Factors such as food, transportation, and housing instability, social isolation, and neighborhood conditions profoundly impact health outcomes. Shaped by a long history of racial, social, and economic inequity in the US, such factors also underlie health inequities. Many healthcare leaders now recommend systematic documentation of these social risk factors. Yet while social risk data are increasingly available in electronic health records (EHR), research is lacking on how healthcare teams can use these data to improve patient health and decrease health inequities. Social risk-targeted care (referrals to service agencies) can improve health outcomes, but recent research suggests that such improvements are not solely the result of addressing social conditions. Another path to improved outcomes involves social risk-informed care: modifying care plans to account for patients? social risks (e.g., adjusting insulin prescribing so that when food benefits run out at the end of the month, patients are less likely to be hospitalized with hypoglycemia). Such social risk-informed care may seem intuitive, but very little research has examined how care teams can effectively and systematically make such adaptations. This study will be the first to examine how EHR-based clinical decision support (CDS) could support the provision of contextualized, social risk-informed care.
Our Aims are: 1. Obtain stakeholder input from community health center (CHC) staff and patients on care plan adaptations that could mitigate social risks? impact on patient health and ability to adhere to care recommendations. Develop and pilot-test EHR-integrated CDS tools that present social risks and suggest relevant care plan adaptations. 2. Randomize 12 CHCs to receive: Arm 1) a CDS tool with a social risk summary, links to social service information, and a reminder to consider social risks in care planning; or Arm 2) a CDS tool with the same summary, reminder, and links, plus specific care plan adaptation suggestions tailored to a given patient?s social risks. Assess each tool?s impact on selected national Care Quality Measures (CQM), accounting for secular trends. 3. Assess enactment of the tools? suggested care plan adaptations, and patient / staff perceptions of the tools? usability and impact on care quality and patient-provider interactions. Our setting is the nation?s largest group of CHCs on a single EHR. The PIs? work on an upcoming National Academies report directly informed the social risk-informed CDS proposed here. This proposal addresses PAR-19-093?s calls for research on ?using HIT to reduce disparities by increasing ... higher quality care, & improving patient-clinician communication, and health outcomes,? and on ?models for the inclusion and utility of SDoH in EHR systems/CDS tools that ? improve health equity.? The tools developed here will be made available immediately for implementation in any EHR system, enabling rapid dissemination and greater impact of study findings.

Public Health Relevance

Healthcare providers are increasingly using electronic health records to document social / economic risk factors like food, transportation, and housing insecurity, since these factors can profoundly impact patients? health and ability to follow care recommendations. However, little is known about how healthcare teams can best use this newly available social risk information to adapt care plans to meet patients? needs. We will use patient and provider input to develop ?social risk-informed? care adaptation recommendations, then build these recommendations into clinical decision support tools in 12 CHCs? electronic health record. We will examine how providers and patients use these tools, what they think of them, and how they affect patient health outcomes.

Agency
National Institute of Health (NIH)
Institute
National Institute on Minority Health and Health Disparities (NIMHD)
Type
Research Project (R01)
Project #
1R01MD014886-01
Application #
9884048
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Jean-Francois, Beda
Project Start
2020-01-29
Project End
2024-11-30
Budget Start
2020-01-29
Budget End
2020-11-30
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Kaiser Foundation Research Institute
Department
Type
DUNS #
150829349
City
Oakland
State
CA
Country
United States
Zip Code
94612