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

Scoping Review of Screening and Assessment Tools for Social Determinants of Health in the Field of Cardiovascular Disease

BACKGROUND

Despite the importance of implementing the concept of social determinants of health (SDOH) in the clinical practice of cardiovascular disease (CVD), the tools available to assess SDOH have not been systematically investigated. We conducted a scoping review for tools to assess SDOH and comprehensively evaluated how these tools could be applied in the field of CVD.Methods and Results: We conducted a systematic literature search of PubMed and Embase databases on July 25, 2023. Studies that evaluated an SDOH screening tool with CVD as an outcome or those that explicitly sampled or included participants based on their having CVD were eligible for inclusion. In addition, studies had to have focused on at least one SDOH domain defined by Healthy People 2030. After screening 1984 articles, 58 articles that evaluated 41 distinct screening tools were selected. Of the 58 articles, 39 (67.2%) targeted populations with CVD, whereas 16 (27.6%) evaluated CVD outcome in non-CVD populations. Three (5.2%) compared SDOH differences between CVD and non-CVD populations. Of 41 screening tools, 24 evaluated multiple SDOH domains and 17 evaluated only 1 domain.

CONCLUSIONS

Our review revealed recent interest in SDOH in the field of CVD, with many useful screening tools that can evaluate SDOH. Future studies are needed to clarify the importance of the intervention in SDOH regarding CVD.

Polysocial Risk Scores: Implications for Cardiovascular Disease Risk Assessment and Management

PURPOSE OF REVIEW

To review current evidence, discuss key knowledge gaps and identify opportunities for development, validation and application of polysocial risk scores (pSRS) for cardiovascular disease (CVD) risk prediction and population cardiovascular health management.

RECENT FINDINGS

Limited existing evidence suggests that pSRS are promising tools to capture cumulative social determinants of health (SDOH) burden and improve CVD risk prediction beyond traditional risk factors. However, available tools lack generalizability, are cross-sectional in nature or do not assess social risk holistically across SDOH domains. Available SDOH and clinical risk factor data in large population-based databases are under-utilized for pSRS development. Recent advances in machine learning and artificial intelligence present unprecedented opportunities for SDOH integration and assessment in real-world data, with implications for pSRS development and validation for both clinical and healthcare utilization outcomes. pSRS presents unique opportunities to potentially improve traditional "clinical" models of CVD risk prediction. Future efforts should focus on fully utilizing available SDOH data in large epidemiological databases, testing pSRS efficacy in diverse population subgroups, and integrating pSRS into real-world clinical decision support systems to inform clinical care and advance cardiovascular health equity.

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.

Prescribing patterns of fall risk-increasing drugs in older adults hospitalized for heart failure

BACKGROUND

Older adults hospitalized for heart failure (HF) are at risk for falls after discharge. One modifiable contributor to falls is fall risk-increasing drugs (FRIDs). However, the prevalence of FRIDs among older adults hospitalized for HF is unknown. We describe patterns of FRIDs use and examine predictors of a high FRID burden.

METHODS

We used the national biracial REasons for Geographic and Racial Differences in Stroke (REGARDS) study, a prospective cohort recruited from 2003-2007. We included REGARDS participants aged ≥ 65 years discharged alive after a HF hospitalization from 2003-2017. We determined FRIDs -cardiovascular (CV) and non-cardiovascular (non-CV) medications - at admission and discharge from chart abstraction of HF hospitalizations. We examined the predictors of a high FRID burden at discharge via modified Poisson regression with robust standard errors.

RESULTS

Among 1147 participants (46.5% women, mean age 77.6 years) hospitalized at 676 hospitals, 94% were taking at least 1 FRID at admission and 99% were prescribed at least 1 FRID at discharge. The prevalence of CV FRIDs was 92% at admission and 98% at discharge, and the prevalence of non-CV FRIDs was 32% at admission and discharge. The most common CV FRID at admission (88%) and discharge (93%) were antihypertensives; the most common agents were beta blockers (61% at admission, 75% at discharge), angiotensin-converting enzyme inhibitors (36% vs. 42%), and calcium channel blockers (32% vs. 28%). Loop diuretics had the greatest change in prevalence (53% vs. 72%). More than half of the cohort (54%) had a high FRID burden (Agency for Healthcare Research and Quality (AHRQ) score ≥ 6), indicating high falls risk after discharge. In a multivariable Poisson regression analysis, the factors strongly associated with a high FRID burden at discharge included hypertension (PR: 1.41, 95% CI: 1.20, 1.65), mood disorder (PR: 1.24, 95% CI: 1.10, 1.38), and hyperpolypharmacy (PR: 1.88, 95% CI: 1.64, 2.14).

CONCLUSIONS

FRID use was nearly universal among older adults hospitalized for HF; more than half had a high FRID burden at discharge. Further work is needed to guide the management of a common clinical conundrum whereby guideline indications for treating HF may contribute to an increased risk for falls.

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.

Interprofessional Collaborative Practice Improves Access to Care and Healthcare Quality to Advance Health Equity

ABSTRACT

Healthcare disparites exist in cardiovascular care, including heart failure. Care that is not equitable can lead to higher incidence of heart failure, increased readmissions, and poorer outcomes. The Heart Failure Transitional Care Services for Adults Clinic is an interprofessional collaborative practice that provides guideline-directed medical therapy and education to underserved patients with heart failure. Little is known regarding healthcare equity and quality metrics in relation to interprofessional teams. Thus, the purpose of this study was to examine if an interprofessional collaborative practice care delivery model can affect access to care and healthcare quality outcomes in underserved patients with heart failure. As evidenced by control charts over a two and a half year period, the Heart Failure Transitional Care Services for Adults Clinic was able to show improvements in access to care and quality metrics results without variation. An interprofessional collaborative practice can be an effective delivery model to address health equity and quality of care outcomes.