Should We Implement Geographic or Patient-Reported Social Determinants of Health Measures in Cardiovascular Patients?

Abstract

Objectives: To compare patient-reported social determinants of health (SDOH) to the Brokamp Area Deprivation Index (ADI), and evaluate the association of patient-reported SDOH and ADI with mortality in patients with cardiovascular disease (CVD).Design: Prospective cohort.Setting: Academic medical center.Participants: Adults with acute coronary syndrome (ACS) and/or acute exacerbation of heart failure (HF) hospitalized between 2011 and 2015.Methods: Patient-reported SDOH included: income range, education, health insurance, and household size. ADI was calculated using census tract level variables of poverty, median income, high school completion, lack of health insurance, assisted income, and vacant housing.Primary outcome: All-cause mortality, up to 5 years follow-up.Results: The sample was 60% male, 84% White, and 93% insured; mean patient-reported household income was $48,000 (SD $34,000). ADI components were significantly associated with corresponding patient-report­ed variables. In age, sex, and race adjusted Cox regression models, ADI was associated with mortality for ACS (HR 1.23, 95% CI 1.06, 1.42), but not HF (HR 1.09, 95% CI .99, 1.21). Mortality models for ACS improved with consideration of social determinants data (C-statistics: base demographic model=.612; ADI added=.644; patient-reported SDOH added=.675; both ADI and patient-reported SDOH added=.689). HF mortality models improved only slightly (C-statistics: .600, .602, .617, .620, respectively).Conclusions: The Brokamp ADI is associated with mortality in hospitalized patients with CVD. In the absence of available patient-reported data, hospitals could implement the Brokamp ADI as an approximation for patient-reported data to enhance risk stratification of patients with CVD. Ethn Dis. 2021;31(1):9-22; doi:10.18865/ed.31.1.9

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

“… 13 , 27 , 56 , 59 Primary language spoken at home was not significantly associated with mortality risk. 28 No significant association between insurance status and HF mortality risk was observed, 13 , 28 , 32 , 42 , 64 with the exception of 1 study, where lack of insurance was associated with decreased mortality risk. 42 Marital status was an inconsistent influence: being married was associated with increased 58 or decreased mortality risk 43 ; in 2 studies, 13 , 65 no significant association between marital status and mortality risk was found.…”

“… 28 No significant association between insurance status and HF mortality risk was observed, 13 , 28 , 32 , 42 , 64 with the exception of 1 study, where lack of insurance was associated with decreased mortality risk. 42 Marital status was an inconsistent influence: being married was associated with increased 58 or decreased mortality risk 43 ; in 2 studies, 13 , 65 no significant association between marital status and mortality risk was found. Faith/spirituality was associated with decreased mortality risk, 51 whereas a lack of faith identification was associated with increased mortality risk.…”

“…In total, 59 articles met the criteria for inclusion (Table S2 ). 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , …”

“…In these studies, Black race (compared with White race) was associated with both decreased 26 , 27 , 28 , 63 and increased 52 , 59 , 70 mortality or survival; similarly, Hispanic ethnicity (compared with non‐Hispanic White ethnicity) was associated with decreased 27 , 63 and increased mortality risk. 52 , 59 , 70 Older age (compared with younger age groups) was associated with increased HF mortality risk in several studies, 42 , 43 , 46 , 51 whereas younger (compared with older) age was associated with increased in‐hospital mortality risk in a study examining cardiogenic shock unrelated to acute coronary syndrome. 70 In 1 study, no significant association between age and mortality was found.…”

Prediction of Future Health Care Utilization Through Note-extracted Psychosocial Factors

“…This segment, however, is both the fastest growing and most likely to show near-term outcomes; the variability in these outcomes make additional factors, like psychosocial variables, particularly valuable to plan potential interventions. Others have used additional socioeconomic and geocoded social determinants such as the social vulnerability index51 and area deprivation index52; however, they may have limited effect when individual variables are available 53…”