Evidence map›Paper›PMID 40953441›Full record

ArticleJournal of medical Internet research2025

Integration of Screening and Referral Tools for Social Determinants of Health and Modifiable Lifestyle Factors in the Epic Electronic Health Record System: Scoping Review.

Jawad Ahmed Chishtie, Jenice Tea, Manuel Ester, Gehna Rasheed, Nicelle Chua, Marcus Vaska, Gary Teare, Kamala Adhikari

Abstract readScoping Review
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jawad Ahmed ChishtieCancer Prevention and Screening Innovation, Public Health Evidence and Innovation, Primary Care Alberta, Calgary, AB, Canada.ORCID https://orcid.org/0000-0001-8650-4469
Jenice TeaCancer Prevention and Screening Innovation, Public Health Evidence and Innovation, Primary Care Alberta, Calgary, AB, Canada.ORCID https://orcid.org/0009-0009-3485-0752
Manuel EsterCancer Prevention and Screening Innovation, Public Health Evidence and Innovation, Primary Care Alberta, Calgary, AB, Canada.ORCID https://orcid.org/0000-0002-4961-6063
Gehna RasheedCancer Prevention and Screening Innovation, Public Health Evidence and Innovation, Primary Care Alberta, Calgary, AB, Canada.ORCID https://orcid.org/0009-0002-4895-2337
Nicelle ChuaCancer Prevention and Screening Innovation, Public Health Evidence and Innovation, Primary Care Alberta, Calgary, AB, Canada.ORCID https://orcid.org/0009-0008-5318-3097
Marcus VaskaLibrary Services, Acute Care Alberta, Calgary, AB, Canada.ORCID https://orcid.org/0000-0002-4753-3213
Gary TeareCancer Prevention and Screening Innovation, Public Health Evidence and Innovation, Primary Care Alberta, Calgary, AB, Canada.ORCID https://orcid.org/0000-0002-7655-7409
Kamala AdhikariCancer Prevention and Screening Innovation, Public Health Evidence and Innovation, Primary Care Alberta, Calgary, AB, Canada.ORCID https://orcid.org/0000-0003-2872-9496

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecent health behavior interventions combine social determinants of health (SDOH) and biosocial perspectives, refocusing from the individual to broader societal contexts under the SDOH approach. Targeting modifiable health behaviors can significantly reduce disease risk and save up to 30% of health care costs. Screening tools individual and societal factors are being increasingly integrated into electronic health record (EHR) systems. Epic Systems is a leading, most adopted EHRs worldwide, with modules on SDOH and modifiable risk factors. Literature on integration and use of screening tools for SDOH and modifiable risk factors is lacking.

objectiveThis review aimed to (1) summarize evidence integrating screening and referral tools for SDOH and modifiable risk factors including tobacco/alcohol use and physical inactivity in the Epic EHR; (2) synthesize findings on implementation methods, processes, clinical workflow modifications, and outcomes from integrating SDOH screening and referral tools in EHR systems; and (3) capture the major barriers, facilitators, and lessons learned across the included implementation studies.

methodsWe followed Joanna Briggs Institute's guidelines, Arksey and O'Malley's framework, and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. We included 3 peer-reviewed databases, 2 gray literature sources, and citation chaining from related reviews and articles.

resultsAll included studies (n=43) were from 24 US states; 26 reported quantitative methods, 12 reported mixed methods, and 6 were qualitative studies across various health settings. Most studies focused on adults, with the top 3 SDOH domains being housing, food and transportation, while physical activity, alcohol and tobacco were the most common modifiable risk factors. The top 3 SDOH domains were housing, food, and transportation, while physical activity, alcohol, and tobacco use were the most common risk factors targeted. Various screening tools were used, with the Protocol for Responding to & Assessing Patients' Assets, Risks, and Experiences (PRAPARE) 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 Epic modules and functions. MyChart was the most patient-accepted module. Screening and referral patient outcomes varied, with many studies presenting a significant impact. The most important integration facilitators included leadership support, dedicated clinical champions, and well-defined roles; barriers included clinician time, inefficient workflows, and the availability of devices and staff to ensure integrated tools' usage.

conclusionsIntegration of SDOH and modifiable risk factors in the Epic EHR is being increasingly adopted to capture and target equitable health services. While Epic is among the most globally adopted EHRs, studies are primarily from the United States. Epic's SDOH wheel module is insufficient in capturing context-based SDOH and behavioral domains. Need for contextual standardization of SDOH and modifiable risk factor domains and EHR tools is being increasingly felt. Future research is needed for enhanced learning, improvement and use of built-in and customized tools, standardization, and processes for integrating targeted patient-centered interventions.

Indexed as

Electronic Health RecordsLife StyleMass ScreeningReferral and ConsultationSocial Determinants of HealthHumansRisk Factorselectronic health recordEpic EHR systemintegrationmodifiable risk factorsoptimization.social determinants of health

Identifiers

PMID40953441
PMCPMC12494108

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.