Elyse C Lasser1, Julia M Kim2, Elham Hatef3, Hadi Kharrazi4, Jill A Marsteller5, Lisa Ross DeCamp6. 1. E.C. Lasser is research associate, Johns Hopkins Center for Population Health Information Technology, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; ORCID: https://orcid.org/0000-0002-1758-9822. 2. J.M. Kim is assistant professor, Department of Pediatrics, and faculty, Armstrong Institute for Patient Safety and Quality, Johns Hopkins University School of Medicine, Baltimore, Maryland; ORCID: https://orcid.org/0000-0001-5678-6629. 3. E. Hatef is assistant scientist, Johns Hopkins Center for Population Health Information Technology and Center for Health Disparities Solutions, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; ORCID: https://orcid.org/0000-0003-2535-8191. 4. H. Kharrazi is associate professor, Johns Hopkins Center for Population Health Information Technology, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; ORCID: https://orcid.org/0000-0003-1481-4323. 5. J.A. Marsteller is professor, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health and Armstrong Institute for Patient Safety and Quality, Johns Hopkins University School of Medicine, Baltimore, Maryland; ORCID: https://orcid.org/0000-0002-8458-954X. 6. L.R. DeCamp is associate professor, ACCORDS (Adult and Child Consortium for Health Outcomes Research and Delivery Science), Department of Pediatrics, University of Colorado School of Medicine and Children's Hospital Colorado, Denver, Colorado; ORCID: https://orcid.org/0000-0002-5210-4675.
Abstract
PURPOSE: Social and behavioral determinants of health (SBDH) are important factors that affect the health of individuals but are not routinely captured in a structured and systematic manner in electronic health records (EHRs). The purpose of this study is to generate recommendations for systematic implementation of SBDH data collection in EHRs through (1) reviewing SBDH conceptual and theoretical frameworks and (2) eliciting stakeholder perspectives on barriers to and facilitators of using SBDH information in the EHR and priorities for data collection. METHOD: The authors reviewed SBDH frameworks to identify key social and behavioral variables and conducted focus groups and interviews with 17 clinicians and researchers at Johns Hopkins Health System between March and May 2018. Transcripts were coded and common themes were extracted to understand the barriers to and facilitators of accessing SBDH information. RESULTS: The authors found that although the frameworks agreed that SBDH affect health outcomes, the lack of model consensus complicates the development of specific recommendations for the prioritization of SBDH data collection. Study participants recognized the importance of SBDH information and individual health and agreed that patient-reported information should be captured, but clinicians and researchers cited different priorities for which variables are most important. For the few SBDH variables that are captured, participants reported that data were often incomplete, unclear, or inconsistent, affecting both researcher and clinician responses to SBDH barriers to health. CONCLUSIONS: Health systems need to identify and prioritize the systematic implementation of collection of a high-impact but limited list of SBDH variables in the EHR. These variables should affect care and be amenable to change and collection should be integrated into clinical workflows. Improved data collection of SBDH variables can lead to a better understanding of how SBDH affect health outcomes and ways to better address underlying health disparities that need urgent action.
PURPOSE: Social and behavioral determinants of health (SBDH) are important factors that affect the health of individuals but are not routinely captured in a structured and systematic manner in electronic health records (EHRs). The purpose of this study is to generate recommendations for systematic implementation of SBDH data collection in EHRs through (1) reviewing SBDH conceptual and theoretical frameworks and (2) eliciting stakeholder perspectives on barriers to and facilitators of using SBDH information in the EHR and priorities for data collection. METHOD: The authors reviewed SBDH frameworks to identify key social and behavioral variables and conducted focus groups and interviews with 17 clinicians and researchers at Johns Hopkins Health System between March and May 2018. Transcripts were coded and common themes were extracted to understand the barriers to and facilitators of accessing SBDH information. RESULTS: The authors found that although the frameworks agreed that SBDH affect health outcomes, the lack of model consensus complicates the development of specific recommendations for the prioritization of SBDH data collection. Study participants recognized the importance of SBDH information and individual health and agreed that patient-reported information should be captured, but clinicians and researchers cited different priorities for which variables are most important. For the few SBDH variables that are captured, participants reported that data were often incomplete, unclear, or inconsistent, affecting both researcher and clinician responses to SBDH barriers to health. CONCLUSIONS: Health systems need to identify and prioritize the systematic implementation of collection of a high-impact but limited list of SBDH variables in the EHR. These variables should affect care and be amenable to change and collection should be integrated into clinical workflows. Improved data collection of SBDH variables can lead to a better understanding of how SBDH affect health outcomes and ways to better address underlying health disparities that need urgent action.
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