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IntroductionThis study investigated segmented assimilation patterns and factors influencing health education utilization (HEU) among internal migrant populations in China, driven by concerns over their declining health owing to urbanization-related changes.MethodsData from the 2017 China Migrants Dynamic Survey were analyzed, focusing on 13,998 rural migrants. Negative binomial regression was used to explore assimilation patterns and determine the factors affecting HEU among internal migrants in China.ResultsThe results revealed diverse assimilation patterns among internal migrants in four clusters: first-generation classic assimilation, first-generation integration assimilation, second-generation segmented assimilation, and second-generation underclass assimilation. Adjusting for socioeconomic factors, first-generation integrated assimilation groups showed lower HEU (IRR = 0.922, p

Objective The aim of this study is to develop, implement the precise reservation path (PRP) and investigate its prediction function for scheduling shunting patients for specialist appointment registration in Shanghai, China.Design The PRP system was built on the hospital’s existing information system, integrated with WeChat (WeCom) for user convenience. The outcome analysis employed a mixed-methods approach, integrating quantitative analysis with statistical and machine learning techniques, including multivariate logistic regression, random forest (RF) and artificial neural network (ANN) analysis.Setting This study was conducted at Renji Hospital, a premier general tertiary care institution in Shanghai, China, where the innovative PRP system was implemented. The programme was designed to efficiently connect patients requiring specialised care with the appropriate medical specialists.Participants The PRP encompassed both voluntary specialists at Renji Hospital, as well as patients seeking outpatient specialist services.Primary outcome measures The pass rates of patient for specialist applications.Secondary outcome measures Clinical department, specialists’ and patients’ characteristics influencing specialist review result.Results From a data set of 58 271 applicants across 26 departments between 1 December 2020 and 30 November 2022, we noted an overall pass rate of 34.8%. The departments of urology, breast surgery and thoracic surgery, along with five others, accounted for 86.65% of applications. Pass rates varied significantly, and demographic distributions of applicants across departments revealed distinct patient profiles, with preferences evident for age and gender. We developed an RF model based on pass rates from 26 specialised departments. The RF model, with 92.31% accuracy, identified age as the primary predictor of pass rates, underscoring its impact on specialist review outcomes. Focus on patient demographics, we conducted univariate and multivariate logistic regression analyses on the 58 271 patient data set to explore the relationship between demographic factors and review outcomes. Key findings from logistic regression included significant associations with gender, age and specialist title. Results indicated that older patients were more likely to be approved in specialist reviews, while middle-aged patients had lower pass rates. The generalised linear model, enhanced with specialist and clinical department variables, showed superior predictive accuracy (67.86–68.26%) and model fit over the previous logistic model. An ANN model also identified specialist and clinical department as the most influential, achieving comparable accuracy (67.72–68.28%).Conclusions The PRP programme demonstrates the potential of digital innovation in enhancing the hierarchical medical system. The study’s findings also underscore the value of the PRP programme in healthcare systems for optimising resource allocation, particularly for ageing populations. The programme’s design and implementation offer a scalable model for other healthcare institutions seeking to enhance their appointment systems and specialist engagement through digital innovation.

Physician trust is necessary for improving physician–patient relationships and maintaining an effective health-care system. Most studies on the theory of segmentation assimilation have mainly focused on comparing immigrants in different countries and few studies have applied segmented assimilation to clarify physician–patient relationships, especially physician trust among internal migrants in the context of Chinese megacities. A random sample of 1200 internal migrants was collected through an online questionnaire conducted in Shanghai from August to December 2021. An exploratory K-means cluster analysis and multivariate logistic regression models were employed to identify patterns of segmented assimilation and examine their relationships with physician trust, as well as the factors influencing physician trust among internal migrants in Shanghai. Results show four main patterns were revealed, namely first-generation classic assimilation, first-generation integrative assimilation, first-generation segmentation, and second-generation underclass assimilation, supporting the theory of segmented assimilation. Association between assimilation pattern and physician trust was observed. A relationship was found between assimilation patterns and trust in physicians. Migrants belonging to the first-generation classic and integrative assimilation groups exhibited a higher level of trust in doctors compared to those in the segmented assimilation groups. Additionally, undergraduate and postgraduate education attainment, an annual income of

