Health Uninsurance in rural America: a partial equilibrium analysis

Social Determinants of Health and Surgical Desirability of Outcome Ranking in Older Veterans

Importance

Evaluating how social determinants of health (SDOH) influence veteran outcomes is crucial, particularly for quality improvement.

Objective

To measure associations between SDOH, care fragmentation, and surgical outcomes using a Desirability of Outcome Ranking (DOOR).

Design, Setting, And Participants

This was a cohort study of US veterans using data from the Veterans Affairs (VA) Surgical Quality Improvement Program (VASQIP; 2013-2019) limited to patients aged 65 years or older with inpatient stays between 2 and 30 days, merged with multiple data sources, including Medicare. Race and ethnicity data were retrieved from VASQIP, Medicare and Medicaid beneficiary summary files, the Veterans Health Administration Corporate Data Warehouse, and the United States Veterans Eligibility Trends and Statistics file. Data were analyzed between September 2023 and February 2024.

Exposure

Living in a highly deprived neighborhood (Area Deprivation Index >85), race and ethnicity used as a social construct, rurality, and care fragmentation (percentage of non-VA care days).

Main Outcomes and Measures

DOOR is a composite, patient-centered ranking of 26 outcomes ranging from no complication (1, best) to 90-day mortality or near-death complications (6, worst). A series of proportional odds regressions was used to assess the impact of SDOH and care fragmentation adjusted for clinical risk factors, including presentation acuity (presenting with preoperative acute serious conditions and urgent or emergent surgical procedures).

Results

The cohort had 93 644 patients (mean [SD] age, 72.3 [6.2] years; 91 443 [97.6%] male; 74 624 [79.7%] White). Veterans who identified as Black (adjusted odds ratio [aOR], 1.06; 95% CI, 1.02-1.10; P = .048) vs White and veterans with higher care fragmentation (per 20% increase in VA care days relative to all care days: aOR, 1.01; 95% CI, 1.01-1.02; P < .001) were associated with worse (higher) DOOR scores until adjusting for presentation acuity. Living in rural geographic areas was associated with better DOOR scores than living in urban areas (aOR, 0.93; 95% CI, 0.91-0.96; P < .001), and rurality was associated with lower presentation acuity (preoperative acute serious conditions: aOR, 0.88; 95% CI, 0.81-0.95; P = .001). Presentation acuity was higher in veterans identifying as Black, living in deprived neighborhoods, and with increased care fragmentation.

Conclusions and Relevance

Veterans identifying as Black and veterans with greater proportions of non-VA care had worse surgical outcomes. VA programs should direct resources to reduce presentation acuity among Black veterans, incentivize veterans to receive care within the VA where possible, and better coordinate veterans' treatment and records between care sources.

Factors associated with the enrollment of commercial medical insurance in China: Results from China General Social Survey

BACKGROUND

The Chinese government has been promoting commercial medical insurance (CMI) in recent decades as it plays an increasingly important role in addressing disease burden, health inequities, and other healthcare challenges. However, compared with developed countries, the CMI is still less fledged with low coverage.

OBJECTIVE

This study aims to explore the factors associated with enrollment in CMI, with regards to explicit characteristics (including sociodemographic characteristics and family economic status), latent characteristics (including social security status), and the global incentive compatibility index (including health status), to inform the design of CMI to improve its coverage in China.

METHODS

Based on the principal-agent model, we summarized and classified the factors associated with the enrollment in CMI, and then analyzed the data generated from the Chinese General Social Survey in 2015,2018 and 2021 respectively. A comparison of factors regarding sociodemographic characteristics, family economic status, social security status, and health status was conducted between individuals enrolled and unenrolled in CMI using Mann-Whitney U test and Chi-square test. Binary logistic regression analysis was used to explore factors influencing the enrollment status of CMI.

RESULTS

Of all individuals, the proportion of enrolled individuals shows an increasing trend year by year, with 8.7%,11.8% and 14.1% enrolled in CMI in 2015,2018 and 2021, respectively. The binary regression analysis further suggested that the factors associated with the enrollment in CMI were consistent in 2015,2018 and 2021.We found that individuals divorced, obese, who had a higher level of education, had non-agricultural household registration, perceived themselves as the upper social status, conducted daily exercise, had more family houses, had a car, had investment activities, or did not have basic health insurance were more likely to be enrolled in CMI.

CONCLUSIONS

We identified multidimensional factors associated with the enrollment of CMI, which help inform the government and insurance industry to improve the coverage of CMI.