Does Hospital Location Matter? association of Neighborhood Socioeconomic Disadvantage With Hospital Quality in Us Metropolitan Settings

An aspect of a hospital\u27s location, such as its degree of socioeconomic disadvantage, could potentially affect quality ratings of the hospital; yet, few studies have granularly explored this relationship in United States (US) metropolitan areas characterized by a wide breadth of socioeconomic disparities across neighborhoods. An understanding of the effect of neighborhood socioeconomic disadvantage on hospital quality of care is informative for targeting resources in poor neighborhoods. We assessed the association of neighborhood socioeconomic disadvantage with hospital quality of care across several areas of quality (including mortality, readmission, safety, patient experience, effectiveness of care, summary and overall star rating) in US metropolitan areas. Hospitals in the most disadvantaged neighborhoods, compared to hospitals in the least disadvantaged neighborhoods, had worse mortality scores, readmission scores, safety of care scores, patient experience of care scores, effectiveness of care scores, summary scores and overall star rating. Timeliness of care and efficient use of imaging scores were not strongly associated with neighborhood socioeconomic disadvantage; although, future studies are needed to validate this finding. Policymakers could target innovative strategies for improving neighborhood socioeconomic conditions in more disadvantaged areas, as this may improve hospital quality

Treatment of latent Mycobacterium tuberculosis infection with 12 once weekly directly-observed doses of isoniazid and rifapentine among persons experiencing homelessness.

ObjectivesTo investigate treatment outcomes and associated characteristics of persons experiencing homelessness who received 12-weekly doses of directly observed isoniazid and rifapentine (3HP/DOT) treatment for latent TB infection (LTBI).MethodsAmong homeless persons treated with 3HP/DOT during July 2011 -June 2015 in 11 U.S. TB programs, we conducted descriptive analyses of observational data, and identified associations between sociodemographic factors and treatment outcomes. Qualitative interviews were conducted to understand programmatic experiences.ResultsOf 393 persons experiencing homelessness (median age: 50 years; range: 13-74 years), 301 (76.6%) completed treatment, 55 (14.0%) were lost to follow-up, 18 (4.6%) stopped because of an adverse event (AE), and 19 (4.8%) stopped after relocations or refusing treatment. Eighty-one (20.6%) had at least one AE. Persons aged ≥65 were more likely to discontinue treatment than persons aged 31-44 years. Programs reported difficulty in following up with persons experiencing homelessness because of relocations, mistrust, and alcohol or drug use.ConclusionsThis study demonstrates the feasibility of administering the 3HP/DOT LTBI regimen to persons experiencing homelessness, a high-risk population

Neighborhood deprivation and morbid obesity: Insights from the Houston Methodist Cardiovascular Disease Health System Learning Registry

This study examined the relationship between a validated measure of socioeconomic deprivation, such as the Area Deprivation Index (ADI), and morbid obesity. We used cross-sectional data on adult patients (≥18 years) in the Houston Methodist Cardiovascular Disease Health System Learning Registry (located in Houston, Texas, USA) between June 2016 and July 2021. Each patient was grouped by quintiles of ADI, with higher quintiles signaling greater deprivation. BMI was calculated using measured height and weight with morbid obesity defined as ≥ 40 kg/m2. Multivariable logistic regression models were used to examine the association between ADI and morbid obesity adjusting for demographic (age, sex, and race/ethnicity) factors. Out of the 751,174 adults with an ADI ranking included in the analysis, 6.9 % had morbid obesity (n = 51,609). Patients in the highest ADI quintile had a higher age-adjusted prevalence (10.9 % vs 3.3 %), and about 4-fold odds (aOR, 3.8; 95 % CI = 3.6, 3.9) of morbid obesity compared to the lowest ADI quintile. We tested for and found interaction effects between ADI and each demographic factor, with stronger ADI-morbid obesity association observed for patients that were female, Hispanic, non-Hispanic White and 40–65 years old. The highest ADI quintile also had a high prevalence (44 %) of any obesity (aOR, 2.2; 95 % CI = 2.1, 2.2). In geospatial mapping, areas with higher ADI were more likely to have higher proportion of patients with morbid obesity. Census-based measures, like the ADI, may be informative for area-level obesity reduction strategies as it can help identify neighborhoods at high odds of having patients with morbid obesity

Cumulative social disadvantage and health-related quality of life: national health interview survey 2013–2017

