Social Determinants of Health and 90-Day Mortality After Hospitalization for Heart Failure in the REGARDS Study

The Efficacy and Safety of Levosimendan in Patients with Advanced Heart Failure: An Updated Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Intermittent ambulatory levosimendan administration has been shown in several small randomized controlled trials to benefit patients with advanced heart failure, preventing heart failure rehospitalization and mortality. We aim to investigate the totality of high-quality evidence regarding the efficacy and safety of intermittent levosimendan in advanced heart failure patients.

METHODS

Up to September 2023, we systematically reviewed the randomized controlled trials indexed in PubMed, Embase Cochrane, SCOPUS, and Web of Science. We used mean difference (MD) to estimate the continuous outcomes, and risk ratio (RR) for the dichotomous outcomes with a 95% confidence interval (CI), using the random-effects model. Ultimately, a trial sequential analysis was employed to enhance the reliability of our findings and Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework for certainty leveling.

RESULTS

Fifteen randomized controlled trials with 1181 patients were included. Intermittent levosimendan was significantly associated with an improved left ventricular ejection fraction compared with  placebo (MD 6.39 [95% CI 3.04-9.73], P = 0.002; I2 = 75, P = 0.0005), with cumulative z-score of change after ≤ 1 week passing the monitoring boundaries, favoring the levosimendan, but did not cross the required information size. Additionally, levosimendan reduced the all-cause mortality rate (RR 0.60 [95% CI 0.40-0.90], P = 0.01; I2 = 9, P = 0.36). However, we found no difference between levosimendan and placebo in all-cause rehospitalization rate (RR 0.75 [95% CI 0.46-1.22], P = 0.25; I2 = 70, P = 0.04), event-free survival rate (RR 0.97 [95% CI 0.72-1.30], P = 0.84; I2 = 63, P = 0.03), or any adverse event (RR 1 [95% CI 0.73-1.37], P = 1.00, I2 = 0%, P = 0.70).

CONCLUSION

In patients with advanced heart failure, intermittent levosimendan significantly improved left ventricular ejection fraction, brain natriuretic peptide values, and all-cause mortality rate. Levosimendan use is not associated with a change in rehospitalization or event-free survival.

REGISTRATION

PROSPERO identifier number (CRD42023487838).

Cardiovascular disease and cancer: shared risk factors and mechanisms

Cardiovascular disease (CVD) and cancer are among the leading causes of morbidity and mortality globally, and these conditions are increasingly recognized to be fundamentally interconnected. In this Review, we present the current epidemiological data for each of the modifiable risk factors shared by the two diseases, including hypertension, hyperlipidaemia, diabetes mellitus, obesity, smoking, diet, physical activity and the social determinants of health. We then review the epidemiological data demonstrating the increased risk of CVD in patients with cancer, as well as the increased risk of cancer in patients with CVD. We also discuss the shared mechanisms implicated in the development of these conditions, highlighting their inherent bidirectional relationship. We conclude with a perspective on future research directions for the field of cardio-oncology to advance the care of patients with CVD and cancer.

Development and validation of mortality prediction models based on the social determinants of health

BACKGROUND

There is no standardised approach to screening adults for social risk factors. The goal of this study was to develop mortality risk prediction models based on the social determinants of health (SDoH) for clinical risk stratification.

METHODS

Data were used from REasons for Geographic And Racial Differences in Stroke (REGARDS) study, a national, population-based, longitudinal cohort of black and white Americans aged ≥45 recruited between 2003 and 2007. Analysis was limited to participants with available SDoH and mortality data (n=20 843). All-cause mortality, available through 31 December 2018, was modelled using Cox proportional hazards with baseline individual, area-level and business-level SDoH as predictors. The area-level Social Vulnerability Index (SVI) was included for comparison. All models were adjusted for age, sex and sampling region and underwent internal split-sample validation.

RESULTS

The baseline prediction model including only age, sex and REGARDS sampling region had a c-statistic of 0.699. An individual-level SDoH model (Model 1) had a higher c-statistic than the SVI (0.723 vs 0.708, p<0.001) in the testing set. Sequentially adding area-level SDoH (c-statistic 0.723) and business-level SDoH (c-statistics 0.723) to Model 1 had minimal improvement in model discrimination. Structural racism variables were associated with all-cause mortality for black participants but did not improve model discrimination compared with Model 1 (p=0.175).

CONCLUSION

In conclusion, SDoH can improve mortality prediction over 10 years relative to a baseline model and have the potential to identify high-risk patients for further evaluation or intervention if validated externally.

Pain, Return to Community Status, and 90-Day Mortality Among Hospitalized Patients With Heart Failure

BACKGROUND

Pain is common among patients with heart failure but has not been examined with short-term discharge outcomes. The purpose was to examine whether pain at discharge predicts return to community status and 90-day mortality among hospitalized patients with heart failure.

METHODS

Data from medical records of 2169 patients hospitalized with heart failure were analyzed in this retrospective cohort study. The independent variable was a diagnosis of pain at discharge. Outcomes were return to community status (yes/no) and 90-day mortality. Logistic regression was used to address aims. Covariates included age, gender, race, vital signs, comorbid symptoms, comorbid conditions, cardiac devices, and length of stay.

RESULTS

The sample had a mean age of 66.53 years, and was 57.4% women and 55.9% Black. Of 2169 patients, 1601 (73.8%) returned to community, and 117 (5.4%) died at or before 90 days. Patients with pain returned to community less frequently (69.6%) compared with patients without pain (75.2%), which was a statistically significant relationship (odds ratio, 0.74; 95% confidence interval, 0.57-0.97; P = .028). Other variables that predicted return to community status included age, comorbid conditions, dyspnea, fatigue, systolic blood pressure, and length of stay. Pain did not predict increased 90-day mortality. Variables that predicted mortality included age, liver disease, and systolic blood pressure.

CONCLUSION

Patients with pain were less likely to return to community but did not have higher 90-day mortality. Pain in combination with other symptoms and comorbid conditions may play a role in mortality if acute pain versus chronic pain can be stratified in a future study.

Identifying social determinants of health from clinical narratives: A study of performance, documentation ratio, and potential bias

OBJECTIVE

To develop a natural language processing (NLP) package to extract social determinants of health (SDoH) from clinical narratives, examine the bias among race and gender groups, test the generalizability of extracting SDoH for different disease groups, and examine population-level extraction ratio.

METHODS

We developed SDoH corpora using clinical notes identified at the University of Florida (UF) Health. We systematically compared 7 transformer-based large language models (LLMs) and developed an open-source package - SODA (i.e., SOcial DeterminAnts) to facilitate SDoH extraction from clinical narratives. We examined the performance and potential bias of SODA for different race and gender groups, tested the generalizability of SODA using two disease domains including cancer and opioid use, and explored strategies for improvement. We applied SODA to extract 19 categories of SDoH from the breast (n = 7,971), lung (n = 11,804), and colorectal cancer (n = 6,240) cohorts to assess patient-level extraction ratio and examine the differences among race and gender groups.

RESULTS

We developed an SDoH corpus using 629 clinical notes of cancer patients with annotations of 13,193 SDoH concepts/attributes from 19 categories of SDoH, and another cross-disease validation corpus using 200 notes from opioid use patients with 4,342 SDoH concepts/attributes. We compared 7 transformer models and the GatorTron model achieved the best mean average strict/lenient F1 scores of 0.9122 and 0.9367 for SDoH concept extraction and 0.9584 and 0.9593 for linking attributes to SDoH concepts. There is a small performance gap (∼4%) between Males and Females, but a large performance gap (>16 %) among race groups. The performance dropped when we applied the cancer SDoH model to the opioid cohort; fine-tuning using a smaller opioid SDoH corpus improved the performance. The extraction ratio varied in the three cancer cohorts, in which 10 SDoH could be extracted from over 70 % of cancer patients, but 9 SDoH could be extracted from less than 70 % of cancer patients. Individuals from the White and Black groups have a higher extraction ratio than other minority race groups.

CONCLUSIONS

Our SODA package achieved good performance in extracting 19 categories of SDoH from clinical narratives. The SODA package with pre-trained transformer models is available at https://github.com/uf-hobi-informatics-lab/SODA_Docker.

