Evidence map›Paper›PMID 33146626›Full record

ArticleJMIR medical informatics2020

Alert Override Patterns With a Medication Clinical Decision Support System in an Academic Emergency Department: Retrospective Descriptive Study.

Junsang Yoo, Jeonghoon Lee, Poong-Lyul Rhee, Dong Kyung Chang, Mira Kang, Jong Soo Choi, David W Bates, Won Chul Cha

Abstract read
In one paragraph

Article in JMIR medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  9. Mitigating bias in AI at the point of care.Science (New York, N.Y.) · 2023
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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.

Junsang YooInstitution of Healthcare Resource, School of Nursing, Sahmyook University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0003-2331-7644
Jeonghoon LeeSamsung Advanced Institute for Health Sciences & Technology (SAIHST), Department of Digital Health, Sungkyunkwan University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-8619-6811
Poong-Lyul RheeDepartment of Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0003-0495-5296
Dong Kyung ChangSamsung Advanced Institute for Health Sciences & Technology (SAIHST), Department of Digital Health, Sungkyunkwan University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0001-8925-4629
Mira KangSamsung Advanced Institute for Health Sciences & Technology (SAIHST), Department of Digital Health, Sungkyunkwan University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-7842-0035
Jong Soo ChoiHealth Information and Strategy Center, Samsung Medical Center, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0003-3108-406X
David W BatesDivision of General Internal Meidicine and Primary Care, Brigham and Women's Hospital, Boston, MA, United States.ORCID https://orcid.org/0000-0001-6268-1540
Won Chul ChaSamsung Advanced Institute for Health Sciences & Technology (SAIHST), Department of Digital Health, Sungkyunkwan University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-2778-2992

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPhysicians' alert overriding behavior is considered to be the most important factor leading to failure of computerized provider order entry (CPOE) combined with a clinical decision support system (CDSS) in achieving its potential adverse drug events prevention effect. Previous studies on this subject have focused on specific diseases or alert types for well-defined targets and particular settings. The emergency department is an optimal environment to examine physicians' alert overriding behaviors from a broad perspective because patients have a wider range of severity, and many receive interdisciplinary care in this environment. However, less than one-tenth of related studies have targeted this physician behavior in an emergency department setting.

objectiveThe aim of this study was to describe alert override patterns with a commercial medication CDSS in an academic emergency department.

methodsThis study was conducted at a tertiary urban academic hospital in the emergency department with an annual census of 80,000 visits. We analyzed data on the patients who visited the emergency department for 18 months and the medical staff who treated them, including the prescription and CPOE alert log. We also performed descriptive analysis and logistic regression for assessing the risk factors for alert overrides.

resultsDuring the study period, 611 physicians cared for 71,546 patients with 101,186 visits. The emergency department physicians encountered 13.75 alerts during every 100 orders entered. Of the total 102,887 alerts, almost two-thirds (65,616, 63.77%) were overridden. Univariate and multivariate logistic regression analyses identified 21 statistically significant risk factors for emergency department physicians' alert override behavior.

conclusionsIn this retrospective study, we described the alert override patterns with a medication CDSS in an academic emergency department. We found relatively low overrides and assessed their contributing factors, including physicians' designation and specialty, patients' severity and chief complaints, and alert and medication type.

Indexed as

alertalert fatigueclinicalclinical decision support systemdecision support systemsemergency departmenthealth personnelmedical order entry systemsmedication

Identifiers

PMID33146626
PMCPMC7673981

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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 OpenQuestion graph.