Evidence map›Paper›PMID 36545752›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2023

Characterizing the relative frequency of clinician engagement with structured social determinants of health data.

Bradley E Iott, Julia Adler-Milstein, Laura M Gottlieb, Matthew S Pantell

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. 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

4 authors.

Bradley E IottCenter for Clinical Informatics and Improvement Research, University of California, San Francisco (UCSF), San Francisco, California, USA.ORCID 0000-0001-9784-0521
Julia Adler-MilsteinCenter for Clinical Informatics and Improvement Research, University of California, San Francisco (UCSF), San Francisco, California, USA.
Laura M GottliebSocial Interventions Research and Evaluation Network, University of California, San Francisco (UCSF), San Francisco, California, USA.
Matthew S PantellCenter for Health and Community, University of California, San Francisco (UCSF), San Francisco, California, USA.

Funding

Addressing Unmet Social Needs among Hospitalized ChildrenK08HS028473 · AHRQ · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI PANTELL, MATTHEW SHANNON · 2022 to 2023
$298k
AHRQ HHS K08 HS028473NICHD NIH HHS L40 HD106442
6 · The paper itself

Abstract

objectiveElectronic health records (EHRs) are increasingly used to capture social determinants of health (SDH) data, though there are few published studies of clinicians' engagement with captured data and whether engagement influences health and healthcare utilization. We compared the relative frequency of clinician engagement with discrete SDH data to the frequency of engagement with other common types of medical history information using data from inpatient hospitalizations. MATERIALS AND

methodsWe created measures of data engagement capturing instances of data documentation (data added/updated) or review (review of data that were previously documented) during a hospitalization. We applied these measures to four domains of EHR data, (medical, family, behavioral, and SDH) and explored associations between data engagement and hospital readmission risk.

resultsSDH data engagement was associated with lower readmission risk. Yet, there were lower levels of SDH data engagement (8.37% of hospitalizations) than medical (12.48%), behavioral (17.77%), and family (14.42%) history data engagement. In hospitalizations where data were available from prior hospitalizations/outpatient encounters, a larger proportion of hospitalizations had SDH data engagement than other domains (72.60%). DISCUSSION: The goal of SDH data collection is to drive interventions to reduce social risk. Data on when and how clinical teams engage with SDH data should be used to inform informatics initiatives to address health and healthcare disparities.

conclusionOverall levels of SDH data engagement were lower than those of common medical, behavioral, and family history data, suggesting opportunities to enhance clinician SDH data engagement to support social services referrals and quality measurement efforts.

Indexed as

Patient ReadmissionSocial Determinants of HealthElectronic Health RecordsHumansMotivationPatient Acceptance of Health Caredocumentationelectronic health recordsengagementreadmissionsreviewsocial determinants of health

Identifiers

PMID36545752
PMCPMC9933071

What OpenQuestion holds

Textmetadata
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.