The role of comorbidities, medications, and social determinants of health in understanding urban-rural outcome differences among patients with heart failure

PURPOSE

There is now a 20% disparity in all-cause, excess deaths between urban and rural areas, much of which is driven by disparities in cardiovascular death. We sought to explain the sources of these disparities for Medicare beneficiaries with heart failure with reduced ejection fraction (HFrEF).

METHODS

Using a sample of Medicare Parts A, B, and D, we created a cohort of 389,528 fee-for-service beneficiaries with at least 1 heart failure hospitalization from 2008 to 2017. The primary outcome was 30-day mortality after discharge; 1-year mortality, readmissions, and return emergency room (ER) admissions were secondary outcomes. We used hierarchical, logistic regression modeling to determine the contribution of comorbidities, guideline-directed medical therapy (GDMT), and social determinants of health (SDOH) to outcomes.

RESULTS

Thirty-day mortality rates after hospital discharge were 6.3% in rural areas compared to 5.7% in urban regions (P < .001); after adjusting for patient health and GDMT receipt, the 30-day mortality odds ratio for rural residence was 1.201 (95% CI 1.164-1.239). Adding the SDOH measure reduced the odds ratio somewhat (1.140, 95% CI 1.103-1.178) but a gap remained. Readmission rates in rural areas were consistently lower for all model specifications, while ER admissions were consistently higher.

CONCLUSIONS

Among patients with HFrEF, living in a rural area is associated with an increased risk of death and return ER visits within 30 days of discharge from HF hospitalization. Differences in SDOH appear to partially explain mortality differences but the remaining gap may be the consequence of rural-urban differences in HF treatment.

Social associations and cardiovascular mortality in the United States counties, 2016 to 2020

BACKGROUND

The positive aspects of social interaction on health have been described often, with considerably less attention to their negative aspect. This study aimed to assess the impact of social associations on cardiovascular mortality in the United States.

METHODS

The Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) data sets from 2016 to 2020 were used to identify death records due to cardiovascular disease in the United States population aged 15 years and older. The social association rate defined as membership associations per 10,000 population, accessed from the 2020 County Health Rankings data was used as a surrogate for social participation. All United States counties were grouped into quartiles based on their social association rate; Q1 being the lowest quartile of social association, and Q4 the highest quartile. Age-adjusted mortality rate (AAMR) was calculated for each quartile. County health factor rankings for the state of Texas were used to adjust the AAMR for baseline comorbidities of county population, using Gaussian distribution linear regression.

RESULTS

Overall, the AAMR was highest in the 4th social association rate quartile (306.73 [95% CI, 305.72-307.74]) and lowest in the 1st social association rate quartile (266.80 [95% CI, 266.41-267.20]). The mortality rates increased in a linear pattern from lowest to highest social association rate quartiles. After adjustment for the county health factor ranks of Texas, higher social association rate remained associated with a significantly higher AAMR (coefficient 15.84 [95% CI, 12.78-18.89]).

CONCLUSIONS

Our study reported higher cardiovascular AAMR with higher social associations in the United States, with similar results after adjustment for County Health Rankings in the state of Texas.

Association of educational attainment with cancer mortality in a national cohort study of black and white adults: A mediation analysis

Background

Low educational attainment is associated with excess cancer mortality. However, the mechanisms driving this association remain unknown.

Methods

Using data from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study, we evaluated the associations of participant and parental/caregiver education with cancer mortality using Cox proportional hazards models, adjusting for socio-demographic characteristics and health conditions. We used principal components analysis to generate indices of measures representing the social determinants of health (SDOH) and health behaviors. We used structural equation modeling to determine if the association between educational attainment and cancer mortality was mediated by these domains.

Results

Among 30,177 REGARDS participants included in this analysis, 3798 (12.6%) had less than a high school degree. In fully adjusted models, those without a high school education experienced about 50% greater risk of death than high school graduates and higher (White participants HR: 1.47; 95% CI: 1.23, 1.76 and Black HR: 1.54; 95% CI: 1.33, 1.79). There was evidence of a modest mediation effect for the association between education and cancer mortality by the SDOH domain score (White total effect HR: 1.25; 95% CI: 1.18, 1.33, indirect effect HR: 1.04; 95% CI: 1.03, 1.05, direct effect HR: 1.21; 95% CI: 1.14, 1.28 and Black total effect HR: 1.24; 95% CI: 1.18, 1.29, indirect effect HR: 1.04; 95% CI: 1.03, 1.05, direct effect HR: 1.19; 95% CI: 1.14, 1.24). There was no evidence of mediation by the health behaviors score. No significant associations were found for female caregiver/mother's or male caregiver/father's education (N = 13,209).

Conclusions

In conclusion, participant education was strongly associated with cancer mortality, and this association was partially mediated by the SDOH domain score.

Social Determinants of Health in Women With Heart Failure: Prospective Observational Cohort Study

Objective

The social determinants of health (SDoH) account for 80%-90% of modifiable contributors to health outcomes for chronic diseases such as heart failure. Knowledge gaps exist on how SDoH influences hospitalization rates in women with heart failure. Our aim was to evaluate the relationship between the baseline SDoH status of women with heart failure with subsequent all-cause and cardiovascular hospitalization.

Methods

This is a prospective observational longitudinal cohort study of women diagnosed with heart failure with 6-month follow-up. The subjects completed SDoH assessment by the Institute of Medicine. Monthly follow-ups were performed to assess for hospitalization events.

Results

A total of 92 patients with at least 1 follow-up clinic visit were included. The mean age was 66 ± 15 years and 80% had nonischemic cardiomyopathy as the etiology of heart failure. New York Heart Association (NYHA) Classifications I-II were the most common (n = 66, 71.8%). In total, 51 patients (55.4%) had overall high-risk SDoH (4 or more SDoH domains at risk). By the 6-month follow-up, 22 (23.9%) patients were hospitalized for any cause; 8 patients (8.7%) were hospitalized for cardiovascular causes. There were no deaths. In multivariate logistic regression analysis, the high-risk SDoH group had a higher odds ratio for all-cause hospitalization (OR 5.31, 95% CI 1.59-17.73). In addition, Kansas City Cardiomyopathy Questionnaire 12-item (KCCQ-12) scores, surrogate for quality of life, were worse in the high-risk SDoH group.

Conclusion

SDoH adversely impacts hospitalizations and quality of life in women with heart failure. Future efforts for screening and interventions should evaluate the SDoH at all levels, including the individual health care provider, institutional, and national levels.

Social Determinants of Health and Cardiologist Involvement in the Care of Adults Hospitalized for Heart Failure

Importance

Involvement of a cardiologist in the care of adults during a hospitalization for heart failure (HF) is associated with reduced rates of in-hospital mortality and hospital readmission. However, not all patients see a cardiologist when they are hospitalized for HF.

Objective

To determine whether social determinants of health (SDOH) are associated with cardiologist involvement in the management of adults hospitalized for HF.

Design, Setting, and Participants

This retrospective cohort study used data from the Reasons for Geographic and Racial Difference in Stroke (REGARDS) cohort. Participants included adults who experienced an adjudicated hospitalization for HF between 2009 and 2017 in all 48 contiguous states in the US. Data analysis was performed from November 2022 to January 2023.

Exposures

A total of 9 candidate SDOH, aligned with the Healthy People 2030 conceptual model, were examined: Black race, social isolation, social network and/or caregiver availability, educational attainment less than high school, annual household income less than $35 000, living in rural area, living in a zip code with high poverty, living in a Health Professional Shortage Area, and living in a state with poor public health infrastructure.

Main Outcomes and Measures

The primary outcome was cardiologist involvement, defined as involvement of a cardiologist as the primary responsible clinician or as a consultant. Bivariate associations between each SDOH and cardiologist involvement were examined using Poisson regression with robust SEs.

Results

The study included 1000 participants (median [IQR] age, 77.8 [71.5-84.0] years; 479 women [47.9%]; 414 Black individuals [41.4%]; and 492 of 876 with low income [56.2%]) hospitalized at 549 unique US hospitals. Low annual household income (<$35 000) was the only SDOH with a statistically significant association with cardiologist involvement (relative risk, 0.88; 95% CI, 0.82-0.95). In a multivariable analysis adjusting for age, race, sex, HF characteristics, comorbidities, and hospital characteristics, low income remained inversely associated with cardiologist involvement (relative risk, 0.89; 95% CI, 0.82-0.97).

