Table_1_Perceptions of the benefits of the basic medical insurance system among the insured: a mixed methods research of a northern city in China.DOC

BackgroundThe perceptions of the benefits of the basic medical insurance system among the insured not only reflect the system's performance but also the public's basic medical insurance policy literacy, valuable information for countries that have entered the stage of deepening reform. This study aims to examine the factors that affect the perceptions of the benefits of the basic medical insurance system in China, diagnose the key problems, and propose corresponding measures for improvement.MethodsA mixed method design was used. Data for the quantitative study were obtained from a cross-sectional questionnaire survey (n = 1,045) of residents of Harbin who had enrolled for basic medical insurance system. A quota sampling method was further adopted. A multivariate logistic regression model was then employed to identify the factors influencing the perceptions of the benefits of the basic medical insurance system, followed by semi-structured interviews with 30 conveniently selected key informants. Interpretative phenomenological analysis was used to analyze the interview data.ResultsApproximately 44% of insured persons reported low perceptions of benefits. The logistic regression model showed that low perceptions of the benefits of the basic medical insurance system was positively correlated with the experience of daily drug purchases (OR = 1.967), perceptions of recognition with basic medical insurance system (OR = 1.948), perceptions of the financial burden of participation costs (OR = 1.887), perceptions of the convenience of using basic medical insurance for medical treatment (OR = 1.770), perceptions of the financial burden of daily drug purchases costs (OR = 1.721), perceptions of the financial burden of hospitalization costs (OR = 1.570), and type of basic medical insurance system (OR = 1.456). The results of the qualitative analysis showed that the key problem areas of perceptions of the benefits of the basic medical insurance system were: (I) system design of basic medical insurance; (II) intuitive cognition of the insured; (III) rational cognition of the insured; and (IV) the system environment.ConclusionsImproving the perceptions of the benefits of the basic medical insurance system of the insured requires joint efforts in improving system design and implementation, exploring effective publicity methods of basic medical insurance system information, supporting public policy literacy, and promoting the health system environment.</p

Patient Satisfaction with Hospital Inpatient Care: Effects of Trust, Medical Insurance and Perceived Quality of Care

<div><p>Objective</p><p>Deteriorations in the patient-provider relationship in China have attracted increasing attention in the international community. This study aims to explore the role of trust in patient satisfaction with hospital inpatient care, and how patient-provider trust is shaped from the perspectives of both patients and providers.</p><p>Methods</p><p>We adopted a mixed methods approach comprising a multivariate logistic regression model using secondary data (1200 people with inpatient experiences over the past year) from the fifth National Health Service Survey (NHSS, 2013) in Heilongjiang Province to determine the associations between patient satisfaction and trust, financial burden and perceived quality of care, followed by in-depth interviews with 62 conveniently selected key informants (27 from health and 35 from non-health sectors). A thematic analysis established a conceptual framework to explain deteriorating patient-provider relationships.</p><p>Findings</p><p>About 24% of respondents reported being dissatisfied with hospital inpatient care. The logistic regression model indicated that patient satisfaction was positively associated with higher level of trust (OR = 14.995), lower levels of hospital medical expenditure (OR = 5.736–1.829 as compared with the highest quintile of hospital expenditure), good staff attitude (OR = 3.155) as well as good ward environment (OR = 2.361). But patient satisfaction was negatively associated with medical insurance for urban residents and other insurance status (OR = 0.215–0.357 as compared with medical insurance for urban employees). The qualitative analysis showed that patient trust—the most significant predictor of patient satisfaction—is shaped by perceived high quality of service delivery, empathic and caring interpersonal interactions, and a better designed medical insurance that provides stronger financial protection and enables more equitable access to health care.</p><p>Conclusion</p><p>At the core of high levels of patient dissatisfaction with hospital care is the lack of trust. The current health care system reform in China has yet to address the fundamental problems embedded in the system that caused distrust. A singular focus on doctor-patient inter-personal interactions will not offer a successful solution to the deteriorated patient-provider relationships unless a systems approach to accountability is put into place involving all stakeholders.</p></div

Independent variables and coding for regression modeling.

<p>Independent variables and coding for regression modeling.</p

Characteristics of respondents and overall satisfaction towards hospital inpatient care (n = 1200).

<p>Characteristics of respondents and overall satisfaction towards hospital inpatient care (n = 1200).</p

Logistic regression analysis on inpatients’ overall satisfaction.

<p>Logistic regression analysis on inpatients’ overall satisfaction.</p

Conceptual framework of patients’ distrust in care providers.

<p>Conceptual framework of patients’ distrust in care providers.</p

Table_1_Epidemiological trend in scarlet fever incidence in China during the COVID-19 pandemic: A time series analysis.DOCX

ObjectiveOver the past decade, scarlet fever has caused a relatively high economic burden in various regions of China. Non-pharmaceutical interventions (NPIs) are necessary because of the absence of vaccines and specific drugs. This study aimed to characterize the demographics of patients with scarlet fever, describe its spatiotemporal distribution, and explore the impact of NPIs on the disease in the era of coronavirus disease 2019 (COVID-19) in China.MethodsUsing monthly scarlet fever data from January 2011 to December 2019, seasonal autoregressive integrated moving average (SARIMA), advanced innovation state-space modeling framework that combines Box-Cox transformations, Fourier series with time-varying coefficients, and autoregressive moving average error correction method (TBATS) models were developed to select the best model for comparing between the expected and actual incidence of scarlet fever in 2020. Interrupted time series analysis (ITSA) was used to explore whether NPIs have an effect on scarlet fever incidence, while the intervention effects of specific NPIs were explored using correlation analysis and ridge regression methods.ResultsFrom 2011 to 2017, the total number of scarlet fever cases was 400,691, with children aged 0–9 years being the main group affected. There were two annual incidence peaks (May to June and November to December). According to the best prediction model TBATS (0.002, {0, 0}, 0.801, {}), the number of scarlet fever cases was 72,148 and dual seasonality was no longer prominent. ITSA showed a significant effect of NPIs of a reduction in the number of scarlet fever episodes (β2 = −61526, P ConclusionsThe incidence of scarlet fever during COVID-19 was lower than expected, and the total incidence decreased by 80.74% in 2020. The results of this study indicate that strict NPIs may be of potential benefit in preventing scarlet fever occurrence, especially that related to public event cancellation. However, it is still important that vaccines and drugs are available in the future.</p

Additional file 1 of Spatial effects of air pollution on the economic burden of disease: implications of health and environment crisis in a post-COVID-19 world

Additional file 1: Appendix Fig. 1. The robustness test results of AQI related results