Evidence map›Paper›PMID 36279133›Full record

Trial reportJAMA network open2022

Effect of Electronic Health Record Clinical Decision Support on Contextualization of Care: A Randomized Clinical Trial.

Saul J Weiner, Alan Schwartz, Frances Weaver, William Galanter, Sarah Olender, Karl Kochendorfer, Amy Binns-Calvey, Ravisha Saini, Sana Iqbal, Monique Diaz and 2 more

Registry-linked trialOpen access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03244033 (Integrating Contextual Factors Into Clinical Decision Support to Reduce Contextual Error and Improve Outcomes in Ambulatory Care), which is not on this map. Cited by 18 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 4 pooled it
4.5field-weighted citation impact, top 5% of its field
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.

NCT03244033 nacompletednot on this map

Integrating Contextual Factors Into Clinical Decision Support to Reduce Contextual Error and Improve Outcomes in Ambulatory Care

TypeinterventionalSponsorUniversity of Illinois at ChicagoRan2018 to 2021Enrolled452ConditionsMedical Errors, Decision Support Systems, Clinical, Diagnostic ErrorsArmsContextual clinical decision support, Contextual survey
3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 4 syntheses or guidelines pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  4. Pooled it
  5. The Utility of Large Language Models to Assist With Emergency Triage Decisions Within Otolaryngology.Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery · 2026
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  13. Context factors in clinical decision-making: a scoping review.BMC medical informatics and decision making · 2025
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  17. Review
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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

12 authors at 9 institutions in 1 country.

Saul J WeinerDepartment of Medicine, College of Medicine, University of Illinois Chicago.
Alan SchwartzDepartment of Medical Education, College of Medicine, University of Illinois Chicago.
Frances WeaverCenter of Innovation for Complex Chronic Healthcare, Edward Hines, Jr VA Hospital, Hines, Illinois.
William GalanterDepartment of Medicine, College of Medicine, University of Illinois Chicago.
Sarah OlenderUniversity of Illinois Cancer Center, College of Medicine, University of Illinois Chicago.
Karl KochendorferDepartment of Family and Community Medicine, College of Medicine, University of Illinois Chicago.
Amy Binns-CalveyDepartment of Medicine, College of Medicine, University of Illinois Chicago.
Ravisha SainiDepartment of Medicine, College of Medicine, University of Illinois Chicago.
Sana IqbalClinical Research Office, Health Sciences Campus, Loyola University Chicago, Maywood, Illinois.
Monique DiazDignity Health, Pacific Central Coast Health Centers, Arroyo Grande, California.
Aaron MichelfelderDepartment of Family Medicine, Stritch School of Medicine, Loyola University Chicago, Maywood, Illinois.
Anita VarkeyOak Street Health, East Point, Georgia.
Edward Hines, Jr. VA Hospital · USUniversity of Illinois Chicago · USUniversity of Illinois Urbana-Champaign · USDignity Health · USJesse Brown VA Medical Center · USLoyola Medicine · USLoyola University Chicago · USPoint University · USUniversity of Chicago Medical Center · US

Funding

Integrating Contextual Factors into Clinical Decision Support to Reduce Contextual Error and Improve Outcomes in Ambulatory CareR01HS025374 · AHRQ · UNIVERSITY OF ILLINOIS AT CHICAGO · PI WEINER, SAUL J. · 2017 to 2020
$1.5M
AHRQ HHS R01 HS025374
6 · The paper itself

Abstract

Importance: Contextualizing care is a process of incorporating information about the life circumstances and behavior of individual patients, termed contextual factors, into their plan of care. In 4 steps, clinicians recognize clues (termed contextual red flags), clinicians ask about them (probe for context), patients disclose contextual factors, and clinicians adapt care accordingly. The process is associated with a desired outcome resolution of the presenting contextual red flag. Objective: To determine whether contextualized clinical decision support (CDS) tools in the electronic health record (EHR) improve clinician contextual probing, attention to contextual factors in care planning, and the presentation of contextual red flags. Design, Setting, and Participants: This randomized clinical trial was performed at the primary care clinics of 2 academic medical centers with different EHR systems. Participants were adults 18 years or older consenting to audio record their visits and their physicians between September 6, 2018, and March 4, 2021. Patients were randomized to an intervention or a control group. Analyses were performed on an intention-to-treat basis. Interventions: Patients completed a previsit questionnaire that elicited contextual red flags and factors and appeared in the clinician's note template in a contextual care box. The EHR also culled red flags from the medical record, included them in the contextual care box, used passive and interruptive alerts, and proposed relevant orders. Main Outcomes and Measures: Proportion of contextual red flags noted at the index visit that resolved 6 months later (primary outcome), proportion of red flags probed (secondary outcome), and proportion of contextual factors addressed in the care plan by clinicians (secondary outcome), adjusted for study site and for multiple red flags and factors within a visit. Results: Four hundred fifty-two patients (291 women [65.1%]; mean [SD] age, 55.6 [15.1] years) completed encounters with 39 clinicians (23 women [59.0%]). Contextual red flags were not more likely to resolve in the intervention vs control group (adjusted odds ratio [aOR], 0.96 [95% CI, 0.57-1.63]). However, the intervention increased both contextual probing (aOR, 2.12 [95% CI, 1.14-3.93]) and contextualization of the care plan (aOR, 2.67 [95% CI, 1.32-5.41]), controlling for whether a factor was identified by probing or otherwise. Across study groups, contextualized care plans were more likely than noncontextualized plans to result in improvement in the presenting red flag (aOR, 2.13 [95% CI, 1.38-3.28]). Conclusions and Relevance: This randomized clinical trial found that contextualized CDS did not improve patients' outcomes but did increase contextualization of their care, suggesting that use of this technology could ultimately help improve outcomes. Trial Registration: ClinicalTrials.gov Identifier: NCT03244033.

Indexed as

Decision Support Systems, ClinicalElectronic Health RecordsAcademic Medical CentersAdultFemaleHumansMiddle Aged

Identifiers

PMID36279133
PMCPMC9593230
OpenAlexW4307299474

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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.