Conclusions and Relevance

This cohort study found that adults with low household income were 11% less likely than adults with higher incomes to have a cardiologist involved in their care during a hospitalization for HF. These findings suggest that socioeconomic status may bias the care provided to patients hospitalized for HF.

Determinants of Health and Outcomes in Medicare Recipients With Heart Disease: A Population Study

CONTEXT

Heart disease (HD) is a primary cause of mortality and morbidity in the United States. While there is a growing body of evidence demonstrating the contribution of social determinants of health (SDoH) to HD outcomes, the impact of combined or individual SDoH on health-related quality of life (HRQoL) in patients with HD is not well understood.

OBJECTIVES

To analyze the National Health and Aging Trends Study (NHATS) to explore the relationship of SDoH with HRQoL, advance care planning, and treatment preferences in Medicare beneficiaries with HD.

METHODS

The study design was a secondary data analysis using latent class analysis (LCA) and multivariable analysis of NHATS participants with HD, Round 8, that included End of Life Plans and Care questions.

RESULTS

1202 participants, median age 81 years, 57% female, 70% non-Hispanic White, 20% non-Hispanic Black, 10% Other. LCA identified two SDoH risk profiles (low/high), using 12 measures within the NHATS Economic and Social Consequences key concept area. The high-risk SDoH profile participants were more likely to have fair/poor HRQoL, and identify as female, non-White (P < 0.0001); and less likely to have completed advance care planning (P < 0.0001). High-risk SDoH participants were more likely to want life-prolonging treatments (P < 0.0001), however, this association was not significant after adjusting for age, sex, and race (P = 0.344).

CONCLUSION

Higher risk SDoH profiles are associated with reduced HRQoL, reduced advance care planning completion, female sex, and non-White race in a cohort of Medicare beneficiaries. These findings provide opportunities to improve SDoH-related care practices in older patients with HD.

Evaluating Social Determinants of Health Domains and Their Predictive Validity Within Black/African American and White Older Adults From the ACTIVE Trial

OBJECTIVE

To assess domains of social determinants of health (SDoH) and their associations with cognition and quality of life.

METHOD

This investigation uses baseline data from individuals participating in the ACTIVE trial (n = 2505) to reproduce the SDoH domains described in Healthy People 2030 (economic stability, health care, education, neighborhood and built environment, and social and community context). Results: Results support using data from the ACTIVE trial to assess all five SDoH domains, and the ability of the composites to predict baseline performance on measures of cognition and self-reported quality of life within a sample of older adults. Additionally, higher SDoH domain scores were associated with better functioning on composite measures of cognition and higher scores for mental and general health-related quality of life with Access to Healthcare associated with all outcomes. Discussion: These findings can inform investigators interested in assessing multiple domains of SDoH and highlight the importance of access to health care within older Black/African American and White older adults.

The association between social determinants of health and patient-centred outcomes in adults with heart failure with reduced ejection fraction

AIMS

To explore the associations between social determinants of health and patient-centred outcomes among adults with chronic heart failure with reduced ejection fraction.

DESIGN

Cross-sectional online self-report survey.

METHODS

A survey assessing social determinants of health (demographics, socio-economic position, affordability of care and social support) and patient-centred outcomes, including the Kansas City Cardiomyopathy Questionnaire-12 and validated measures of medication adherence, treatment satisfaction, treatment burden and mental health, was completed by 512 adults with chronic heart failure with a reduced ejection fraction between 06 March and 29 June 2020. Multivariable analyses included linear and logistic regression.

RESULTS

Female gender, having a care partner, and being offered financial assistance with medications were associated with worse health status, while perceiving medication as affordable and being married were associated with better health status. Females and having Medicaid, dual Medicaid/Medicare or no medical insurance were associated with a higher likelihood of depression, and non-white race/ethnicity was associated with less depression. Medication adherence was lower in patients having a care partner and offered financial assistance. Patients being offered financial and medication management assistance were more likely to be overwhelmed by the treatment burden, whereas those having some college education were less so.

CONCLUSIONS

Social determinants of health are associated with patients' disease-specific health status, mental health and treatment satisfaction and burden. These findings underscore the importance of assessing social determinants of health in clinical practice and the need for developing and testing novel strategies to determine whether they improve patients' health.

IMPACT

The relationship between social determinants of health- and patient-centred outcomes was assessed; affordability of care and social support factors were most strongly associated with outcomes for patients with chronic heart failure and reduced ejection fraction, underscoring the importance of assessing social determinants of health in routine clinical care.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

Social determinants of health data could potentially inform care delivery for patients with heart failure and reduced ejection fraction by helping to identify those who require additional support to manage their symptoms, access care and adhere to treatment. Social support and affordability of treatment were associated with most patient-centred outcomes, suggesting these factors may provide clinicians with an indicator of a patient's level of general well-being that could be assessed during routine follow-up care.

REPORTING METHOD

This research followed the STROBE checklist for cross-sectional studies.

PATIENT OR PUBLIC CONTRIBUTION

Adults who have heart failure with reduced ejection fraction that consented to participate in the study provided the data used for all analyses reported on in the manuscript. Service users, caregivers or members of the public had no involvement in the study.

Allostatic load and incident heart failure in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study

BACKGROUND

Allostatic load (AL) is the physiologic "wear and tear" on the body from stress. Yet, despite stress being implicated in the development heart failure (HF), it is unknown whether AL is associated with incident HF events.

METHODS

We examined 16,765 participants without HF at baseline from the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. The main exposure was AL score quartile. AL was determined according to 11 physiologic parameters, whereby each parameter was assigned points (0-3) based on quartiles within the sample, and points were summed to create a total AL score ranging from 0-33. The outcome was incident HF event. We examined the association between AL quartile (Q1-Q4) and incident HF events using Cox proportional hazards models, adjusted for demographics, socioeconomic factors, and lifestyle.

RESULTS

The mean age was 64 ± 9.6 years, 61.5% were women, and 38.7% were Black participants. Over a median follow up of 11.4 years, we observed 750 incident HF events (635 HF hospitalizations and 115 HF deaths). Compared to the lowest AL quartile (Q1), the fully adjusted hazards of an incident HF event increased in a graded fashion: Q2 HR 1.49 95% CI 1.12-1.98; Q3 HR 2.47 95% CI 1.89-3.23; Q4 HR 4.28 95% CI 3.28-5.59. The HRs for incident HF event in the fully adjusted model that also adjusted for CAD were attenuated, but remained significant and increased in a similar, graded fashion by AL quartile. There was a significant age interaction (p-for-interaction < 0.001), whereby the associations were observed across each age stratum, but the HRs were highest among those aged < 65 years.

CONCLUSION

AL was associated with incident HF events, suggesting that AL could be an important risk factor and potential target for future interventions to prevent HF.

Relationship between socioeconomic status and cognitive ability among Chinese older adults: the moderating role of social support

BACKGROUND

Understanding the causes and pathways of cognitive decline among older populations is of great importance in China. This study aims to examine whether the discrepancy in socioeconomic status (SES) makes a difference to the cognitive ability among Chinese older adults, and to disentangle the moderating role of different types of social support in the process in which SES influences cognition.

METHODS

We utilized a nationally representative sample from the 2018 Chinese Longitudinal Healthy Longevity Survey. A cumulative SES score was constructed to measure the combined effect of different socioeconomic statuses on the cognitive ability of the elderly. We further examined the moderating role of two types of social support, including emotional support, and financial support. Hierarchical regression analysis was applied to test the direct effect of SES on cognitive ability, and to investigate the moderating role of social support on the association of the SES with the dependent variables.

RESULTS

The results showed that the higher SES of older adults was significantly associated with better cognitive ability (β = 0.52, p < 0.001) after controlling for age, sex, marital status, living region, Hukou, health insurance, lifestyle factors, and physical health status. Emotional support and financial support were moderated the relationship between SES score and cognitive ability.

CONCLUSION

Our results reveal the importance of considering social support in buffering the effects of SES and the associated cognitive ability for aging populations. It highlights the importance of narrowing the socioeconomic gap among the elderly. Policymakers should consider promoting social support to improve the cognitive ability among older adults.

