Objective: This study applied the vulnerability framework and examined the combined effect of race and income on health insurance coverage in the US. Data source: The household component of the US Medical Expenditure Panel Survey (MEPS-HC) of 2017 was used for the study. Study design: Logistic regression models were used to estimate the associations between insurance coverage status and vulnerability measure, comparing insured with uninsured or insured for part of the year, insured for part of the year only, and uninsured only, respectively. Data collection/extraction methods: We constructed a vulnerability measure that reflects the convergence of predisposing (race/ethnicity), enabling (income), and need (self-perceived health status) attributes of risk. Principal findings: While income was a significant predictor of health insurance coverage (a difference of 6.1–7.2% between high- and low-income Americans), race/ethnicity was independently associated with lack of insurance. The combined effect of income and race on insurance coverage was devastating as low-income minorities with bad health had 68% less odds of being insured than high-income Whites with good health. Conclusion: Results of the study could assist policymakers in targeting limited resources on subpopulations likely most in need of assistance for insurance coverage. Policymakers should target insurance coverage for the most vulnerable subpopulation, i.e., those who have low income and poor health as well as are racial/ethnic minorities.

In China, most people tend to use hospitals rather than health centers for their primary care generally due to the perception that quality of care provided in the hospital setting is superior to that provided at the health centers. No studies have been conducted in China to compare the quality of primary care provided at different health care settings. The purpose of this study is to compare the quality of primary care provided in different types of health care facilities in China. A cross-sectional survey with patients was conducted in Guangdong province of China, using the validated Chinese Primary Care Assessment Tool (PCAT). ANOVA was performed to compare the overall and 10 domains of primary care quality for patients in tertiary, secondary, and primary health care settings. Multivariate analyses were used to assess the association between types of facility and quality of primary care attributes while controlling for sociodemographic and health care characteristics. The final number of respondents was 864 including 161 from county hospitals, 190 from rural community health centers (CHCs), 164 from tertiary hospitals, 80 from secondary hospitals, and 269 from urban CHCs. Type of health care facilities was significantly associated with total PCAT score and domain scores. CHC was associated with higher total PCAT score and scores for first contact-access, ongoing care, comprehensiveness-services available, and community orientation than secondary and/or tertiary hospitals, after controlling for patients’ demographic and health characteristics. Higher PCAT score was associated with greater satisfaction with primary care received. CHC patients were more likely to report satisfactory experiences compared to patients from secondary and tertiary facilities. The study demonstrated that CHCs provided better quality primary care when compared with secondary and tertiary health care facilities, justifying CHCs as a model of primary care delivery.

This study examined the impact of an Integrated Care Delivery intervention on health care seeking and outcomes for chronically-ill patients in Henan province, China. A case-control study was carried out in six health care organizations from two counties in Henan province, China. 371 patients aged 50 years or over with hypertension or diabetes who visited either community health centers or hospitals in the Intervention or Control Counties were systematically selected and surveyed on health care seeking behavior, quality of care, and pathway of care for their major chronic condition. Bivariate analyses were performed to compare quality and value of care indicators between patients from the Intervention and Control Counties. Multivariate analyses were used to confirm these associations after controlling for patients’ demographic and health characteristics. Patients in both the Intervention and Control Counties chose their current health care providers primarily out of concern for quality of care (provider expertise and adequate medical equipment) and patient-centered care. Compared with the patients from the Control County, those from the Intervention County performed significantly better on almost all the quality and value of care indicators even after controlling for patients’ demographic and health characteristics. Significant associations between types of health care facilities and quality as well as value of care were also observed. The study showed that the Integrated Care Delivery Model was critical in guiding patients’ health care seeking behavior and associated with improved accessibility, continuity, coordination and comprehensiveness of care, as well as reducing health inequities and mitigating disparities for older patients with chronic conditions.

Reform of the health care system in urban areas of China has prompted concerns about the utilization of Community Health Centers (CHC). This study examined which of the dominant primary care delivery models, i.e., the public CHC model, the ‘gate-keeper’ CHC model, or the hospital-owned CHC models, was most effective in enhancing access to and quality of care for patients with chronic illness. The case-comparison design was used to study nine health care organizations in Guangzhou, Dongguan, and Shenzhen cities within Guangdong province, China. 560 patients aged 50 or over with hypertension or diabetes who visited either CHCs or hospitals in these three cities were surveyed by using face-to-face interviews. Bivariate analyses were performed to compare quality and value of care indicators among subjects from the three cities. Multivariate analyses were used to assess the association between type of primary care delivery and quality as well as value of chronic care after controlling for patients’ demographic and health status characteristics. Patients from all three cities chose their current health care providers primarily out of concern for quality of care (both provider expertise and adequate medical equipment), patient-centered care, and insurance plan requirement. Compared with patients from Guangzhou, those from Dongguan performed significantly better on most quality and value of care indicators. Most of these indicators remained significantly better even after controlling for patients' demographic and health status characteristics. The Shenzhen model (hospital-owned and -managed CHC) was generally effective in enhancing accessibility and continuity. However, coordination suffered due to seemingly duplicating primary care outpatients at the hospital setting. Significant associations between types of health care facilities and quality of care were also observed such that patients from CHCs were more likely to be satisfied with traveling time and follow-up care by their providers. The study suggested that the Dongguan model (based on insurance mandate and using family practice physicians as ‘gate-keepers’) seemed to work best in terms of improving access and quality for patients with chronic conditions. The study suggested adequately funded and well-organized primary care system can play a gatekeeping role and has the potential to provide a reasonable level of care to patients.

Background: Pervasive differences in cancer screening among race/ethnicity and insurance groups presents a challenge to achieving equitable healthcare access and health outcomes. However, the change in the magnitude of cancer screening disparities over time has not been thoroughly examined using recent public health survey data. Methods: A retrospective cross-sectional analysis of the 2008 and 2018 National Health Interview Survey (NHIS) database focused on breast, cervical, and colorectal cancer screening rates among race/ethnicity and insurance groups. Multivariable logistic regression models were used to assess the relationship between cancer screening rates, race/ethnicity, and insurance coverage, and to quantify the changes in disparities in 2008 and 2018, adjusting for potential confounders. Results: Colorectal cancer screening rates increased for all groups, but cervical and mammogram rates remained stagnant for specific groups. Non-Hispanic Asians continued to report consistently lower odds of receiving cervical tests (OR: 0.42, 95% CI: 0.32–0.55, p<0.001) and colorectal cancer screening (OR: 0.55, 95% CI: 0.42–0.72, p<0.001) compared to non-Hispanic Whites in 2018, despite significant improvements since 2008. Non-Hispanic Blacks continued to report higher odds of recent cervical cancer screening (OR: 1.98, 95% CI: 1.47–2.68, p<0.001) and mammograms (OR: 1.32, 95% CI: 1.02–1.71, p<0.05) than non-Hispanic Whites in 2018, consistent with higher odds observed in 2008. Hispanic individuals reported improved colorectal cancer screening over time, with no significant difference compared to non-Hispanics Whites in 2018, despite reporting lower odds in 2008. The uninsured status was associated with significantly lower odds of cancer screening than private insurance for all three cancers in 2008 and 2018. Conclusion: Despite an overall increase in breast and colorectal cancer screening rates between 2008 and 2018, persistent racial/ethnic and insurance disparities exist among race/ethnicity and insurance groups. These findings highlight the importance of addressing underlying factors contributing to disparities among underserved populations and developing corresponding interventions.