Evidence map›Paper›PMID 32620948›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2020

The tradeoffs between safety and alert fatigue: Data from a national evaluation of hospital medication-related clinical decision support.

Zoe Co, A Jay Holmgren, David C Classen, Lisa Newmark, Diane L Seger, Melissa Danforth, David W Bates

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

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

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  18. Learning decision thresholds for risk stratification models from aggregate clinician behavior.Journal of the American Medical Informatics Association : JAMIA · 2021
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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

7 authors.

Zoe CoDepartment of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
A Jay HolmgrenHarvard Business School, Harvard University, Boston, Massachusetts, USA.
David C ClassenDivision of Clinical Epidemiology, University of Utah, Salt Lake City, Utah, USA.
Lisa NewmarkClinical and Quality Analysis, Mass General Brigham, Somerville, Massachusetts, USA.
Diane L SegerClinical and Quality Analysis, Mass General Brigham, Somerville, Massachusetts, USA.
Melissa DanforthLeapfrog Group, Washington DC, USA.
David W BatesDepartment of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.

Funding

Ensuring Safe Performance of Electronic Health RecordsR01HS023696 · AHRQ · BRIGHAM AND WOMEN'S HOSPITAL · PI BATES, DAVID W., MD,MSC · 2014 to 2014
$1.2M
AHRQ HHS R01 HS023696
6 · The paper itself

Abstract

objectiveThe study sought to evaluate the overall performance of hospitals that used the Computerized Physician Order Entry Evaluation Tool in both 2017 and 2018, along with their performance against fatal orders and nuisance orders. MATERIALS AND

methodsWe evaluated 1599 hospitals that took the test in both 2017 and 2018 by using their overall percentage scores on the test, along with the percentage of fatal orders appropriately alerted on, and the percentage of nuisance orders incorrectly alerted on.

resultsHospitals showed overall improvement; the mean score in 2017 was 58.1%, and this increased to 66.2% in 2018. Fatal order performance improved slightly from 78.8% to 83.0% (P < .001), though there was almost no change in nuisance order performance (89.0% to 89.7%; P = .43). Hospitals alerting on one or more nuisance orders had a 3-percentage-point increase in their overall score. DISCUSSION: Despite the improvement of overall scores in 2017 and 2018, there was little improvement in fatal order performance, suggesting that hospitals are not targeting the deadliest orders first. Nuisance order performance showed almost no improvement, and some hospitals may be achieving higher scores by overalerting, suggesting that the thresholds for which alerts are fired from are too low.

conclusionsAlthough hospitals improved overall from 2017 to 2018, there is still important room for improvement for both fatal and nuisance orders. Hospitals that incorrectly alerted on one or more nuisance orders had slightly higher overall performance, suggesting that some hospitals may be achieving higher scores at the cost of overalerting, which has the potential to cause clinician burnout and even worsen safety.

Indexed as

Alert Fatigue, Health PersonnelDecision Support Systems, ClinicalHospitalsMedical Order Entry SystemsElectronic Health RecordsHealth Care SurveysHumansPatient SafetyQuality of Health CareUnited Statesburnoutcomputerized physician order entryelectronic health recordpatient safetyquality of care

Identifiers

PMID32620948
PMCPMC7647300

What OpenQuestion holds

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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.