Social Determinants of Health and Cardiologist Involvement in the Care of Adults Hospitalized for Heart Failure

Introduction

The involvement of a cardiologist in the care of adults during a hospitalization for heart failure (HF) is associated with reduced rates of in-hospital mortality and hospital readmission. However, not all patients see a cardiologist when they are hospitalized for HF. Since reasons for this are not entirely clear, we sought to determine whether social determinants of health (SDOH) are associated with cardiologist involvement in the management of adults hospitalized for HF. We hypothesized that SDOH would be inversely associated with cardiologist involvement in the care of adults hospitalized for HF.

Methods

We included adult participants from the national REasons for Geographic And Racial Difference in Stroke (REGARDS) cohort, who experienced an adjudicated hospitalization for HF between 2009 and 2017. We excluded participants who were hospitalized at institutions that lacked cardiology services (n=246). We examined nine candidate SDOH, which align with the Healthy People 2030 conceptual model: Black race, social isolation (0-1 visits from a family or friend in the past month), social network/caregiver availability (having someone to care for them if ill), educational attainment < high school, annual household income < $35,000, living in rural areas, living in a zip code with high poverty, living in a Health Professional Shortage Area, and residing in a state with poor public health infrastructure. The primary outcome was cardiologist involvement, a binary variable which was defined as involvement of a cardiologist as the primary responsible clinician or as a consultant, collected via chart review. We examined associations between each SDOH and cardiologist involvement using Poisson regression with robust standard errors. Candidate SDOH with statistically significant associations (p<0.10) were retained for multivariable analysis. Potential confounders/covariates for the multivariable analysis included age, race, sex, HF characteristics, comorbidities, and hospital characteristics.

Results

We examined 876 participants hospitalized at 549 unique US hospitals. The median age was 77.5 years (IQR 71.0-83.7), 45.9% were female, 41.4% were Black, and 56.2% had low income. Low household income (<$35,000/year) was the only SDOH that had a statistically significant association with cardiologist involvement in a bivariate analysis (RR: 0.88 [95% CI: 0.82-0.95]). After adjusting for potential confounders, low income remained inversely associated (RR: 0.89 [95% CI: 0.82-0.97]).

Conclusions

Adults with low household income were 11% less likely to have a cardiologist involved in their care during a hospitalization for HF. This suggests that socioeconomic status may implicitly bias the care provided to patients hospitalized for HF.

Influence of Social Determinants of Health on Heart Failure Outcomes: A Systematic Review

Background Prior research suggests an association between clinical outcomes in heart failure (HF) and social determinants of health (SDoH). Because providers should identify and address SDoH in care delivery, we evaluated how SDoH have been defined, measured, and evaluated in studies that examine HF outcomes. Methods and Results Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, databases were searched for observational or interventional studies published between 2009 and 2021 that assessed the influence of SDoH on outcomes. Selected articles were assessed for quality using a validated rating scheme. We identified 1373 unique articles for screening; 104 were selected for full-text review, and 59 met the inclusion criteria, including retrospective and prospective cohort, cross-sectional, and intervention studies. The majority examined readmissions and hospitalizations (k=33), mortality or survival (k=29), and success of medical devices and transplantation (k=8). SDoH examined most commonly included race, ethnicity, age, sex, socioeconomic status, and education or health literacy. Studies used a range of 1 to 9 SDoH as primary independent variables and 0 to 7 SDoH as controls. Multiple data sources were employed and frequently were electronic medical records linked with national surveys and disease registries. The effects of SDoH on HF outcomes were inconsistent because of the heterogeneity of data sources and SDoH constructs. Conclusions Our systematic review reveals shortcomings in measurement and deployment of SDoH variables in HF care. Validated measures need to be prospectively and intentionally collected to facilitate appropriate analysis, reporting, and replication of data across studies and inform the design of appropriate, evidence-based interventions that can ameliorate significant HF morbidity and societal costs.

Cumulative Social Disadvantage and All-Cause Mortality in the United States: Findings from a National Study

The extent to which cumulative social disadvantage-defined as aggregate social risk resulting from multiple co-occurring adverse social determinants of health (SDOH)-affects the risk of all-cause mortality, independent of demographic and clinical risk factors, is not well understood. The objective of this study was to examine the association between cumulative social disadvantage, measured using a comprehensive 47-factor SDOH framework, and mortality in a nationally representative sample of adults in the United States. The authors conducted secondary analysis of pooled data for 63,540 adult participants of the 2013-2015 National Death Index-linked National Health Interview Survey. Age-adjusted mortality rates (AAMRs) were reported by quintiles of aggregate SDOH burden, with higher quintiles denoting greater social disadvantage. Cox proportional hazards models were used to examine the association between cumulative social disadvantage and risk of all-cause mortality. AAMR increased significantly with greater SDOH burden, ranging from 631 per 100,000 person-years (PYs) for participants in SDOH-Q1 to 1490 per 100,000 PYs for those in SDOH-Q5. In regression models adjusted for demographics, being in SDOH-Q5 was associated with 2.5-fold higher risk of mortality, relative to Q1 (adjusted hazard ratio [aHR] = 2.57 [95% confidence interval, CI = 1.94-3.41]); the observed association persisted after adjusting for comorbidities, with over 2-fold increased risk of mortality for SDOH-Q5 versus Q1 (aHR = 2.02 [95% CI = 1.52-2.67]). These findings indicate that cumulative social disadvantage is associated with increased risk of all-cause mortality, independent of demographic and clinical factors. Population level interventions focused on improving individuals' social, economic, and environmental conditions may help reduce the burden of mortality and mitigate persistent disparities.

Readmission rates and predictors of avoidable readmissions in older adults in a tertiary care centre

Context

Thirty-day readmissions are used to gauge health care accountability, which occurs as part of the natural course of the illness or due to avoidable fallacies during the index admission. The utility of this metric is unknown in older adults from developing countries.

Aim

To ascertain the unplanned 30-day readmission rate and enumerate predictors of avoidable hospital readmission among early (0-7 days) and late (8-30 days) readmissions.

Settings and Design

A retrospective chart audit of 140 older adults who were readmitted to a premier tertiary care teaching hospital under Geriatrics from the neighboring states of Tamil Nadu, Andhra Pradesh, and Kerala were undertaken.

Methods and Materials

Data from health records were collected from the hospital electronic database from May 2015 to May 2020. The data was reviewed to determine the 30-day readmission rate and to ascertain the predictors of avoidable readmissions among both early and late readmissions.

Results

Out of 2698 older adults admitted to the geriatric wards from the catchment areas, the calculated 30-day hospital readmission rate was 5.18%, and 41.4% of these readmissions were potentially avoidable. The median duration from discharge to the first readmission was ten days (Interquartile range: 5-18 days). Patients had to spend INR 44,000 (approximately 602 USD) towards avoidable readmission. The most common causes for readmission included an exacerbation, reactivation, or progression of a previously existing disease (55.7%), followed by the emergence of a new disease unrelated to index admission (43.2%). Fifty-eight patients (41.4%) were readmitted within seven days following discharge. Early readmissions were seen in patients with malignancies [8 (13.5%) vs. 4 (4.8%); P = 0.017], on insulin (P = 0.04) or on antidepressants (P = 0.01). Advanced age was found to be an independent predictor of avoidable early readmission (OR 2.99 95%CI 1.34-6.62, P = 0.007), and admission to a general ward (as compared to those admitted in a private ward) was an independent predictor of early readmissions (OR 2.99 95%CI 1.34-6.62, P = 0.007).

Conclusion

The 30-day readmission rate in a geriatric unit in a tertiary care hospital was 5.2%. Advanced age was considered to be an independent predictor of avoidable early readmission. Future prospective research on avoidable readmissions should be undertaken to delineate factors affecting 30-day avoidable hospital readmissions in developing nations.

Depressive symptoms, cognitive impairment, and all-cause mortality among REGARDS participants with heart failure

Aims

To ascertain whether depressive symptoms and cognitive impairment (CI) are associated with mortality among patients with heart failure (HF), adjusting for sociodemographic, comorbidities, and biomarkers.

