Evidence map›Paper›PMID 36463877›Full record

ReviewYearbook of medical informatics2022

Electronic Health Record-Integrated Clinical Decision Support for Clinicians Serving Populations Facing Health Care Disparities: Literature Review.

Carole H Stipelman, Polina V Kukhareva, Elly Trepman, Quang-Tuyen Nguyen, Lourdes Valdez, Colleen Kenost, Maia Hightower, Kensaku Kawamoto

Open access · hybridAbstract readReview
In one paragraph

Review in Yearbook of medical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
5.9field-weighted citation impact, top 4% 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.

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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Advancing equity and value in United States healthcare: an umbrella review.International journal for equity in health · 2026
    Pooled it
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  9. Applying Machine Learning Techniques to Implementation Science.Online journal of public health informatics · 2024
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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

8 authors at 2 institutions in 2 countries.

Carole H StipelmanDepartment of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT, USA.
Polina V KukharevaDepartment of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA.
Elly TrepmanDepartment of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, MB, Canada.
Quang-Tuyen NguyenDepartment of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT, USA.
Lourdes ValdezDepartment of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA.
Colleen KenostDepartment of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA.
Maia HightowerHealth Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA.
Kensaku KawamotoDepartment of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA.
University of Utah · USUniversity of South Alabama · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo review current studies about designing and implementing clinician-facing clinical decision support (CDS) integrated or interoperable with an electronic health record (EHR) to improve health care for populations facing disparities.

methodsWe searched PubMed to identify studies published between January 1, 2011 and October 22, 2021 about clinician-facing CDS integrated or interoperable with an EHR. We screened abstracts and titles and extracted study data from articles using a protocol developed by team consensus. Extracted data included patient population characteristics, clinical specialty, setting, EHR, clinical problem, CDS type, reported user-centered design, implementation strategies, and outcomes.

resultsThere were 28 studies (36 articles) included. Most studies were performed at safety net institutions (14 studies) or Indian Health Service sites (6 studies). CDS tools were implemented in primary care outpatient settings in 24 studies (86%) for screening or treatment. CDS included point-of-care alerts (93%), order facilitators (46%), workflow support (39%), relevant information display (36%), expert systems (11%), and medication dosing support (7%). Successful outcomes were reported in 19 of 26 studies that reported outcomes (73%). User-centered design was reported during CDS planning (39%), development (32%), and implementation phase (25%). Most frequent implementation strategies were education (89%) and consensus facilitation (50%).

conclusionsCDS tools may improve health equity and outcomes for patients who face disparities. The present review underscores the need for high-quality analyses of CDS-associated health outcomes, reporting of user-centered design and implementation strategies used in low-resource settings, and methods to disseminate CDS created to improve health equity.

Indexed as

Decision Support Systems, ClinicalHealth EquityElectronic Health RecordsExpert SystemsHealthcare DisparitiesHumansUnited States

Identifiers

PMID36463877
PMCPMC9719761
OpenAlexW4311282421

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.