs for both rural and urban residents. The coverage of public health insurance and individuals' health status contributed most to the inequalities in the unmet needs identified. The most prevalent reason for unmet needs was affordability, especially for poor or rural respondents. Despite the rapid development of universal healthcare, unmet needs for healthcare services still existed and remained high among people living in rural areas and with low incomes in China. Policy interventions should focus on improving the public health insurance system and targeting financial barriers to obtaining care, particularly vulnerable populations in China.

Characteristics of Medical Quality in Tertiary Traditional Chinese Medicine Hospitals by TOPSIS and RSR Methods

Performance evaluation is important for improving medical quality and services. But, there is a lack of research for medical quality in traditional Chinese medicine (TCM) hospitals. This study examines the medical quality and various indicators of tertiary public traditional Chinese medicine hospitals in Gansu Province, to establish a foundation for improving the medical and management standards of these hospitals. This study collected performance assessment data from 10 tertiary TCM hospitals in Gansu Province from 2019 to 2022. Thirteen indicators with TCM characteristics were selected and categorized into 3 aspects: control of medical costs, internal operational dimensions, and comprehensive management. The level of medical quality in different hospitals and in different years were determined using the TOPSIS method for ranking and the RSR method for grading. Firstly, in terms of TCM characteristic indicators, hospital H had the highest control of medical costs and comprehensive management among different hospitals, with 45.87% and 24.20% respectively. The highest values for control of medical costs and comprehensive management were observed in 2020, with 40.65% and 18.69% respectively among different years. When evaluating the medical quality of different hospitals using the TOPSIS method, it was found that hospital H had the highest ranking from 2020 to 2022, with Ci values of 0.725, 0.778, and 0.667 respectively. Additionally, the RSR method indicated that hospital H had a high level of grading from 2020 to 2022, with Pi values of 0.687, 0.690, and 0.723 respectively. These findings suggest that the medical quality of hospital H is at a high and stable level of development. Based on the TOPSIS method to evaluate the performance appraisal results and ranking of different hospitals from 2019 to 2022. The results showed that the highest ranking was hospital B(Ci = 0.913) in 2019. The highest ranking was hospital C(Ci = 0.809)in 2020. The highest ranking was hospital D(Ci = 0.689) in 2021. The highest ranking was hospital J(Ci = 0.865) in 2022. The RSR method indicated that high grading level were hospitals B(Pi = 0.899),F(Pi = 0.795) in 2019. The highest grading level was hospital C(Pi = 0.809) in 2020. The highest grading level were hospitals A(Pi = 0.868), D(Pi = 0.813), E(Pi = 0.689), G(Pi = 0.873), J(Pi = 0.813), K(Pi = 0.842) in 2022. Based on the above results indicate that there is a large variation in the medical quality profile of different hospitals from 2019 to 2022. By comparing the results of TOPSIS and RSR method from 2019 to 2022, we found that the hospitals with identical ranking were D and J, and the hospitals with ≤2 difference in ranking was A,B,C,E in 2019, the hospitals with >2 ranking was A, F in 2020, the hospitals with >2 ranking were C, G in 2021, and the hospitals with identical ranking results were B,D,E,G,J in 2022. Comparing the ranking results of TOPSIS and RSR methods, showed that the hospitals with identical rankings were B, F from 2019 to 2022. The difference in ranking results ≤2 were A, C, D, E, G, H, J, K, indicating that high consistency between TOPSIS and RSR methods and credible results. The findings reveal significant fluctuations in medical quality across different years, while the overall level of medical quality remains relatively stable among the various hospitals. It is recommended that TCM hospitals focus on improving management efficiency, optimizing hospital operations, enhancing the utilization of medical resources, and fostering the efficient development of hospitals.

Can Comprehensive Medical Reform Improve the Efficiency of Medical Resource Allocation? Evidence From China

Objectives: To evaluate the impact of comprehensive medical reform on the efficiency of medical resource allocation in China. Methods: This study employs the Slacks-Based Measure- Directional Distance Function (SBM-DDF) to estimate the efficiency of medical resource allocation (MRAE) in China, using panel data from 30 provinces during 2009-2021. Moreover, a multi-period Difference in differences (DID) model is developed to explore the effect of the comprehensive medical reform pilot (CMRP) strategy on efficiency of medical resource allocation in China. Results: The results show that the average value of China's medical resources allocation efficiency is 0.861 during the sample period. Coastal area has a higher MRAE than that in the inland area. The DID results show that the comprehensive medical reform pilot strategy has a good, long-lasting impact on the efficiency of medical resource allocation. And the results remain valid after a series of robustness analysis. Additionally, the comprehensive medical reform policy has heterogeneous impact on efficiency of medical resource allocation. The promotion effect is only statistically significant in the eastern and central regions, the groups of higher MRAE and larger population size. Conclusion: China's comprehensive medical reform policy can effectively promote the improvement of regional efficiency of medical resource allocation.

Prevalence and Influencing Factors of Help-Seeking Behavior Among Women with Urinary Incontinence: A Systematic Review and Meta-Analysis

Purpose: This systematic review and meta-analysis aimed to investigate the mean (weighted) prevalence of help-seeking behavior among women with urinary incontinence (UI) in relevant subgroups and the related influencing factors. Materials and Methods: Six English and four Chinese databases were systematically searched between 1996 and July 10, 2022. Two researchers independently screened the literature, extracted data, and evaluated the quality of the included studies. All statistical analyses were conducted using RevMan 5.4. Results: The mean (weighted) prevalence of help-seeking behavior based on the 41 included studies, including a total of 32,640 women with UI, was 28% (95% confidence interval [CI]: 22%-34%). We performed a subgroup analysis based on UI type, population, region, publication time, case definition of help-seeking, and use of validated tools to determine UI. The results of the subgroup analysis showed that the pooled prevalence of help-seeking behavior was 23% (95% CI: 14%-32%) among pregnant and maternity women, 27% (95% CI: 19%-35%) among menopausal women, 24% (95% CI: 14%-35%) among 20- to 50-year-old women, 31% (95% CI: 25%-36%) among those older than 50 years, 24% (95% CI: 17%-30%) in Asia, and 33% (95% CI: 22%-44%) in Europe. Meanwhile, the pooled odds ratio showed that education level, UI type, UI severity, and quality of life significantly influenced help-seeking behavior among women with UI. Conclusions: This systematic review revealed that the pooled prevalence of help-seeking behaviors among women with UI is 28%. These influencing factors have important implications for adapting to health care and social care systems.