Methods and results

We utilized Medicare-linked data from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study, a biracial prospective ongoing cohort of 30 239 US community-dwelling adults, recruited in 2003-07. HF diagnosis was ascertained in claims analysis. Depressive symptoms were defined as a score ≥4 on the four-item Center for Epidemiological Studies-Depression scale. Cognitive impairment was defined as a score of ≤4 on the six-item screener that assessed three-item recall and orientation to year, month, and day of the week. Sequentially adjusted Cox proportional hazard models were used to estimate the risk of death. We analyzed 1059 REGARDS participants (mean age 73, 48%-African American) with HF; of those 146 (14%) reported depressive symptoms, 136 (13%) had CI and 31 (3%) had both. Over the median follow-up of 6.8 years (interquartile range, 3.4-10.3), 785 (74%) died. In the socio-demographics-adjusted model, CI was significantly associated with increased mortality, hazard ratio 1.24 (95% confidence interval 1.01-1.52), compared with persons with neither depressive symptoms nor CI, but this association was attenuated after further adjustment. Neither depressive symptoms alone nor their comorbidity with CI was associated with mortality. Risk factors of all-cause mortality included: low income, comorbidities, smoking, physical inactivity, and severity of HF.

Conclusion

Depressive symptoms, CI, or their comorbidity was not associated with mortality in HF in this study. Treatment of HF in elderly needs to be tailored to cognitive status and includes focus on medical comorbidities.

Demographic and social determinants of cognitive dysfunction following hospitalization for COVID-19

BACKGROUND

Persistent cognitive symptoms have been reported following COVID-19 hospitalization. We investigated the relationship between demographics, social determinants of health (SDOH) and cognitive outcomes 6-months after hospitalization for COVID-19.

METHODS

We analyzed 6-month follow-up data collected from a multi-center, prospective study of hospitalized COVID-19 patients. Demographic and SDOH variables (age, race/ethnicity, education, employment, health insurance status, median income, primary language, living arrangements, and pre-COVID disability) were compared between patients with normal versus abnormal telephone Montreal Cognitive Assessments (t-MOCA; scores<18/22). Multivariable logistic regression models were constructed to evaluate predictors of t-MoCA.

RESULTS

Of 382 patients available for 6-month follow-up, 215 (56%) completed the t-MoCA (n = 109/215 [51%] had normal and n = 106/215 [49%] abnormal results). 14/215 (7%) patients had a prior history of dementia/cognitive impairment. Significant univariate predictors of abnormal t-MoCA included older age, ≤12 years of education, unemployment pre-COVID, Black race, and a pre-COVID history of cognitive impairment (all p < 0.05). In multivariable analyses, education ≤12 years (adjusted OR 5.21, 95%CI 2.25-12.09), Black race (aOR 5.54, 95%CI 2.25-13.66), and the interaction of baseline functional status and unemployment prior to hospitalization (aOR 3.98, 95%CI 1.23-12.92) were significantly associated with abnormal t-MoCA scores after adjusting for age, history of dementia, language, neurological complications, income and discharge disposition.

CONCLUSIONS

Fewer years of education, Black race and unemployment with baseline disability were associated with abnormal t-MoCA scores 6-months post-hospitalization for COVID-19. These associations may be due to undiagnosed baseline cognitive dysfunction, implicit biases of the t-MoCA, other unmeasured SDOH or biological effects of SARS-CoV-2.

Students' knowledge and perceptions of social determinants of health utilizing interactive computer simulation-based learning

INTRODUCTION

The purpose of this study was to assess if using computer simulations as a supplemental tool for teaching social determinants of health (SDoH) would impact first-year pharmacy students' knowledge and perceptions of SDoH.

METHODS

A brief lecture and online poverty game were followed by completion of two, in-class, computer-simulated SDoH clinical scenarios and corresponding case discussion. Students completed a pre- and post-quiz and perception survey with two open-ended questions. Qualitative analysis of the open-ended questions and quantitative analyses of the poverty game choices, quiz, and perception survey were conducted.

RESULTS

In total, 132 students were enrolled in this study. Thematic analysis of the open-ended question asking students what they learned included empathy (42%), general SDoH knowledge (30%), culture/religion (18%), and economic impact (15%). Student perceptions for all teaching modalities had a mean score of 4. Mean quiz scores on the pre- and post-class quizzes were 2.31 (SD 0.93) and 2.51 (SD 0.89), respectively.

CONCLUSIONS

Computer simulations can be utilized as a supplemental tool to teach and apply clinical patient cases focused on SDoH. Strategically threading SDoH throughout the pharmacy curriculum is recommended to further develop SDoH knowledge and clinical skills.

National Heart, Lung, and Blood Institute: Social Determinants of Health Research, Fiscal Year 2008-2020

INTRODUCTION

Social determinants of health influence the prevention, treatment, and progression of chronic diseases, including heart, lung, blood, and sleep diseases and conditions. Healthy People 2020 classifies Social Determinants of Health into 5 subcategories: (1) Neighborhood and Built Environment, (2) Education, (3) Economic Stability, (4) Social and Community Context, and (5) Health and Health Care. This study's goal is to characterize the National Heart, Lung, and Blood Institute's Fiscal Year 2008-2020 funding in overall Social Determinants of Health research and in the Healthy People 2020 subcategories.

METHODS

The Social Determinants of Health Research, Condition, and Disease Categorization code was used to identify funded grants in this area. Natural language processing methods further categorized grants into the 5 Healthy People 2020 Social Determinants of Health subcategories.

RESULTS

There were 915 (∼4.3%) social determinants of health‒funded grants from 2008 to 2020 representing $1,034 billion in direct costs. Most grants were relevant to cardiovascular diseases (n=653), with a smaller number relevant to lung diseases (n=186), blood diseases (n=47), and translational and implementation science (n=29). Grants fit multiple Social Determinants of Health subcategories with the majority identified as Health and Health Care (62%) and Economic Stability (61%). The number of National Heart, Lung, and Blood Institute social determinants of health grants awarded increased by 127% from Fiscal Year 2008 to Fiscal Year 2020.

CONCLUSIONS

This study identifies Social Determinants of Health grants funded by the National Heart, Lung, and Blood Institute during 2008‒2020. Enhancing the understanding of these determinants and developing effective interventions will ultimately help to advance the mission of the National Heart, Lung, and Blood Institute.

Association of Social Determinants of Health and Their Cumulative Impact on Hospitalization Among a National Sample of Community-Dwelling US Adults

IMPORTANCE

While the association between Social Determinants of Health (SDOH) and health outcomes is well known, few studies have explored the impact of SDOH on hospitalization.

OBJECTIVE

Examine the independent association and cumulative effect of six SDOH domains on hospitalization.

DESIGN

Using cross-sectional data from the 2016-2018 National Health Interview Surveys (NHIS), we used multivariable logistical regression models controlling for sociodemographics and comorbid conditions to assess the association of each SDOH and SDOH burden (i.e., cumulative number of SDOH) with hospitalization.

SETTING

National survey of community-dwelling individuals in the US PARTICIPANTS: Adults ≥18 years who responded to the NHIS survey EXPOSURE: Six SDOH domains (economic instability, lack of community, educational deficits, food insecurity, social isolation, and inadequate access to medical care) MEASURES: Hospitalization within 1 year RESULTS: Among all 55,186 respondents, most were ≤50 years old (54.2%), female (51.7%, 95% CI 51.1-52.3), non-Hispanic (83.9%, 95% CI 82.4-84.5), identified as White (77.9%, 95% CI 76.8-79.1), and had health insurance (90%, 95% CI 88.9-91.9). Hospitalized individuals (n=5506; 8.7%) were more likely to be ≥50 years old (61.2%), female (60.7%, 95% CI 58.9-62.4), non-Hispanic (87%, 95% CI 86.2-88.4), and identify as White (78.5%, 95% CI 76.7-80.3), compared to those who were not hospitalized. Hospitalized individuals described poorer overall health, reporting higher incidence of having ≥5 comorbid conditions (38.9%, 95% CI 37.1-40.1) compared to those who did not report a hospitalization (15.9%, 95% CI 15.4-16.5). Hospitalized respondents reported higher rates of economic instability (33%), lack of community (14%), educational deficits (67%), food insecurity (14%), social isolation (34%), and less access to health care (6%) compared to non-hospitalized individuals. In adjusted analysis, food insecurity (OR: 1.36, 95% CI 1.22-1.52), social isolation (OR: 1.17, 95% CI 1.08-1.26), and lower educational attainment (OR: 1.12, 95% CI 1.02-1.25) were associated with hospitalization, while a higher SDOH burden was associated with increased odds of hospitalization (3-4 SDOH [OR: 1.25, 95% CI 1.06-1.49] and ≥5 SDOH [OR: 1.72, 95% CI 1.40-2.06]) compared to those who reported no SDOH.

