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Toward standardization, harmonization, and integration of social determinants of health data: A Texas Clinical and Translational Science Award institutions collaboration.
Craven, Catherine K; Highfield, Linda; Basit, Mujeeb; Bernstam, Elmer V; Choi, Byeong Yeob; Ferrer, Robert L; Gelfond, Jonathan A; Pruitt, Sandi L; Kannan, Vaishnavi; Shireman, Paula K; Spratt, Heidi; Morales, Kayla J Torres; Wang, Chen-Pin; Wang, Zhan; Zozus, Meredith N; Sankary, Edward C; Schmidt, Susanne.
Affiliation
  • Craven CK; Department of Population Health Sciences, University of Texas Health Science Center San Antonio, Joe R. and Teresa Lozano Long School of Medicine, San Antonio, TX, USA.
  • Highfield L; Division of Clinical Research Informatics, University of Texas Health Science Center San Antonio, Joe R. and Teresa Lozano Long School of Medicine, San Antonio, TX, USA.
  • Basit M; University of Texas Health Science Center at Houston, School of Public Health, San Antonio, TX, USA.
  • Bernstam EV; Department of Internal Medicine, Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Choi BY; D. Bradley McWilliams School of Biomedical Informatics and Division of General Internal Medicine, University of Texas Health Science Center at Houston, McGovern Medical School, Houston, TX, USA.
  • Ferrer RL; Department of Population Health Sciences, University of Texas Health Science Center San Antonio, Joe R. and Teresa Lozano Long School of Medicine, San Antonio, TX, USA.
  • Gelfond JA; Biostatistics Division, University of Texas Health Science Center San Antonio, Joe R. and Teresa Lozano Long School of Medicine, San Antonio, TX, USA.
  • Pruitt SL; Department of Community and Family Medicine, University of Texas Health Science Center San Antonio, Joe R. and Teresa Lozano Long School of Medicine, San Antonio, TX, USA.
  • Kannan V; Department of Population Health Sciences, University of Texas Health Science Center San Antonio, Joe R. and Teresa Lozano Long School of Medicine, San Antonio, TX, USA.
  • Shireman PK; Biostatistics Division, University of Texas Health Science Center San Antonio, Joe R. and Teresa Lozano Long School of Medicine, San Antonio, TX, USA.
  • Spratt H; University of Texas Southwestern Medical Center, Harold C. Simmons Comprehensive Cancer Center, Dallas, TX, USA.
  • Morales KJT; Houston Methodist, Houston, TX, USA.
  • Wang CP; Department of Surgery, Division of Vascular and Endovascular Surgery, Texas A&M University School of Medicine, Bryan, TX, USA.
  • Wang Z; Departments of Primary Care & Rural Medicine and Medical Physiology, University of Texas Health Science Center San Antonio, San Antonio, TX, USA.
  • Zozus MN; Department of Biostatistics and Data Science, University of Texas Medical Branch Galveston, Galveston, TX, USA.
  • Sankary EC; Department of Population Health Sciences, University of Texas Health Science Center San Antonio, Joe R. and Teresa Lozano Long School of Medicine, San Antonio, TX, USA.
  • Schmidt S; Division of Clinical Research Informatics, University of Texas Health Science Center San Antonio, Joe R. and Teresa Lozano Long School of Medicine, San Antonio, TX, USA.
J Clin Transl Sci ; 8(1): e17, 2024.
Article in En | MEDLINE | ID: mdl-38384919
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Clin Transl Sci Year: 2024 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Clin Transl Sci Year: 2024 Type: Article Affiliation country: United States