JMIR Publications

ABSTRACT

Background:

Targeting modifiable health behaviors can significantly reduce risk of disease, and result in saving up to 30% of health care costs. Recent interventions for affecting health behaviors are based on combining the social determinants of health (SDOH) and biosocial perspectives, shifting the focus from the individual to broader societal contexts under the SDOH approach. Tools for screening patients for individual and societal factors are being increasingly integrated into electronic health record (EHR) systems. Epic Systems © is one of the leading and most adopted EHR across the globe, with modules on SDOH and modifiable risk factors. There is a gap in literature on integration and use of screening tools for SDOH and modifiable risk factors.

Objective:

To synthesize evidence on the integration of screening tools for SDOH and modifiable risk factors in the Epic EHR, focusing on approaches, lessons, and impact.

Methods:

We followed established methods for conducting and reporting scoping reviews, including Joanna Briggs Institute’s (JBI) guidance, Arksey and O’Malley’s framework and the PRISMA-ScR checklist. We included 3 peer reviewed databases, 2 grey literature sources and citation chained from related reviews and articles.

Results:

All included studies (n=43) were from USA, spanning 24 states. Methods included 26 quantitative, 12 mixed methods, and 6 qualitative studies, across a variety of health settings. Most studies focused on adults, with data collected from patients on SDOH, and a smaller proportion for modifiable risk factors. Among the SDOH domains, housing, food and transportation were the top three, while physical activity, alcohol and tobacco were the most common risk factors targeted. There were a variety of screening tools used, with the PRAPARE tool being used the most across 6 studies. Most integrations used enhanced support or optimized workflows, with MyChart and Best Practice Advisories being the most used in-built Epic modules. MyChart was the most accepted module among patients. Screening and referral patient outcomes varied, with many studies presenting significant impact. Most important facilitators to integration included leadership support, dedicated clinical champions, and well-defined roles. Barriers to integration were clinician time, inefficient workflows, and availability of devices and staff to ensure use of integrated tools.

Conclusions:

Integration of SDOH and modifiable risk factors in the Epic EHR are being increasingly adopted to capture and target equitable health services. While Epic is one of the most globally adopted EHRs, studies are primarily from the USA. Epic’s SDOH wheel module is not sufficient for capturing context-based SDOH and behavioral domains. In addition, there is an increasing need for standardization of domains and tools. Future research is needed for enhanced learning on improvement and use of in-built tools, standardization, and processes for integrating interventions for targeting patient needs. Clinical Trial: Not applicable.