Cited by 252Electronic Health Records SystemsMedical Coding and Health InformationPrimary Care and Health Outcomes

The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index; none of the 25 sources its claims cite is checked for support yet.

Adoption of Social Determinants of Health EHR Tools by Community Health Centers

Open access

Gold, Rachel, Bunce, Arwen, Cowburn, Stuart, Dambrun, Katie, Dearing, Marla, Middendorf, Mary, Mossman, Ned, Hollombe, Celine, Mahr, Peter, Melgar, Gerardo, Davis, James, Gottlieb, Laura, Cottrell, Erika·2018·The Annals of Family Medicine

DOI 10.1370/afm.2275PMC PMC6131002

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Abstract

PURPOSE: This pilot study assessed the feasibility of implementing electronic health record (EHR) tools for collecting, reviewing, and acting on patient-reported social determinants of health (SDH) data in community health centers (CHCs). We believe it is the first such US study. METHODS: We implemented a suite of SDH data tools in 3 Pacific Northwest CHCs in June 2016, and used mixed methods to assess their adoption through July 2017. We modified the tools at clinic request; for example, we added questions that ask if the patient wanted assistance with SDH needs. RESULTS: Social determinants of health data were collected on 1,130 patients during the study period; 97% to 99% of screened patients (n = 1,098) had ≥1 SDH need documented in the EHR, of whom 211 (19%) had an EHR-documented SDH referral. Only 15% to 21% of patients with a documented SDH need indicated wanting help. Examples of lessons learned on adoption of EHR SDH tools indicate that clinics should: consider how to best integrate tools into existing workflow processes; ensure that staff tasked with SDH efforts receive adequate tool training and access; and consider that timing of data entry impacts how and when SDH data can be used. CONCLUSIONS: Our results indicate that adoption of systematic EHR-based SDH documentation may be feasible, but substantial barriers to adoption exist. Lessons from this study may inform primary care providers seeking to implement SDH-related efforts, and related health policies. Far more research is needed to address implementation barriers related to SDH documentation in EHRs.

AI snapshot

Written from the paper’s full text.

TL;DR

This pilot implemented EHR tools for collecting, reviewing, and acting on patient-reported social determinants of health (SDH) data in 3 Pacific Northwest community health centers. It found systematic EHR-based SDH documentation feasible but identified substantial adoption barriers, with high positive screening rates but low referral and patient-requested-help rates.

Key findings

SDH data were collected on 1,130 patients, representing 4% to 18% of adult patients with an ambulatory visit at the pilot clinics; 97% to 99% of screened patients had ≥1 SDH need documented, and 211 (19%) had an EHR-documented SDH referral.
After questions about wanting help were added, 15% of Clinic A patients and 21 of Clinic B patients with a documented SDH need requested help.
Facilitators included a trusted, EHR-savvy clinic champion, ability to customize EHR views, and reporting requirements; barriers included fragmented patient data, added workflow difficulty, paper-based data entry, time-consuming referrals, and unmanageable follow-up workload before desire-for-help questions were added.
The clinics successfully documented SDH in the EHR and continued post-study, but referral documentation was especially challenging.

Methods

Concurrent mixed-methods pilot at 3 OCHIN member community health centers in the Pacific Northwest; Epic-based SDH tools built on PRAPARE were deployed in June 2016 and assessed through July 2017, extended from 12 to 13 months.
Quantitative EHR data described adult patients with documented SDH data or ≥1 ambulatory visit, including demographics, SDH needs, referrals, and problem list diagnoses.
Qualitative data included 6 days of workflow observation, 24 interviews with care team members, and observations of clinic decision-maker discussions; analysis used deductive and inductive coding and the constant comparative method.

Limitations

The paper states it could not calculate SDH screening documentation rates among targeted patients because target populations changed, change dates were unclear, and target criteria were not easily extracted from the EHR; screened vs unscreened differences therefore cannot be interpreted as related to EHR-based SDH screening.
The paper states screened-patient counts may be low and SDH need prevalence may be higher than in the overall population because some paper surveys were likely not entered into the EHR; referral rates are likely underestimated because referrals were often documented in chart notes rather than discrete fields.
The paper states it could not assess changes in SDH status, care quality, or biomarkers; could not quantify how often the SDH summary was accessed or by whom; the SDH screening measures have not been validated as predictive of specific outcomes; and the single EHR system limits transferability. Evident from the text: this was a small 3-clinic pilot with clinic-selected pragmatic target groups and no control or comparison group.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1370/afm.2275

Cites

55 of 55 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 25 cited sources checked · 0 supported · 0 flagged

