Evidence map›Paper›PMID 40834872›Full record

ArticleApplied clinical informatics2025

A Measurement Science Framework to Optimize CDS for Opioid Use Disorder Treatment in the ED.

Mark S Iscoe, Carolina Diniz Hooper, Deborah R Levy, John Lutz, Hyung Paek, Christian Rose, Thomas Kannampallil, Daniella Meeker, James D Dziura, Edward R Melnick

Abstract read
In one paragraph

Article in Applied clinical informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Mark S IscoeDepartment of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, United States.
Carolina Diniz HooperDepartment of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, United States.
Deborah R LevyDepartment of Biomedical Informatics and Data Sciences, Yale University School of Medicine, New Haven, Connecticut, United States.
John LutzYale University School of Medicine, New Haven, Connecticut, United States.
Hyung PaekDepartment of Biostatistics (Health Informatics), Yale School of Public Health, New Haven, Connecticut, United States.
Christian RoseDepartment of Emergency Medicine, Stanford University School of Medicine, Stanford, California, United States.
Thomas KannampallilInstitute for Informatics, Data Science, and Biostatistics Washington University School of Medicine, St. Louis, Missouri, United States.
Daniella MeekerDepartment of Biomedical Informatics and Data Sciences, Yale University School of Medicine, New Haven, Connecticut, United States.
James D DziuraDepartment of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, United States.
Edward R MelnickDepartment of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, United States.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
ADAPT: Adaptive Decision support for Addiction TreatmentR33DA059884 · NIDA · YALE UNIVERSITY · PI Edward Robert Melnick · 2023 to 2026
$4.8M
NCATS NIH HHS UL1 TR001863NIDA NIH HHS R33 DA059884NIDA NIH HHS R33DA059884
6 · The paper itself

Abstract

In the emergency department-initiated buprenorphine for opioid use disorder (EMBED) trial, a clinical decision support (CDS) tool had no effect on rates of buprenorphine initiation in emergency department (ED) patients with opioid use disorder. The Agency for Healthcare Research and Quality (AHRQ) recently released a CDS Performance Measure Inventory to guide data-driven CDS development and evaluation. Through partner co-design, we tailored AHRQ inventory measures to evaluate EMBED CDS performance and drive improvements.Relevant AHRQ inventory measures were selected and adapted using a partner co-design approach grounded in consensus methodology, with three iterative, multidisciplinary partner working group sessions involving stakeholders from various roles and institutions; meetings were followed by postmeeting surveys. The co-design process was divided into conceptualization, specification, and evaluation phases building on the Centers for Medicare and Medicaid Services' measure life cycle framework. Final measures were evaluated in three EDs in a single health system from January 1, 2023, to December 31, 2024.The partner working group included 25 members. During conceptualization, 13 initial candidate metrics were narrowed to 6 priority categories. These were further specified and validated as the following measures, presented with preliminary values based on the use of the current (i.e., preoptimization) EMBED CDS: eligible encounters with CDS engagement, 5.0% (95% confidence interval: 4.3-5.8%); teamwork on ED initiation of buprenorphine, 39.9% (32.5-47.3%); proportion of eligible users who used EMBED, 58.3% (50.9-65.8%); time spent on EMBED, 29.0 seconds (20.4-37.7 seconds); proportion of buprenorphine orders placed through EMBED, 6.5% (3.4-9.6%); and task completion, 13.8% (8.9-18.7%) for buprenorphine order/prescription.A measurement science framework informed by partner co-design was a feasible approach to develop measures to guide CDS improvement. Subsequent research could adapt this approach to evaluate other CDS applications.

Indexed as

Decision Support Systems, ClinicalEmergency Service, HospitalOpioid-Related DisordersBuprenorphineHumansBuprenorphine

Identifiers

PMID40834872
PMCPMC12431813

What Socratic holds

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LicenceCC BY
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Registered trials

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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.