CONCLUSIONS

Among community-dwelling US adults, three SDOH domains: food insecurity, social isolation, and low educational attainment increase an individual's risk of hospitalization. Additionally, risk of hospitalization increases as SDOH burden increases.

Interconnected Clinical and Social Risk Factors in Breast Cancer and Heart Failure

Breast cancer and heart failure share several known clinical cardiovascular risk factors, including age, obesity, glucose dysregulation, cholesterol dysregulation, hypertension, atrial fibrillation and inflammation. However, to fully comprehend the complex interplay between risk of breast cancer and heart failure, factors attributed to both biological and social determinants of health must be explored in risk-assessment. There are several social factors that impede implementation of prevention strategies and treatment for breast cancer and heart failure prevention, including socioeconomic status, neighborhood disadvantage, food insecurity, access to healthcare, and social isolation. A comprehensive approach to prevention of both breast cancer and heart failure must include assessment for both traditional clinical risk factors and social determinants of health in patients to address root causes of lifestyle and modifiable risk factors. In this review, we examine clinical and social determinants of health in breast cancer and heart failure that are necessary to consider in the design and implementation of effective prevention strategies that altogether reduce the risk of both chronic diseases.

Health disparities and access to advanced therapy for overactive bladder

AIMS

Refractory overactive bladder (OAB) is among the most common reasons for referral to specialists in voiding dysfunction. Significant racial and ethnic disparities exist in prevalence, severity, and management of OAB, presenting care barriers for marginalized patients. We aim to explicate these disparities and explore the factors that led to their existence and persistence. We will additionally offer suggestions to mitigate such disparities and approach equitable care for our patients.

METHODS

This is a narrative review of pertinent articles related to health disparities in OAB. Articles on OAB prevalence stratified by race and ethnicity, and variations in treatment patterns for patients of marginalized backgrounds were identified from the PubMed database. We also included a review of evidence from governmental and historical sources to provide sociocultural context.

RESULTS

Patients from marginalized backgrounds are underrepresented in OAB literature. There appear to be differences in symptom severity and prevalence based on race. OAB severity seems closely entwined with social determinants of health. Patients from marginalized populations experience numerous care barriers impeding the treatment of OAB. Finally, White patients are more likely to receive advanced management for OAB.

CONCLUSIONS

Numerous health disparities exist in the diagnosis and management of OAB. This review is grounded in societal context: health injustice in the United States ultimately stems from systemic racism. Improving our understanding of care disparities and the systems that allow them to persist will bring us closer to equity and allow our patients from marginalized backgrounds to obtain the evidence-based care they deserve.

A Socioecological Model of Heart Failure Self-Care

Heart failure is a chronic, progressively worsening condition afflicting more than 64 million individuals worldwide. Heart failure outcomes are influenced by self-care, a naturalistic patient-centered decision-making process. The situation-specific theory of heart failure self-care addresses how this decision-making process determines actions and outcomes. However, little is known about the impact of socioecological determinants of health on heart failure self-care. A theoretical synthesis could advance the situation-specific theory of heart failure self-care through the inclusion of socioecological determinants of health. Thus, socioecological determinants of health related to heart failure self-care can be better explored, understood, and overcome through research and health promotion.

ICD-10 Z-Code Health-Related Social Needs and Increased Healthcare Utilization

INTRODUCTION

Health-related social needs are known drivers of health and health outcomes, yet work to date to examine health-related social needs using ICD-10 Z-codes remains limited. This study seeks to evaluate the differences in the prevalence of conditions as well as utilization and cost between patients with and without health-related social needs.

METHODS

Using the 2017 Florida State Emergency Department and State Inpatient Databases, this study identified patients with documented health-related social needs using ICD-10 Z-codes. The prevalence ratio was calculated for 14 conditions that are the leading causes of mortality and economic costs. In addition, ratios for the median total number of negative health events and total annual costs between patients with health-related social needs and those without health-related social needs across these conditions were calculated. Data analysis was conducted in 2021.

RESULTS

Of 4,477,772 patients, 46,081 (1.0%) had documented health-related social needs and had 4 times the negative health events and 9.3 times the total annual costs. Trends of increased negative health events and costs were seen across all examined conditions; patients with health-related social needs had 2.5-3.5 times the negative health events and 2-18 times greater total costs. The biggest difference in negative health events was seen in patients with unintentional injuries and depression and psychoses (3.5 times for patients with health-related social needs), whereas the biggest difference in total costs was for unintentional injuries (18.4 times for patients with health-related social needs).

CONCLUSIONS

This study shows the increased prevalence of numerous high-priority conditions as well as increased utilization and costs among patients with documented health-related social needs.

Social determinants of health and obesity: Findings from a national study of US adults

OBJECTIVE

This study examined the association between social determinants of health (SDOH) burden and overweight/obesity in a nationally representative sample of adults in the United States.

METHODS

Data for 161,795 adults aged ≥18 years from the 2013 to 2017 National Health Interview Survey were used. A total of 38 SDOH were aggregated to create a cumulative SDOH score, which was divided into quartiles (Q1-Q4) to denote levels of SDOH burden. Prevalence of overweight and obesity was examined across SDOH quartiles in the total population and by age, sex, and race/ethnicity. Multinomial logistic regression models were used to analyze the association between SDOH quartiles and overweight/obesity, adjusting for relevant covariates.

RESULTS

There was a graded increase in obesity prevalence with increasing SDOH burden. At nearly each quartile, overweight and obesity rates were higher for middle-aged and non-Hispanic Black adults compared with their counterparts; additional differences were observed by sex. In fully adjusted models, SDOH-Q4 was associated with 15%, 50%, and 70% higher relative prevalence of overweight, obesity class 1 and 2, and obesity class 3, respectively, relative to SDOH-Q1.

CONCLUSIONS

Cumulative social disadvantage, denoted by higher SDOH burden, was associated with increased odds of obesity, independent of clinical and demographic factors.

Fatigue in Persons With Heart Failure: A Systematic Literature Review and Meta-Synthesis Using the Biopsychosocial Model of Health

BACKGROUND

Fatigue is a common and distressing symptom of heart failure (HF) and has important implications for patient-reported and clinical outcomes. Despite being a common and bothersome symptom, fatigue has been understudied in HF. We sought to synthesize existing literature on fatigue in HF through a systematic literature review guided by the biopsychosocial model of health.

METHODS AND RESULTS

A systematic search of the literature was performed on March 18, 2020, using Pubmed, Embase, and CINAHL. Full-text, primary research articles, written in English, in which fatigue was a primary symptom of interest in adults with a diagnosis of HF, were included. The search yielded 1138 articles; 33 articles that met inclusion criteria were selected for extraction and synthesis. Biological and psychological factors associated with fatigue were New York Heart Association functional class, hemoglobin level, history of stroke, and depression. However, there are limited HF-specific factors linked to fatigue. Social factors related to fatigue included social roles, relationship strain, and loneliness and isolation. Few nonpharmacologic interventions have been tested by show some promise for alleviating fatigue in HF. Studies show conflicting evidence related to the prognostic implications of fatigue.

CONCLUSIONS

Important biological correlates of fatigue were identified; however, psychological and social variables were limited to qualitative description. There is need for expanded models to better understand the complex physiologic nature of fatigue in HF. Additionally, more research is needed to (1) define the relationships between fatigue and both psychological and social factors, (2) better describe the prognostic implications of fatigue, and (3) develop more therapeutic approaches to alleviate fatigue with the goal of improving overall quality of life.