A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Only 15% to 21% of patients with a documented SDH need indicated wanting help.”
- Also stated in: § SDH Screening Documentation and Referrals · plain
  “15% of Clinic A patients and 21% of Clinic B patients with a documented need requested help.”
§ Adoption of Social Determinants of Health EHR Tools by Community Health Centers > Abstract
Strength:plain· not yet calibratedn = 182
Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“97% to 99% of screened patients (n = 1,098) had ≥1 SDH need documented in the EHR”
- Also stated in: § SDH Screening Documentation and Referrals · hedged
  “Most screened patients (97% to 99%) indicated a potential SDH need in ≥1 SDH domain”
§ Adoption of Social Determinants of Health EHR Tools by Community Health Centers > Abstract
Strength:plain· not yet calibratedn = 1,098
Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes

Show all 30 claims

It may state two separate claims as one. 26
Probably not a substantial claim. 23

A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Social determinants of health data were collected on 1,130 patients during the study period”
- Also stated in: § SDH Screening Documentation and Referrals · plain
  “Social determinants of health data were collected on 1,130 patients, representing 4% to 18% of adult patients with an ambulatory visit at the pilot clinics during the study period (Table 2 and Table 3).”
§ Adoption of Social Determinants of Health EHR Tools by Community Health Centers > Abstract
Strength:plain· not yet calibratedn = 1,130
Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes
It may state two separate claims as one.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“While some aspects of the tools were not widely adopted, this is common to such efforts [58][59][60][61] ; adoption of new EHR tools can take time.”
§ Adoption of Social Determinants of Health EHR Tools by Community Health Centers > DISCUSSION
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [58]
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [59]
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [60]
Strength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“SDH documentation, review, and referral-making in EHRs can be feasible and useful, but is challenging to adopt.63”
§ Adoption of Social Determinants of Health EHR Tools by Community Health Centers > DISCUSSION
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [63]
Load-bearingStrength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
In the paper
“Analysis followed the constant comparative method 46 ; new data were compared with previously collected/coded data to detect commonalities/differences, and to develop nuanced understandings of clinic experiences.”
§ Adoption of Social Determinants of Health EHR Tools by Community Health Centers > Data Collection and Analyses
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [46]
Strength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Before benefits can be fully realized, the unique challenges of EHR-based SDH documentation and referral-making must be understood and addressed.1,39,48”
§ Adoption of Social Determinants of Health EHR Tools by Community Health Centers > DISCUSSION
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [1]
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [39]
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [48]
Load-bearingStrength:plain· not yet calibratedCausal:conditional· not yet calibrated
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passes
Probably not a substantial claim. It may be too vague to check against evidence.
In the paper
“Our findings are consistent with those of a prior case study on EHR-based SDH documentation.62”
§ Adoption of Social Determinants of Health EHR Tools by Community Health Centers > DISCUSSION
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [62]
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.

36 of 36

The authors state this as an assumption.
The study is the first US study on the collection of SDH data using EHR-based tools in community health centers.
“We believe it is the first such US study.”
“We believe this is the first US study on the collection of SDH data using EHR-based tools in CHCs.”
The paper relies on this without support.
Most health care systems document and track most patient information in EHRs.
“Since most health care systems document and track most patient information in EHRs, SDH data should also be in EHRs.”

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“However, its application in oncology populations has been limited (Gold et al., 2018).”

Authors: Gold, R., Bunce, A., Cowburn, S., Dambrun, K., Dearing, M., Middendorf, M., Mossman, N., Hollombe, C., Mahr, P., Melgar, G., Davis, J., Gottlieb, L., & Cottrell, E.
Affiliations: Kaiser Permanente Center for Health Research (US)
Ochin (US)
Multnomah County Health Department (US)
University of California, San Francisco (US)
ORCID: Gold, Rachel
Bunce, Arwen
Cowburn, Stuart
Gottlieb, Laura
Cottrell, Erika
Venue: The Annals of Family Medicine
Publisher: Annals of Family Medicine
Published: 2018-09
Volume: 16
Issue: 5
Pages: 399-407
ISSN: 1544-1709 (ISSN-L)
1544-1717
DOI: 10.1370/afm.2275
PMC: PMC6131002
OpenAlex: W2891941547
Semantic Scholar: ec90bbff459f6d579a5de4a0ee6586f1aebfa662
Cited by: 252
References: 55
Citations by year: 2026: 21 · 2025: 32 · 2024: 25 · 2023: 38 · 2022: 38 · 2021: 42 · 2020: 31 · 2019: 23 · 2018: 2
FWCI: 31.11
Type: journal article
Language: en
Open access: diamond
doi.org
Locations: The Annals of Family Medicine (publishedVersion)
Europe PMC (PubMed Central) (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
eScholarship (California Digital Library) (submittedVersion)
Funders: National Institute of Diabetes and Digestive and Kidney Diseases (R18DK105463)
Topics: Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
Health Sciences › Medicine › Family Practice › Primary Care and Health Outcomes
Keywords: social determinants of health, electronic health records, community health centers, social needs screening, referral documentation, implementation barriers, primary care, health policy
MeSH terms: Community Health Centers, Documentation, Feasibility Studies, Health Plan Implementation, Humans, Pilot Projects, Referral and Consultation, Electronic Health Records, Social Determinants of Health

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Adoption of Social Determinants of Health EHR Tools by Community Health Centers

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