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Integrating Social and Behavioral Determinants of Health into Patient Care and Population Health at Veterans Health Administration: a Conceptual Framework and an Assessment of Available Individual and Population Level Data Sources and Evidence-based...

Overview
Specialty Public Health
Date 2019 Oct 23
PMID 31637271
Citations 13
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Abstract

The premise of this project was that social and behavioral determinants of health (SBDH) affect the use of healthcare services and outcomes for patients in an integrated healthcare system such as the Veterans Health Administration (VHA), and thus individual patient level socio-behavioral factors in addition to the neighborhood characteristics and geographically linked factors could add information beyond medical factors mostly considered in clinical decision making, patient care, and population health. To help VHA better address SBDH risk factors for the veterans it cares for within its primary care clinics, we proposed a conceptual and analytic framework, a set of evidence-based measures, and their data source. The framework and recommended SBDH metrics can provide a road map for other primary care-centric healthcare organizations wishing to use health analytic tools to better understand how SBDH affect health outcomes.

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References
1.
Oreskovic N, Maniates J, Weilburg J, Choy G . Optimizing the Use of Electronic Health Records to Identify High-Risk Psychosocial Determinants of Health. JMIR Med Inform. 2017; 5(3):e25. PMC: 5575417. DOI: 10.2196/medinform.8240. View

2.
Wang L, Ruan X, Yang P, Liu H . Comparison of Three Information Sources for Smoking Information in Electronic Health Records. Cancer Inform. 2016; 15:237-242. PMC: 5147453. DOI: 10.4137/CIN.S40604. View

3.
Bhavsar N, Gao A, Phelan M, Pagidipati N, Goldstein B . Value of Neighborhood Socioeconomic Status in Predicting Risk of Outcomes in Studies That Use Electronic Health Record Data. JAMA Netw Open. 2019; 1(5):e182716. PMC: 6324505. DOI: 10.1001/jamanetworkopen.2018.2716. View

4.
Hatef E, Searle K, Predmore Z, Lasser E, Kharrazi H, Nelson K . The Impact of Social Determinants of Health on Hospitalization in the Veterans Health Administration. Am J Prev Med. 2019; 56(6):811-818. DOI: 10.1016/j.amepre.2018.12.012. View

5.
Kharrazi H, Anzaldi L, Hernandez L, Davison A, Boyd C, Leff B . The Value of Unstructured Electronic Health Record Data in Geriatric Syndrome Case Identification. J Am Geriatr Soc. 2018; 66(8):1499-1507. DOI: 10.1111/jgs.15411. View