Emerging from the epidemiological transition and accelerated aging process, China's fragmentated healthcare systems struggle to meet the demands of the population. On Sept 1st 2017, China's National Health and Family Planning Commission encouraged all cities to learn from the Luohu model of integration adopted in Luohu as an approach to meeting these challenges. In this paper, we study the integration process, analyze the core mechanisms, and conduct preliminary evaluations of integrated policy development in the Luohu model. The Luohu hospital group was established in Aug 2015, consists of five district hospitals, 23 community health stations and an institute of precision medicine. The group adopted a series of professional, organizational, system, functional and normative strategies for integrated care, which was provided for the residents of Luohu, especially for the elderly population and patients with chronic conditions. According to a preliminary evaluation of the past two years, the Luohu model showed improvement in the structure and process towards integrated care. New preventive programs conducted in the hospital group resulted in changes of disease incidence. Residents were more satisfied with the Luohu model. However, spending exceeded the global budget for health insurance because of short-term increases in the demand for health care. First, engagement of multiple stakeholders is essential for the design and implementation of reform. Second, organizational integration is a prerequisite for integrated care in China. Third, effective care integration requires alignment with payment reforms. Fourth, normative integration could promote collaboration in an integrated healthcare system. Core strategies and mechanisms of the Luohu model will promote integrated care in urban China and other countries facing the same challenges. However, it is necessary to study the effects of the Luohu model over the long term and continue to strive for integrated care.

Background: There is evidence that multidisciplinary teams can improve health outcomes for patients with chronic conditions, enhance the quality and coordination of care, and promote teamwork among staff in hospital settings. However, their effectiveness in non-hospital settings remains unclear. Therefore, we conducted a systematic review and meta-analysis to assess the effects of multidisciplinary teams on patients with chronic conditions, health professionals, and healthcare in non-hospital settings. Methods: We searched PubMed, Web of Science, Embase, EconLit, OpenGrey, China National Knowledge Infrastructure (CNKI), and WanFang for randomised controlled trials published before March 2025. Narrative syntheses were used to synthesise the characteristics of multidisciplinary teams, interventions, and effects. Data were statistically pooled using both random-effects and fixed-effects meta-analyses to synthesize the outcomes. The methodological quality of the included studies was assessed using Cochrane’s risk of bias tool. Results: Thirty-nine studies were analyzed, with a total of 8186 participants. Nurses, general practitioners, and specialists were the most common members of the multidisciplinary teams. Staffing models, shared care and role expansion or task shifting are the most common multidisciplinary teamwork interventions. Narrative syntheses revealed improvements in self-management, self-efficiency, satisfaction, health behaviours, and knowledge. A meta-analysis found a significant reduction in hospitalisation days for patients with chronic obstructive pulmonary disease (MD=-0.66, 95% CI -1.05 to -0.26, I² = 0%) and significant improvement in quality of life for patients with chronic heart failure (MD=-4.63, 95% CI: -8.67 to -0.60, I² = 0%). There is no consistent evidence of other indicators of this effect. Conclusions: Multidisciplinary teamwork can improve patient-reported outcomes for patients with chronic conditions in non-hospital settings, but the effects on clinical outcomes, health utilisation, and costs are not evident. Trial registration: The study protocol was registered with PROSPERO on January 21, 2019, with the registration number CRD42019121109.

We study the effect of gambling culture in the province where a firm is located on its bond yield spread. Our findings suggest that a high gambling culture translates into a high bond yield spread. In addition, the impact is more salient for firms with high operating volatility and increased default risk. Overall, the results are consistent with the notion that when firms are located in high gambling culture provinces, they are riskier, and thus bond investors ask for a high bond yield.

