Literature DB >> 32412300

Social Determinants of Health Improve Predictive Accuracy of Clinical Risk Models for Cardiovascular Hospitalization, Annual Cost, and Death.

Gmerice Hammond1, Kenton Johnston2, Kristine Huang1, Karen E Joynt Maddox1,3.   

Abstract

BACKGROUND: Risk models in the private insurance setting may systematically underpredict in the socially disadvantaged. In this study, we sought to determine whether US minority Medicare beneficiaries had disproportionately low costs compared with their clinical outcomes and whether adding social determinants of health (SDOH) into risk prediction models improves prediction accuracy. METHODS AND
RESULTS: Retrospective observational cohort study of 2016 to 2017 Medicare Current Beneficiary Survey data (n=3614) linked to Medicare fee-for-service claims. Logistic and linear regressions were used to determine the relationship between race/ethnicity and annual costs of care, all-cause hospitalization, cardiovascular hospitalization, and death. We calculated the observed-to-expected (O:E) ratios for all outcomes under 4 risk models: (1) age+sex, (2) model 1+clinical comorbidity adjustment, (3) model 2+SDOH, and (4) SDOH alone. Our sample was 44% male and 11% black or Hispanic. Among minorities, adverse clinical outcomes were inversely related to cost. After multivariable adjustment, blacks/Hispanics had higher rates of cardiovascular hospitalization (incidence rate ratio, 1.78; P=0.012) but similar annual costs ($-336, P=0.77) compared with whites. Among whites, models 1 to 4 all showed similar O:E ratios, suggesting high accuracy in risk prediction using current models. Among minorities, adjustment for age, sex, and comorbidities underpredicted all-cause hospitalization by 20% (O:E, 1.20) and cardiovascular hospitalization by 70% (O:E, 1.70) and overpredicted death by 21% (O:E, 0.79); adding SDOH brought O:E near 1 for all outcomes. Among both groups, the SDOH risk model alone performed with equal or superior accuracy to the model based on clinical comorbidities.
CONCLUSIONS: A paradoxical relationship was observed between clinical outcomes and costs among racial and ethnic minorities. Because of systematic differences in access to care, cost may not be an appropriate surrogate for predicting clinical risk among vulnerable populations. Adjustment for SDOH improves the accuracy of risk models among racial and ethnic minorities and could guide use of prevention strategies.

Entities:  

Keywords:  cohort studies; ethnic groups; health policy; linear models; primary prevention

Year:  2020        PMID: 32412300      PMCID: PMC7299736          DOI: 10.1161/CIRCOUTCOMES.120.006752

Source DB:  PubMed          Journal:  Circ Cardiovasc Qual Outcomes        ISSN: 1941-7713


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4.  The accuracy of the Framingham risk-score in different socioeconomic groups: a prospective study.

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Authors:  Colleen G Koch; Liang Li; George A Kaplan; Jared Wachterman; Mehdi H Shishehbor; Joseph Sabik; Eugene H Blackstone
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6.  Socioeconomic status predicts second cardiovascular event in 29,226 survivors of a first myocardial infarction.

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Review 7.  Stress and the Mental Health of Populations of Color: Advancing Our Understanding of Race-related Stressors.

Authors:  David R Williams
Journal:  J Health Soc Behav       Date:  2018-12

8.  Stress-Associated Neurobiological Pathway Linking Socioeconomic Disparities to Cardiovascular Disease.

Authors:  Ahmed Tawakol; Michael T Osborne; Ying Wang; Basma Hammed; Brian Tung; Tomas Patrich; Blake Oberfeld; Amorina Ishai; Lisa M Shin; Matthias Nahrendorf; Erica T Warner; Jason Wasfy; Zahi A Fayad; Karestan Koenen; Paul M Ridker; Roger K Pitman; Katrina A Armstrong
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9.  Accuracy of Cardiovascular Risk Prediction Varies by Neighborhood Socioeconomic Position: A Retrospective Cohort Study.

Authors:  Jarrod E Dalton; Adam T Perzynski; David A Zidar; Michael B Rothberg; Claudia J Coulton; Alex T Milinovich; Douglas Einstadter; James K Karichu; Neal V Dawson
Journal:  Ann Intern Med       Date:  2017-08-29       Impact factor: 25.391

10.  Social Determinants of Health in the United States: Addressing Major Health Inequality Trends for the Nation, 1935-2016.

Authors:  Gopal K Singh; Gem P Daus; Michelle Allender; Christine T Ramey; Elijah K Martin; Chrisp Perry; Andrew A De Los Reyes; Ivy P Vedamuthu
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Authors:  Kreager A Taber; Jessica N Williams; Weixing Huang; Katherine McLaughlin; Christine Vogeli; Rebecca Cunningham; Lisa Wichmann; Candace H Feldman
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2.  Psychosocial Syndemics and Multimorbidity in Patients with Heart Failure .

Authors:  Kenneth E Freedland; Judith A Skala; Robert M Carney; Brian C Steinmeyer; Michael W Rich
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Review 3.  Social Determinants of Cardiovascular Disease.

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

Authors:  Charlie M Wray; Janet Tang; Lenny López; Katherine Hoggatt; Salomeh Keyhani
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Review 5.  A scoping review on the use of machine learning in research on social determinants of health: Trends and research prospects.

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  5 in total

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