Evidence map›Paper›PMID 37673096›Full record

ArticleApplied clinical informatics2023

Behavioral Health Decision Support Systems and User Interface Design in the Emergency Department.

Nicholas W Jones, Sophia L Song, Nicole Thomasian, Elizabeth A Samuels, Megan L Ranney

Open access · bronzeAbstract read
In one paragraph

Article in Applied clinical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 20% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 2 institutions in 1 country.

Nicholas W JonesDepartment of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island, United States.
Sophia L SongWarren Alpert Medical School of Brown University, Providence, Rhode Island, United States.
Nicole ThomasianDepartment of Anesthesiology, New York Presbyterian-Weill Cornell Medical Center, New York, New York, United States.
Elizabeth A SamuelsDepartment of Emergency Medicine, Warren Alpert Medical School of Brown University, Providence, Rhode Island, United States.
Megan L RanneyDepartment of Emergency Medicine, Warren Alpert Medical School of Brown University, Providence, Rhode Island, United States.
Brown University · USCornell University · US

Funding

Tracking and Evaluation CoreU54GM115677 · NIGMS · BROWN UNIVERSITY · PI CHOUDHARY, GAURAV · 2016 to 2025
$45.0M
NIGMS NIH HHS U54 GM115677
6 · The paper itself

Abstract

objectiveThe objective of this qualitative study is to gauge physician sentiment about an emergency department (ED) clinical decision support (CDS) system implemented in multiple adult EDs within a university hospital system. This CDS system focuses on predicting patients' likelihood of ED recidivism and/or adverse opioid-related events.

methodsThe study was conducted among adult emergency physicians working in three EDs of a single academic health system in Rhode Island. Qualitative, semistructured interviews were conducted with ED physicians. Interviews assessed physicians' prior experience with predictive analytics, thoughts on the alert's placement, design, and content, the alert's overall impact, and potential areas for improvement. Responses were aggregated and common themes identified.

resultsTwenty-three interviews were conducted (11 preimplementation and 12 postimplementation). Themes were identified regarding each physician familiarity with predictive analytics, alert rollout, alert appearance and content, and on alert sentiments. Most physicians viewed these alerts as a neutral or positive EHR addition, with responses ranging from neutral to positive. The alert placement was noted to be largely intuitive and nonintrusive. The design of the alert was generally viewed positively. The alert's content was believed to be accurate, although the decision to respond to the alert's call-to-action was physician dependent. Those who tended to ignore the alert did so for a few reasons, including already knowing the information the alert contains, the alert offering information that is not relevant to this particular patient, and the alert not containing enough information to be useful.

conclusionUltimately, this alert appears to have a marginally positive effect on ED physician workflow. At its most beneficial, the alert reminded physicians to deeply consider the care provided to high-risk populations and to potentially adjust their care and referrals. At its least beneficial, the alert did not affect physician decision-making but was not intrusive to the point of negatively impacting workflow.

Indexed as

Decision Support Systems, ClinicalPhysiciansAdultEmergency Service, HospitalHospitals, UniversityHumansQualitative Research

Identifiers

PMID37673096
PMCPMC10482498
OpenAlexW4386472245

What Socratic 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 Socratic graph.