Background: The original Rainbow Model of Integrated Care Measurement Tool (RMIC-MT) is based on the Rainbow Model of Integrated Care (RMIC), which provides a comprehensive theoretical framework for integrated care. To translate and adapt the original care provider version of the RMIC-MT and evaluate its psychometric properties by a pilot study in Chinese primary care systems. Methods: The translation and adaptation process were performed in four steps, forward and back-translation, experts review and pre-testing. We conducted a cross-sectional study with 1610 community care professionals in all 79 community health stations in the Nanshan district. We analyzed the distribution of responses to each item to study the psychometric sensitivity. Exploratory factor analysis with principal axis extraction method and promax rotation was used to assess the construct validity. Cronbach’s alpha was utilized to ascertain the internal consistency reliability. Lastly, confirmation factor analysis was used to evaluate the exploratory factor analysis model fit. Results: During the translation and adaptation process, all 48 items were retained with some detailed modifications. No item was found to have psychometric sensitivity problems. Six factors (person- & community-centeredness, care integration, professional integration, organizational integration, cultural competence and technical competence) with 45 items were determined by exploratory factor analysis, accounting for 61.46% of the total variance. A standard Cronbach’s alpha of 0.940 and significant correlation among all items in the scale (> 0.4) showed good internal consistency reliability of the tool. And, the model passed the majority of goodness-to-fit test by confirmation factor analysis. Conclusions: The results showed initial satisfactory psychometric properties for the validation of the Chinese RMIC-MT provider version. Its application in China will promote the development of people-centered integrated primary care. However, further psychometric testing is needed in multiple primary care settings with both public and private community institutes.

Objectives: Fragmented healthcare in China cannot meet the needs of the growing number of type 2 diabetes patients. The World Health Organization proposed an integrated primary care approach to address the needs of patients with chronic conditions. This study aims to measure type 2 diabetes patients’ preferences for urban integrated primary care in China. Methods: A discrete choice experiment was designed to measure type 2 diabetes patient preferences for seven priority attributes of integrated care. A two-stage sampling survey of 307 type 2 diabetes mellitus (T2DM) patients in 16 community health stations was carried out. Interviews were conducted to explore the reasons underpinning the preferences. A logit regression model was used to estimate patients’ willingness to pay and to analyze the expected impact of potential policy changes. Results: Travel time to care providers and experience of care providers are the most valued attributes for respondents rather than out-of-pocket cost. Attention to personal situation, the attentiveness of care providers, and the friendliness and helpfulness of staff were all related to interpersonal communication between patients and health care providers. Accurate health information and multidisciplinary care were less important attributes. Conclusions: The study provides an insight into type 2 diabetes patients’ needs and preferences of integrated primary care. People-centered interventions, such as increasing coverage by family doctor and cultivating mutual continuous relationships appear to be key priorities of policy and practice in China.

The original Rainbow Model of Integrated Care Measurement Tool (RMIC-MT) is based on the Rainbow Model of Integrated Care (RMIC), which provides a comprehensive theoretical framework for integrated care. The aim of this paper is to modify the original patient version of the RMIC-MT for the Chinese primary care context and validate its psychometric properties. The translation and adaptation processes were performed in four steps, forward and back-translation, experts review and pre-testing. We conducted a cross-sectional study with 386 patients with diabetes attending one of 20 community health stations in the Nanshan district. We analyzed the distribution of responses to each item to study the psychometric sensitivity. Exploratory factor analysis with principal axis extraction method was used to assess the construct validity. Confirmation factor analysis was used to evaluate model fit of the modified version. Cronbach’s alpha was used to ascertain the internal consistency reliability. During the translation and adaptation process, all 24 items were retained with some detailed modifications. No item was found to have psychometric sensitivity problems. Five factors (person-centeredness, clinical integration, professional integration, team-based coordination, organizational integration) with 15 items were determined by exploratory factor analysis, accounting for 53.51% of the total variance. Good internal consistency was achieved with each item correlated the highest on an assigned subscale and Cronbach’s alpha score of 0.890. Moderately positive associations (r≥ 0.4, p<0.01) between the score of the scale and these correlations indicate good construct validity. The results showed initial satisfactory psychometric properties for the validation of the Chinese RMIC-MT patient version. Its application in China will promote the development of people-centered integrated primary care. However, future studies with diverse samples crossing regions would be needed to test its psychometric properties for the various Chinese primary care contexts.