Background: Pediatric pneumonia presents a significant global health challenge, particularly in low- and middle-income countries. This study aimed to investigate the incidence of pneumonia in preschool children in Urumqi and its association with indoor environmental factors. Methods: This case-control study collected data from December 2018 to December 2019 on 1522 preschool children in Urumqi (779 boys and 743 girls) who were diagnosed with pneumonia by a physician. A control group of children who had never had pneumonia was matched in a 1:1 ratio based on gender, age, and ethnicity. Using questionnaires, data were collected on children's general characteristics, passive smoking, types of housing, flooring materials, and indoor dampness, analyzing potential factors associated with the incidence of pediatric pneumonia. Results: Multivariate analysis revealed that cesarean birth (odds ratio [OR] = 1.27; 95 % confidence interval [95%CI] = 1.08–1.48), being an only child (OR = 1.32; 95%CI = 1.13–1.55), antibiotic treatment during the first year of life (OR = 2.51; 95%CI = 1.98–3.19), passive smoking during the mother's pregnancy (OR = 1.62; 95%CI = 1.24–2.13), living in multi-family apartment housing (OR = 1.64; 95%CI = 1.28–2.10) and other types of housing (OR = 1.47; 95%CI = 1.09–1.99), laminate flooring (OR = 1.31; 95%CI = 1.01–1.72), and tile/stone/cement flooring flooring (OR = 1.31; 95%CI = 1.06–1.61), and dampness in dwelling (during first year of mother's pregnancy) (OR = 1.30; 95%CI = 1.04–1.63) were risk factors for pediatric pneumonia. The use of fresh air filtration systems in children's residences (OR = 0.66; 95%CI = 0.50–0.86) was identified as a protective factor. Conclusion: This study underscores the importance of indoor environmental factors in the prevention of pediatric pneumonia. Public health strategies should consider these factors to reduce the incidence of pneumonia in children. Future research needs to be conducted over a broader geographical range and consider a more comprehensive range of factors influencing pediatric pneumonia.

BackgroundHealthcare resources are necessary for individuals to maintain their health. The Chinese government has implemented policies to optimize the allocation of healthcare resources and achieve the goal of equality in healthcare for the Chinese people since the implementation of the new medical reform in 2009. Given that no study has investigated regional differences from the perspective of healthcare resource agglomeration, this study aimed to investigate China’s healthcare agglomeration from 2009 to 2017 in China and identify its determinants to provide theoretical evidence for the government to develop and implement scientific and rational healthcare policies.MethodsThe study was conducted using 2009–2017 data to analyze health-resource agglomeration on institutions, beds, and workforce in China. An agglomeration index was applied to evaluate the degree of regional differences in healthcare resource allocation, and spatial econometric models were constructed to identify determinants of the spatial agglomeration of healthcare resources.ResultsFrom 2009 to 2017, all the agglomeration indexes of healthcare exhibited a downward trend except for the number of institutions in China. Population density (PD), government health expenditures (GHE), urban resident’s disposable income (URDI), geographical location (GL), and urbanization level (UL) all had positive significant effects on the agglomeration of beds, whereas both per capita health expenditures (PCHE), number of college students (NCS), and maternal mortality rate (MMR) had significant negative effects on the agglomeration of institutions, beds, and the workforce. In addition, population density (PD) and per capita gross domestic product (PCGDP) in one province had negative spatial spillover effects on the agglomeration of beds and the workforce in neighboring provinces. However, MMR had a positive spatial spillover effect on the agglomeration of beds and the workforce in those regions.ConclusionThe agglomeration of healthcare resources was observed to remain at an ideal level in China from 2009 to 2017. According to the significant determinants, some corresponding targeted measures for the Chinese government and other developing countries should be fully developed to balance regional disparities in the agglomeration of healthcare resources across administrative regions.