Social Determinants of Health and 30-Day Readmissions Among Adults Hospitalized for Heart Failure in the REGARDS Study

BACKGROUND

It is not known which social determinants of health (SDOH) impact 30-day readmission after a heart failure (HF) hospitalization among older adults. We examined the association of 9 individual SDOH with 30-day readmission after an HF hospitalization.

METHODS AND RESULTS

Using the REGARDS study (Reasons for Geographic and Racial Differences in Stroke), we included Medicare beneficiaries who were discharged alive after an HF hospitalization between 2003 and 2014. We assessed 9 SDOH based on the Healthy People 2030 Framework: race, education, income, social isolation, social network, residential poverty, Health Professional Shortage Area, rural residence, and state public health infrastructure. The primary outcome was 30-day all-cause readmission. For each SDOH, we calculated incidence per 1000 person-years and multivariable-adjusted hazard ratios of readmission. Among 690 participants, the median age was 76 years at hospitalization (interquartile range, 71-82), 44.3% were women, 35.5% were Black, 23.5% had low educational attainment, 63.0% had low income, 21.0% had zip code-level poverty, 43.5% resided in Health Professional Shortage Areas, 39.3% lived in states with poor public health infrastructure, 13.1% were socially isolated, 13.3% had poor social networks, and 10.2% lived in rural areas. The 30-day readmission rate was 22.4%. In an unadjusted analysis, only Health Professional Shortage Area was significantly associated with 30-day readmission; in a fully adjusted analysis, none of the 9 SDOH were individually associated with 30-day readmission.

CONCLUSIONS

In this modestly sized national cohort, although prevalent, none of the SDOH were associated with 30-day readmission after an HF hospitalization. Policies or interventions that only target individual SDOH to reduce readmissions after HF hospitalizations may not be sufficient to prevent readmission among older adults.

Health care experiences during the COVID-19 pandemic by race and social determinants of health among adults age ≥ 58 years in the REGARDS study

BACKGROUND

Understanding health care experiences during the COVID-19 pandemic may provide insights into patient needs and inform policy. The objective of this study was to describe health care experiences by race and social determinants of health.

METHODS

We conducted a telephone survey (July 6, 2020-September 4, 2021) among 9492 Black and White participants in the longitudinal REasons for Geographic And Racial Differences in Stroke cohort study, age 58-105 years, from the continental United States. Among participants with symptoms of COVID-19, outcomes were: 1. Sought care or advice for the illness; 2. Received a SARS-CoV-2 test for the illness; and 3. Tested positive. Among participants without symptoms of COVID-19, outcomes were: 1. Wanted a test; 2. Wanted and received a test; 3. Did not want but received a test; and 4. Tested positive. We examined these outcomes overall and in subgroups defined by race, household income, marital status, education, area-level poverty, rural residence, Medicaid expansion, public health infrastructure ranking, and residential segregation.

RESULTS

The average age of participants was 76.8 years, 36% were Black, and 57% were female. Among participants with COVID-19 symptoms (n = 697), 74% sought care or advice for the illness, 50% received a SARS-CoV-2 test, and 25% had a positive test (50% of those tested). Among participants without potential COVID-19 symptoms (n = 8795), 29% wanted a SARS-CoV-2 test, 22% wanted and received a test, 8% did not want but received a test, and 1% tested positive; a greater percentage of participants who were Black compared to White wanted (38% vs 23%, p < 0.001) and received tests (30% vs 18%, p < 0.001) and tested positive (1.4% vs 0.8%, p = 0.005).

CONCLUSIONS

In this national study of older US adults, many participants with potential COVID-19 symptoms and asymptomatic participants who desired testing did not receive COVID-19 testing.

Social determinants of health and cancer mortality in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort study

BACKGROUND

Social determinants of health (SDOHs) cluster together and can have deleterious impacts on health outcomes. Individually, SDOHs increase the risk of cancer mortality, but their cumulative burden is not well understood. The authors sought to determine the combined effect of SDOH on cancer mortality.

METHODS

Using the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort, the authors studied 29,766 participants aged 45+ years and followed them 10+ years. Eight potential SDOHs were considered, and retained SDOHs that were associated with cancer mortality (P < .10) were retained to create a count (0, 1, 2, 3+). Cox proportional hazard models estimated associations between the SDOH count and cancer mortality through December 31, 2017, adjusting for confounders. Models were age-stratified (45-64 vs 65+ years).

RESULTS

Participants were followed for a median of 10.6 years (interquartile range [IQR], 6.5, 12.7 years). Low education, low income, zip code poverty, poor public health infrastructure, lack of health insurance, and social isolation were significantly associated with cancer mortality. In adjusted models, among those <65 years, compared to no SDOHs, having 1 SDOH (adjusted hazard ratio [aHR], 1.39; 95% CI, 1.11-1.75), 2 SDOHs (aHR, 1.61; 95% CI, 1.26-2.07), and 3+ SDOHs (aHR, 2.09; 95% CI, 1.58-2.75) were associated with cancer mortality (P for trend <.0001). Among individuals 65+ years, compared to no SDOH, having 1 SDOH (aHR, 1.16; 95% CI, 1.00-1.35) and 3+ SDOHs (aHR, 1.26; 95% CI, 1.04-1.52) was associated with cancer mortality (P for trend = .032).

CONCLUSIONS

A greater number of SDOHs were significantly associated with an increased risk of cancer mortality, which persisted after adjustment for confounders.

Social Vulnerability Indices as a Risk Factor for Heart Failure Readmissions

Objectives: The objective of our study was to use the parameters of social vulnerability index (SVI) to observe their association with the 30-day hospital readmissions in the heart failure population.Methods: Data required for analysis were extracted from the electronic medical record. The geographic SVI data was then merged with the clinical data. Qualitative variables and reported as frequency and quantitative variables and reported as the mean ± standard deviation. Variables from univariate analysis with a P value of ≤ 0.10 were evaluated using multivariate logistic regression with stepwise backward variable selection and receiver operating curve (ROC) analysis.Results: The odds ratio of readmission predicted by HOSPITAL score was 1.137 (P value = 0.004, 95% CI = 1.041-1.241). SVI parameter recording disability showed odds ratio of 1.521 (P value = 0.006, 95% CI = 1.125-2.058) and SVI parameter tracking vehicle ownership showed odds ratio of 15.355 (P value = 0.014, 95% CI = 1.755 - 134.383). The ROCs were generated for three scenarios: (i) HOSPITAL score only which had area under the curve (AUC) of 0.702 (P value = 0.015), (ii) SVI indicators tracking vehicle ownership and disability resulted in the AUC of 0.589 (P value = 0.016), and (iii) all of the above combined increased the AUC increased to 0.718 (P value = 0.015).Conclusions: Two social parameters (limited vehicle access and prevalence of disability) from the SVI showed a strong association with 30-day hospital readmissions.

Social and Behavioral Determinants of Health in the Era of Artificial Intelligence with Electronic Health Records: A Scoping Review

Background. There is growing evidence that social and behavioral determinants of health (SBDH) play a substantial effect in a wide range of health outcomes. Electronic health records (EHRs) have been widely employed to conduct observational studies in the age of artificial intelligence (AI). However, there has been limited review into how to make the most of SBDH information from EHRs using AI approaches.Methods. A systematic search was conducted in six databases to find relevant peer-reviewed publications that had recently been published. Relevance was determined by screening and evaluating the articles. Based on selected relevant studies, a methodological analysis of AI algorithms leveraging SBDH information in EHR data was provided.Results. Our synthesis was driven by an analysis of SBDH categories, the relationship between SBDH and healthcare-related statuses, natural language processing (NLP) approaches for extracting SBDH from clinical notes, and predictive models using SBDH for health outcomes.Discussion. The associations between SBDH and health outcomes are complicated and diverse; several pathways may be involved. Using NLP technology to support the extraction of SBDH and other clinical ideas simplifies the identification and extraction of essential concepts from clinical data, efficiently unlocks unstructured data, and aids in the resolution of unstructured data-related issues.Conclusion. Despite known associations between SBDH and diseases, SBDH factors are rarely investigated as interventions to improve patient outcomes. Gaining knowledge about SBDH and how SBDH data can be collected from EHRs using NLP approaches and predictive models improves the chances of influencing health policy change for patient wellness, ultimately promoting health and health equity.

