Evidence map›Paper›PMID 35613913›Full record

ReviewApplied clinical informatics2022

Clinical Decision Support Stewardship: Best Practices and Techniques to Monitor and Improve Interruptive Alerts.

Juan D Chaparro, Jonathan M Beus, Adam C Dziorny, Philip A Hagedorn, Sean Hernandez, Swaminathan Kandaswamy, Eric S Kirkendall, Allison B McCoy, Naveen Muthu, Evan W Orenstein

Abstract readReview
In one paragraph

Review in Applied clinical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing 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

46 citing papers in PubMed.

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  15. Human performance evaluation of a pediatric artificial intelligence sepsis model.Journal of the American Medical Informatics Association : JAMIA · 2025
    Article
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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

10 authors.

Juan D ChaparroDivision of Clinical Informatics, Nationwide Children's Hospital, Columbus, Ohio, United States.
Jonathan M BeusDepartment of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, United States.
Adam C DziornyDepartment of Pediatrics, University of Rochester School of Medicine, Rochester, New York, United States.
Philip A HagedornDepartment of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio, United States.
Sean HernandezCenter for Healthcare Innovation, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States.
Swaminathan KandaswamyDepartment of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, United States.
Eric S KirkendallCenter for Healthcare Innovation, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States.
Allison B McCoyDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Naveen MuthuDepartment of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States.
Evan W OrensteinDepartment of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, United States.

Funding

Wake Forest Clinical and Translational Science AwardUL1TR001420 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ARD, JAMY D, FOLEY, KRISTIE L · 2015 to 2023
$32.3M
NCATS NIH HHS UL1 TR001420
6 · The paper itself

Abstract

Interruptive clinical decision support systems, both within and outside of electronic health records, are a resource that should be used sparingly and monitored closely. Excessive use of interruptive alerting can quickly lead to alert fatigue and decreased effectiveness and ignoring of alerts. In this review, we discuss the evidence for effective alert stewardship as well as practices and methods we have found useful to assess interruptive alert burden, reduce excessive firings, optimize alert effectiveness, and establish quality governance at our institutions. We also discuss the importance of a holistic view of the alerting ecosystem beyond the electronic health record.

Indexed as

Decision Support Systems, ClinicalMedical Order Entry SystemsEcosystemElectronic Health Records

Identifiers

PMID35613913
PMCPMC9132737

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.