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. 2024 Jan 9;8(1):e17.
doi: 10.1017/cts.2024.2. eCollection 2024.

Toward standardization, harmonization, and integration of social determinants of health data: A Texas Clinical and Translational Science Award institutions collaboration

Catherine K Craven  1   2 , Linda Highfield  3 , Mujeeb Basit  4 , Elmer V Bernstam  5 , Byeong Yeob Choi  1   6 , Robert L Ferrer  7 , Jonathan A Gelfond  1   6 , Sandi L Pruitt  8 , Vaishnavi Kannan  9 , Paula K Shireman  10   11 , Heidi Spratt  12 , Kayla J Torres Morales  1   2 , Chen-Pin Wang  1   6 , Zhan Wang  1   2 , Meredith N Zozus  1   2 , Edward C Sankary  13 , Susanne Schmidt  1
Affiliations

Toward standardization, harmonization, and integration of social determinants of health data: A Texas Clinical and Translational Science Award institutions collaboration

Catherine K Craven et al. J Clin Transl Sci. .

Erratum in

Abstract

Introduction: The focus on social determinants of health (SDOH) and their impact on health outcomes is evident in U.S. federal actions by Centers for Medicare & Medicaid Services and Office of National Coordinator for Health Information Technology. The disproportionate impact of COVID-19 on minorities and communities of color heightened awareness of health inequities and the need for more robust SDOH data collection. Four Clinical and Translational Science Award (CTSA) hubs comprising the Texas Regional CTSA Consortium (TRCC) undertook an inventory to understand what contextual-level SDOH datasets are offered centrally and which individual-level SDOH are collected in structured fields in each electronic health record (EHR) system potentially for all patients.

Methods: Hub teams identified American Community Survey (ACS) datasets available via their enterprise data warehouses for research. Each hub's EHR analyst team identified structured fields available in their EHR for SDOH using a collection instrument based on a 2021 PCORnet survey and conducted an SDOH field completion rate analysis.

Results: One hub offered ACS datasets centrally. All hubs collected eleven SDOH elements in structured EHR fields. Two collected Homeless and Veteran statuses. Completeness at four hubs was 80%-98%: Ethnicity, Race; < 10%: Education, Financial Strain, Food Insecurity, Housing Security/Stability, Interpersonal Violence, Social Isolation, Stress, Transportation.

Conclusion: Completeness levels for SDOH data in EHR at TRCC hubs varied and were low for most measures. Multiple system-level discussions may be necessary to increase standardized SDOH EHR-based data collection and harmonization to drive effective value-based care, health disparities research, translational interventions, and evidence-based policy.

Keywords: Social determinants of health; electronic health records; health information interoperability; health level seven; translational science.

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Conflict of interest statement

The authors have no competing interests to declare.

Figures

Figure 1.
Figure 1.
Percent complete of individual-level social determinants of health data elements collected in a structured field in the electronic health record system at four participating Clinical and Translational Science Award institutions.
See this image and copyright information in PMC

References

    1. Bowleg L. We’re not all in this together: on COVID-19, Intersectionality, and structural inequality. Am J Public Health. 2020;110(7):917–917. doi: 10.2105/ajph.2020.305766. - DOI - PMC - PubMed
    1. Castillo EG, Harris C. Directing research toward health equity: a health equity research impact assessment. J Gen Intern Med. 2021;36(9):2803–2808. doi: 10.1007/s11606-021-06789-3. - DOI - PMC - PubMed
    1. Hao B, Hu Y, Sotudian S, et al. Development and validation of predictive models for COVID-19 outcomes in a safety-net hospital population. JAMIA. 2022;14(7):1253–1262. doi: 10.1093/jamia/ocac062. - DOI - PMC - PubMed
    1. Tai DBG, Sia IG, Doubeni CA, Wieland ML. Disproportionate impact of COVID-19 on racial and ethnic minority groups in the United States: a 2021 Update. J Racial Ethn Health Disparities. 2022;9(6):2334–2339. doi: 10.1007/s40615-021-01170-w. - DOI - PMC - PubMed
    1. Holden TM, Simon MA, Arnold DT, Halloway V, Gerardin J. Structural racism and COVID-19 response: higher risk of exposure drives disparate COVID-19 deaths among black and hispanic/Latinx residents of Illinois, USA. BMC Public Health. 2022;22(1):312. doi: 10.1186/s12889-022-12698-9. - DOI - PMC - PubMed

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