Effects of Neighborhood-level Data on Performance and Algorithmic Equity of a Model That Predicts 30-day Heart Failure Readmissions at an Urban Academic Medical Center

BACKGROUND

Socioeconomic data may improve predictions of clinical events. However, owing to structural racism, algorithms may not perform equitably across racial subgroups. Therefore, we sought to compare the predictive performance overall, and by racial subgroup, of commonly used predictor variables for heart failure readmission with and without the area deprivation index (ADI), a neighborhood-level socioeconomic measure.

METHODS AND RESULTS

We conducted a retrospective cohort study of 1316 Philadelphia residents discharged with a primary diagnosis of congestive heart failure from the University of Pennsylvania Health System between April 1, 2015, and March 31, 2017. We trained a regression model to predict the probability of a 30-day readmission using clinical and demographic variables. A second model also included the ADI as a predictor variable. We measured predictive performance with the Brier Score (BS) in a held-out test set. The baseline model had moderate performance overall (BS 0.13, 95% CI 0.13-0.14), and among White (BS 0.12, 95% CI 0.12-0.13) and non-White (BS 0.13, 95% CI 0.13-0.14) patients. Neither performance nor algorithmic equity were significantly changed with the addition of the ADI.

CONCLUSIONS

The inclusion of neighborhood-level data may not reliably improve performance or algorithmic equity.

Health-Related Social Needs and Increased Readmission Rates: Findings from the Nationwide Readmissions Database

BACKGROUND

While health-related social needs (HRSN) are known to compromise health, work to date has not clearly demonstrated the relationship between clinically acknowledged social needs, via ICD-10 Z-codes, and readmission.

OBJECTIVE

Assess the rate of 30-, 60-, and 90-day readmission by the level of ICD-10-identified social need. In addition, we examined the associations between demographics, social need, hospital characteristics, and comorbidities on 30-day readmission.

DESIGN

Retrospective study using the 2017 Nationwide Readmission Database PARTICIPANTS: We identified 5 domains of HRSN from ICD-10 diagnosis codes including employment, family, housing, psychosocial, and socioeconomic status (SES) and identified how many and which an individual was coded with during the year.

MAIN MEASURES

The proportion of patients with 30-, 60-, and 90-day readmission stratified by the number of HRSN domains with a multivariable logistic regression to examine the relationship between the number/type of and readmission adjusting for sex, age, payer, hospital characteristics, functional limitations, and comorbidities.

KEY RESULTS

From 13,217,506 patients, only 2.4% had at least one HRSN diagnosis. Among patients without HRSN, 11.5% had a 30-day readmission, compared to 27.0% of those with 1 domain, increasing to 63.5% for patients with codes in 5 domains. Similar trends were observed for 60- and 90-day readmission; 78.7% of patients with documented HRSN in all 5 domains were hospitalized again within 90 days. The adjusted odds ratio for readmission for individuals with all 5 domains was 12.55 (95% CI: 9.04, 17.43). Housing and employment emerged as two of the most commonly documented HRSN, as well as having the largest adjusted odds ratio.

CONCLUSIONS

There is a dose-response relationship between the number of HRSN diagnoses and hospital readmission. This work calls attention to the need to develop interventions to reduce readmissions for those at social risk and demonstrates the significance of ICD-10 Z-codes in health outcomes studies.

Number of Social Determinants of Health and Fatal and Nonfatal Incident Coronary Heart Disease in the REGARDS Study

BACKGROUND

Social determinants of health (SDH) are individually associated with incident coronary heart disease (CHD) events. Indices reflecting social deprivation have been developed for population management, but are difficult to operationalize during clinical care. We examined whether a simple count of SDH is associated with fatal incident CHD and nonfatal myocardial infarction (MI).

METHODS

We used data from the prospective longitudinal REGARDS cohort study (Reasons for Geographic and Racial Differences in Stroke), a national population-based sample of community-dwelling Black and White adults age ≥45 years recruited from 2003 to 2007. Seven SDH from the 5 Healthy People 2020 domains included social context (Black race, social isolation); education (educational attainment); economic stability (annual household income); neighborhood (living in a zip code with high poverty); and health care (lacking health insurance, living in 1 of the 9 US states with the least public health infrastructure). Outcomes were expert adjudicated fatal incident CHD and nonfatal MI.

RESULTS

Of 22 152 participants free of CHD at baseline, 58.8% were women and 42.0% were Black; 20.6% had no SDH, 30.6% had 1, 23.0% had 2, and 25.8% had ≥3. There were 463 fatal incident CHD events and 932 nonfatal MIs over a median of 10.7 years (interquartile range, 6.6 to 12.7). Fewer SDHs were associated with nonfatal MI than with fatal incident CHD. The age-adjusted incidence per 1000 person-years increased with the number of SDH for both fatal incident CHD (0 SDH, 1.30; 1 SDH, 1.44; 2 SDH, 2.05; ≥3 SDH, 2.86) and nonfatal MI (0 SDH, 3.91; 1 SDH, 4.33; ≥2 SDH, 5.44). Compared with those without SDH, crude and fully adjusted hazard ratios for fatal incident CHD among those with ≥3 SDH were 3.00 (95% CI, 2.17 to 4.15) and 1.67 (95% CI, 1.18 to 2.37), respectively; hazard ratios for nonfatal MI among those with ≥2 SDH were 1.57 (95% CI, 1.30 to 1.90) and 1.14 (95% CI, 0.93 to 1.41), respectively.

CONCLUSIONS

A greater burden of SDH was associated with a graded increase in risk of incident CHD, with greater magnitude and independent associations for fatal incident CHD. Counting the number of SDHs may be a promising approach that could be incorporated into clinical care to identify individuals at high risk of CHD.

Palliative Care in Acute Heart Failure

Purpose of Review

Palliative care is increasingly acknowledged as beneficial in supporting patients and families affected by heart failure, but policy documents have generally focused on the chronic form of this disease. We examined palliative care provision for those with acute heart failure, based on the recently updated National Consensus Project Clinical Practice Guidelines for Quality Palliative Care.

Recent Findings

The commonest reason for hospitalization in those > 65 years, acute heart failure admissions delineate crisis points on the unpredictable disease trajectory. Palliative care is underutilized, often perceived as limited to end-of-life care rather than determined by regular systematic needs assessment. No dominant paradigm of palliative care provision has emerged from the nascent evidence base related to this clinical cohort, underscoring the need for further research.

Summary

Embedding palliative support as mainstream to heart failure care from the point of diagnosis may better ensure treatment strategies for those admitted with acute heart failure remain consistent with patients’ preferences and values.

Social Determinants of Health and 90-Day Mortality After Hospitalization for Heart Failure in the REGARDS Study

Background

Outcomes following heart failure (HF) hospitalizations are poor, with 90‐day mortality rates of 15% to 20%. Although prior studies found associations between individual social determinants of health (SDOH) and post‐discharge mortality, less is known about how an individuals’ total burden of SDOH affects 90‐day mortality.

Methods and Results

We included participants of the REGARDS (Reasons for Geographic and Racial Differences in Stroke) Study who were Medicare beneficiaries aged ≥65 years discharged alive after an adjudicated HF hospitalization. Guided by the Healthy People 2020 Framework, we examined 9 SDOH. First, we examined age‐adjusted associations between each SDOH and 90‐day mortality; those associated with 90‐day mortality were used to create an SDOH count. Next, we determined the hazard of 90‐day mortality by the SDOH count, adjusting for confounders. Over 10 years, 690 participants were hospitalized for HF at 440 unique hospitals in the United States; there were a total of 79 deaths within 90 days. Overall, 28% of participants had 0 SDOH, 39% had 1, and 32% had ≥2. Compared with those with 0, the age‐adjusted hazard ratio for 90‐day mortality among those with 1 SDOH was 2.89 (95% CI, 1.46–5.72) and was 3.06 (1.51–6.19) among those with ≥2 SDOH. The adjusted hazard ratio was 2.78 (1.37–5.62) and 2.57 (1.19–5.54) for participants with 1 SDOH and ≥2, respectively.

Conclusions

While having any of the SDOH studied here markedly increased risk of 90‐day mortality after an HF hospitalization, a greater burden of SDOH was not associated with significantly greater risk in our population.