ObjectivesTo verify the healthy immigration effect on self-rated health (SRH) among Chinese internal migrants, identify the determinants of SRH, and provide recommendations for the Chinese government to formulate effective intervention strategies to improve population governance and health management in megacities.MethodsA sample comprising 1,147 white-and blue-collar migrant workers was randomly selected through an online survey conducted in Shanghai from August to December 2021. Multivariate logistic regression models were used to verify the healthy immigration effect as well as determinants of the effect among internal migrants in Shanghai.ResultsAmong 1,024 eligible internal migrants, 864 (84.4%) were aged between 18 and 59 years, 545 (53.2%) were men, and 818 (79.9%) were married. When confounders in the logistic regression models were adjusted, the odds ratio of SRH for internal migrants who had lived in Shanghai for 5–10 years was 2.418 (p

ObjectiveThe study aimed to measure time trends of inequalities of the geographical distribution of health facilities and workforce in Shanghai from 2010 to 2016 and used a spatial autocorrelation analysis method to precisely detect the priority areas for optimizing health resource reallocation in metropolises like Shanghai in developing countries.MethodsThe study used secondary data from the Shanghai Health Statistical Yearbook and the Shanghai Statistical Yearbook from 2011 to 2017. Five indicators on health resources, namely, health institutions, beds, technicians, doctors, and nurses, were employed to quantitatively measure the healthcare resource in Shanghai. The Theil index and the Gini coefficient were applied to assess the global inequalities in the geographic distribution of these resources in Shanghai. Global and local spatial autocorrelation was performed using global Moran's index and local Moran's index to illustrate the spatial changing patterns and identify the priority areas for two types of healthcare resource allocation.ResultsShanghai's healthcare resources showed decreasing trends of inequalities at large from 2010 to 2016. However, there still existed an unchanged over-concentration distribution in healthcare facilities and workforce density among districts in Shanghai, especially for doctors at the municipal level and facility allocation at the rural level. Through spatial autocorrelation analysis, it was found that there exhibited a significant spatial autocorrelation in the density distribution of all resources, and some identified priority areas were detected for resource re-allocation policy planning.ConclusionThe study identified the existence of inequality in some healthcare resource allocations in Shanghai from 2010 to 2016. Hence, more detailed area-specific healthcare resource planning and distribution policies are required to balance the health workforce distribution at the municipal level and institution distribution at the rural level, and particular geographical areas (low–low and low–high cluster areas) should be focused on and fully considered across all the policies and regional cooperation to ensure health equality for municipal cities like Shanghai in developing countries.

Abstract Background Breast cancer imposes a considerable burden on both the health care system and society, and becomes increasingly severe among women in China. To reduce the economic burden of this disease is crucial for patients undergoing the breast cancer surgery, hospital managers, and medical insurance providers. However, few studies have evidenced the prediction of the total hospital expenses (THE) for breast cancer surgery. The aim of the study is to predict THE for breast cancer surgery and identify the main influencing factors. Methods Data were retrieved from the first page of medical records of 3699 patients undergoing breast cancer surgery in one tertiary hospital from 2017 to 2018. Multiple liner regression (MLR), artificial neural networks (ANNs), and classification and regression tree (CART) were constructed and compared. Results The dataset from 3699 patients were randomly divided into training and test sets at a 70:30 ratio (2599 and 1100 records, respectively). The average total hospital expenses were 12520.54 ± 7844.88 ¥ (US$ 1929.20 ± 1208.11). MLR results revealed six factors to be significantly associated with THE: age, LOS, type of disease, having medical insurance, minimally invasive surgery, and receiving general anesthesia. After comparing three models, ANNs was the best model to predict THEs in patients undergoing breast cancer surgery, and its strong predictive performance was also validated. Conclusions To reduce the THEs, more attention should be paid to related factors of LOS, major and minimally invasive surgeries, and general anesthesia for these patient groups undergoing breast cancer surgery. This may reduce the information asymmetry between doctors and patients and provide more reliable cost, practical inpatient medical consumption standards and reimbursement standards reference for patients, hospital managers, and medical insurance providers ,respectively.