Abstract Background Evidence for the association between social determinants of health (SDoH) and health-related quality of life (HRQoL) is largely based on single SDoH measures, with limited evaluation of cumulative social disadvantage. We examined the association between cumulative social disadvantage and the Health and Activity Limitation Index (HALex). Methods Using adult data from the National Health Interview Survey (2013–2017), we created a cumulative disadvantage index by aggregating 47 deprivations across 6 SDoH domains. Respondents were ranked using cumulative SDoH index quartiles (SDoH-Q1 to Q4), with higher quartile groups being more disadvantaged. We used two-part models for continuous HALex scores and logistic regression for poor HALex (< 20th percentile score) to examine HALex differences associated with cumulative disadvantage. Lower HALex scores implied poorer HRQoL performance. Results The study sample included 156,182 respondents, representing 232.8 million adults in the United States (mean age 46 years; 51.7% women). The mean HALex score was 0.85 and 17.7% had poor HALex. Higher SDoH quartile groups had poorer HALex performance (lower scores and increased prevalence of poor HALex). A unit increase in SDoH index was associated with − 0.010 (95% CI [-0.011, -0.010]) difference in HALex score and 20% higher odds of poor HALex (odds ratio, OR = 1.20; 95% CI [1.19, 1.21]). Relative to SDoH-Q1, SDoH-Q4 was associated with HALex score difference of -0.086 (95% CI [-0.089, -0.083]) and OR = 5.32 (95% CI [4.97, 5.70]) for poor HALex. Despite a higher burden of cumulative social disadvantage, Hispanics had a weaker SDoH-HALex association than their non-Hispanic White counterparts. Conclusions Cumulative social disadvantage was associated with poorer HALex performance in an incremental fashion. Innovations to incorporate SDoH-screening tools into clinical decision systems must continue in order to accurately identify socially vulnerable groups in need of both clinical risk mitigation and social support. To maximize health returns, policies can be tailored through community partnerships to address systemic barriers that exist within distinct sociodemographic groups, as well as demographic differences in health perception and healthcare experience

Social Determinants of Cardiovascular Risk, Subclinical Cardiovascular Disease, and Cardiovascular Events

Background Although there is research on the impact of social determinants of health (SDOHs) on cardiovascular health, most existing evidence is based on individual SDOH components. We evaluated the impact of cumulative SDOH burden on cardiovascular risk factors, subclinical atherosclerosis, and incident cardiovascular disease events. Methods and Results We included 6479 participants from the MESA (Multi‐Ethnic Study of Atherosclerosis). A weighted aggregate SDOH score representing the cumulative number of unfavorable SDOHs, identified from 14 components across 5 domains (economic stability, neighborhood and physical environment, community and social context, education, and health care system access) was calculated and divided into quartiles (quartile 4 being the least favorable). The impact of cumulative SDOH burden on cardiovascular risk factors (hypertension, diabetes, dyslipidemia, smoking, and obesity), systemic inflammation, subclinical atherosclerosis, and incident cardiovascular disease was evaluated. Increasing social disadvantage was associated with increased odds of all cardiovascular risk factors except dyslipidemia. Smoking was the risk factor most strongly associated with worse SDOH (odds ratio [OR], 2.67 for quartile 4 versus quartile 1 [95% CI, 2.13–3.34]). Participants within SDOH quartile 4 had 33% higher odds of increased high‐sensitivity C‐reactive protein (OR, 1.33 [95% CI, 1.11–1.60]) and 31% higher risk of all cardiovascular disease (hazard ratio, 1.31 [95% CI, 1.03–1.67]), yet no greater burden of subclinical atherosclerosis (OR, 1.01 [95% CI, 0.79–1.29]), when compared with those in quartile 1. Conclusions Increasing social disadvantage was associated with more prevalent cardiovascular risk factors, inflammation, and incident cardiovascular disease. These findings call for better identification of SDOHs in clinical practice and stronger measures to mitigate the higher SDOH burden among the socially disadvantaged to improve cardiovascular outcomes

Hospitalization and survival of solid organ transplant recipients with coronavirus disease 2019: A propensity matched cohort study.

BackgroundSolid organ transplant (SOT) recipients are predicted to have worse COVID-19 outcomes due to their compromised immunity. However, this association remains uncertain because published studies have had small sample sizes and variability in chronic comorbidity adjustment.MethodsIn this retrospective cohort study conducted at a multihospital health system, we compared COVID-19 outcomes and survival up to 60 days following hospital admission in SOT recipients taking baseline immunosuppressants versus hospitalized control patients.ResultsThe study included 4,562 patients who were hospitalized with COVID-19 (108 SOT recipients and 4,454 controls) from 03/2020 to 08/2020. Mortality at 60 days was higher for SOT recipients (17% SOT vs 10% control; unadjusted odds ratio (OR) = 1.74, 95% confidence interval (CI) 1.04-2.91, P = 0.04). We then conducted a 1:5 propensity matched cohort analysis (100 SOT recipients; 500 controls) using age, sex, race, body mass index, hypertension, diabetes, chronic kidney disease, liver disease, admission month, and area deprivation index. Within 28 days of admission, SOT recipients had fewer hospital-free days (median; 17 SOT vs 21 control; OR = 0.64, 95%CI 0.46-0.90, P = 0.01) but had similar ICU-free days (OR = 1.20, 95%CI 0.72-2.00, P = 0.49) and ventilator-free days (OR = 0.91, 95%CI 0.53-1.57, P = 0.75). There was no statistically significant difference in 28-day mortality (9% SOT vs 12% control; OR = 0.76, 95%CI 0.36-1.57, P = 0.46) or 60-day mortality (16% SOT vs 14% control; OR = 1.15, 95%CI 0.64-2.08, P = 0.64).ConclusionsHospitalized SOT recipients appear to need additional days of hospital care but can achieve short-term mortality outcomes from COVID-19 that are similar to non-SOT recipients in a propensity matched cohort study