Evidence map›Paper›PMID 24166725›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA

Overrides of medication-related clinical decision support alerts in outpatients.

Karen C Nanji, Sarah P Slight, Diane L Seger, Insook Cho, Julie M Fiskio, Lisa M Redden, Lynn A Volk, David W Bates

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 117 papers, 10 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
117citing papers in PubMed, 10 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

117 citing papers in PubMed, 10 syntheses or guidelines pooled it.

  1. Pooled it
  2. Alert fatigue measurement in clinical decision support: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2026
    Pooled it
  3. A systematic review of the impact of health information technology on nurses' time.Journal of the American Medical Informatics Association : JAMIA · 2020
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  13. The effect of medication cost transparency alerts on prescriber behavior.Journal of the American Medical Informatics Association : JAMIA · 2019
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57 more citing papers are in PubMed but not listed here.

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.

Karen C NanjiDepartment of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.
Sarah P Slight
Diane L Seger
Insook Cho
Julie M Fiskio
Lisa M Redden
Lynn A Volk
David W Bates

Funding

Health Information Technology Center for Education and Research on Therapeutics *U19HS021094 · AHRQ · BRIGHAM AND WOMEN'S HOSPITAL · PI BATES, DAVID W., MD,MSC · 2011 to 2015
$4.1M
AHRQ HHS 1U19HS021094-01AHRQ HHS U19 HS021094
6 · The paper itself

Abstract

backgroundElectronic prescribing is increasingly used, in part because of government incentives for its use. Many of its benefits come from clinical decision support (CDS), but often too many alerts are displayed, resulting in alert fatigue.

objectiveTo characterize the override rates for medication-related CDS alerts in the outpatient setting, the reasons cited for overrides at the time of prescribing, and the appropriateness of overrides.

methodsWe measured CDS alert override rates and the coded reasons for overrides cited by providers at the time of prescribing. Our primary outcome was the rate of CDS alert overrides; our secondary outcomes were the rate of overrides by alert type, reasons cited for overrides at the time of prescribing, and override appropriateness for a subset of 600 alert overrides. Through detailed chart reviews of alert override cases, and selective literature review, we developed appropriateness criteria for each alert type, which were modified iteratively as necessary until consensus was reached on all criteria.

resultsWe reviewed 157,483 CDS alerts (7.9% alert rate) on 2,004,069 medication orders during the study period. 82,889 (52.6%) of alerts were overridden. The most common alerts were duplicate drug (33.1%), patient allergy (16.8%), and drug-drug interactions (15.8%). The most likely alerts to be overridden were formulary substitutions (85.0%), age-based recommendations (79.0%), renal recommendations (78.0%), and patient allergies (77.4%). An average of 53% of overrides were classified as appropriate, and rates of appropriateness varied by alert type (p<0.0001) from 12% for renal recommendations to 92% for patient allergies. DISCUSSION: About half of CDS alerts were overridden by providers and about half of the overrides were classified as appropriate, but the likelihood of overriding an alert varied widely by alert type. Refinement of these alerts has the potential to improve the relevance of alerts and reduce alert fatigue.

Indexed as

Decision Support Systems, ClinicalDrug Therapy, Computer-AssistedElectronic PrescribingMedical Order Entry SystemsAmbulatory CareDrug InteractionsElectronic Health RecordsHumansPhysiciansReminder SystemsAlert FatigueEfficiencyElectronic Health RecordsElectronic PrescribingMeaningful UseSafety

Identifiers

PMID24166725
PMCPMC3994856

What OpenQuestion holds

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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.