IntroductionIn confronting the sudden COVID-19 epidemic, China and other countries have been under great pressure to block virus transmission and reduce fatalities. Converting large-scale public venues into makeshift hospitals is a popular response. This addresses the outbreak and can maintain smooth operation of a country or region's healthcare system during a pandemic. However, large makeshift hospitals, such as the Shanghai New International Expo Center (SNIEC) makeshift hospital, which was one of the largest makeshift hospitals in the world, face two major problems: Effective and precise transfer of patients and heterogeneity of the medical care teams.MethodsTo solve these problems, this study presents the medical practices of the SNIEC makeshift hospital in Shanghai, China. The experiences include constructing two groups, developing a medical management protocol, implementing a multi-dimensional management mode to screen patients, transferring them effectively, and achieving homogeneous quality of medical care. To evaluate the medical practice performance of the SNIEC makeshift hospital, 41,941 infected patients were retrospectively reviewed from March 31 to May 23, 2022. Multivariate logistic regression method and a tree-augmented naive (TAN) Bayesian network mode were used.ResultsWe identified that the three most important variables were chronic disease, age, and type of cabin, with importance values of 0.63, 0.15, and 0.11, respectively. The constructed TAN Bayesian network model had good predictive values; the overall correct rates of the model-training dataset partition and test dataset partition were 99.19 and 99.05%, respectively, and the respective values for the area under the receiver operating characteristic curve were 0.939 and 0.957.ConclusionThe medical practice in the SNIEC makeshift hospital was implemented well, had good medical care performance, and could be copied worldwide as a practical intervention to fight the epidemic in China and other developing countries.

Background Physician trust is a critical determinant of the physician–patient relationship and is necessary for an effective health system. Few studies have investigated the association between acculturation and physician trust. Thus, this study analyzed the association between acculturation and physician trust among internal migrants in China by using a cross-sectional research design. Methods Of the 2000 adult migrants selected using systematic sampling, 1330 participants were eligible. Among the eligible participants, 45.71% were female, and the mean age was 28.50 years old (standard deviation = 9.03). Multiple logistic regression was employed. Results Our findings indicated that acculturation was significantly associated with physician trust among migrants. The length of stay (LOS), the ability of speaking Shanghainese, and the integration into daily life were identified as contributing factors for physician trust when controlling for all the covariates in the model. Conclusion We suggest that specific LOS-based targeted policies and culturally sensitive interventions can promote acculturation among Shanghai’s migrants and improve their physician trust.

Abstract Background The distribution of health-care resources is foundational to achieving fairness and having access to health service. China and its local Shanghai’s government have implemented measures to allocate health-care resources with the equity as one of the major goals since 2009-health-care reform. The aim of this study was to analyze differences in regional distribution and inequality in health-resource allocation on institutions, beds, and workforce in Shanghai over 7 years. Methods The study was conducted using 2010–2016 data to analyze health-resource allocation on institutions, beds, and workforce in Shanghai, China. The annual growth rate (AGR) was used to evaluate the time trends of health-care resource from 2010 to 2016, and Theil index was calculated to measure inequality of five indicators of health-care resource allocation during this study period. Results All quantities of health-care resources per 1000 people increased across Shanghai districts from 2010 to 2016. Compared with suburban districts, the central districts had higher ratios on five health-care resource indicators, and faster average growth in the bed and nurse indicator. The Theil of the indicators, except for doctors in hospitals, all exhibited downward time trends. Conclusions Regional difference between urban and rural areas and inequality between institution and workforce, especially for doctors, still existed. Some targeted measures including but not limited to income raising, facilitation of transportation conditions, investment of more fiscal funds, enhancement of health-care service provision for rural residents should be fully considered to narrow resource distribution gap between urban and rural districts and mitigate the inequality of health-care resource allocation.

ObjectiveTo investigate the effects of cell phone dependence (CPD) on mental health among undergraduates during the COVID-19 pandemic and further identify the determinants that may affect their mental health in China.MethodsThe data were collected from 602 students at a medical school in Shanghai via an online survey conducted from December 2021 to February 2022. The Mobile Phone Addiction Index (MPAI) and Depression Anxiety Stress Scale (DASS) were applied to evaluate CPD and mental health, respectively. Independent sample t-test and one-way analysis of variance (ANOVA) were employed to compare the means of continuous variables among categorical groups. Correlations between continuous variables were detected using Pearson's correlation analysis. Univariable and multivariable logistic regressions were employed to identify the determinants of mental health.ResultsAmong the 402 eligible students, 73.88% were women with an average age of 20.19 ± 2.36 years. On average, the DASS score was 32.20 ± 11.07, the CPD score was 36.23 ± 11.89, and the cell phone use duration was 7.67 ± 3.61 h/day. CPD was found to have a negative effect on mental health among college students in Shanghai. Additionally, cell phone use duration, age, being senior students, faculty-student relationship, insomnia, tobacco use, obesity, and life satisfaction were clarified as contributing factors to mental health among college students.ConclusionHigh degree of CPD could have a negative effect on college students' mental health, which might lead to some psychological problems. Appropriate actions and effective interventions are highly needed to prevent severe psychological injuries among college students in China.

Objectives To analyse differences in regional distribution and inequality in health-resource allocation at the hospital and primary health centre (PHC) levels in Shanghai over 7 years.Design A longitudinal survey using 2010–2016 data, which were collected for analysis.Setting The study was conducted at the hospital and PHC levels in Shanghai, China.Outcome measures Ten health-resource indicators were used to measure health-resource distribution at the hospital and PHC levels. In addition, the Theil Index was calculated to measure inequality in health-resource allocation.Results All quantities of healthcare resources per 1000 people in hospitals and PHCs increased across Shanghai districts from 2010 to 2016. Relative to suburban districts, the central districts had higher ratios, both in terms of doctors and equipment, and had faster growth in the doctor indicator and slower growth in the equipment indicator in hospitals and PHCs. The Theil Indices of all health-resource allocation in hospitals had higher values compared with those in PHCs every year from 2010 to 2016; furthermore, the Theil Indices of the indicators, except for technicians and doctors in hospitals, all exhibited downward time trends in hospitals and PHCs.Conclusions Increased healthcare resources and reduced inequality of health-resource allocation in Shanghai during the 7 years indicated that measures taken by the Shanghai government to deepen the new round of healthcare reform in China since 2009 had been successful. Meanwhile there still existed regional difference between urban and rural areas and inequality across different medical institutions. To solve these problems, we prescribe increased wages, improved working conditions, and more open access to career development for doctors and nurses; reduced investments in redundant equipment in hospitals; and other incentives for balancing the health workforce between hospitals and PHCs.

Objectives To analyse differences in regional distribution and inequality in health-resource allocation at the hospital and primary health centre (PHC) levels in Shanghai over 7 years. Design A longitudinal survey using 2010–2016 data, which were collected for analysis. setting The study was conducted at the hospital and PHC levels in Shanghai, China. Outcome measures Ten health-resource indicators were used to measure health-resource distribution at the hospital and PHC levels. In addition, the Theil Index was calculated to measure inequality in health-resource allocation. results All quantities of healthcare resources per 1000 people in hospitals and PHCs increased across Shanghai districts from 2010 to 2016. Relative to suburban districts, the central districts had higher ratios, both in terms of doctors and equipment, and had faster growth in the doctor indicator and slower growth in the equipment indicator in hospitals and PHCs. The Theil Indices of all health-resource allocation in hospitals had higher values compared with those in PHCs every year from 2010 to 2016; furthermore, the Theil Indices of the indicators, except for technicians and doctors in hospitals, all exhibited downward time trends in hospitals and PHCs. Conclusions Increased healthcare resources and reduced inequality of health-resource allocation in Shanghai during the 7 years indicated that measures taken by the Shanghai government to deepen the new round of healthcare reform in China since 2009 had been successful. Meanwhile there still existed regional difference between urban and rural areas and inequality across different medical institutions. To solve these problems, we prescribe increased wages, improved working conditions, and more open access to career development for doctors and nurses; reduced investments in redundant equipment in hospitals; and other incentives for balancing the health workforce between hospitals and PHCs. [ABSTRACT FROM AUTHOR]