Evidence map›Paper›PMID 29766382›Full record

ArticleJournal of general internal medicine2018

Reduced Effectiveness of Interruptive Drug-Drug Interaction Alerts after Conversion to a Commercial Electronic Health Record.

Adam Wright, Skye Aaron, Diane L Seger, Lipika Samal, Gordon D Schiff, David W Bates

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of general internal medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  9. The Future Hospital in Global Health Systems: The Future Hospital as an Entity.The International journal of health planning and management · 2025
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  14. Pharmacogenomics · 2023
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Adam WrightDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. awright@bwh.harvard.edu.
Skye AaronDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Diane L SegerDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Lipika SamalDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Gordon D SchiffDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
David W BatesDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Funding

Health Information Technology and Improving Mediciation UseU18HS016970 · AHRQ · BRIGHAM AND WOMEN'S HOSPITAL · PI BATES, DAVID W., MD,MSC · 2007 to 2010
$4.0M
Improving clinical decision support reliability using anomaly detection methodsR01LM011966 · NLM · VANDERBILT UNIVERSITY MEDICAL CENTER · PI WRIGHT, ADAM T · 2014 to 2017
$2.4M
Health Information Technology for Chronic Kidney Disease ManagementK23DK097187 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI SAMAL, LIPIKA · 2013 to 2017
$920k
AHRQ HHS U18 HS016970NIDDK NIH HHS K23 DK097187NLM NIH HHS R01 LM011966
6 · The paper itself

Abstract

backgroundDrug-drug interaction (DDI) alerts in electronic health records (EHRs) can help prevent adverse drug events, but such alerts are frequently overridden, raising concerns about their clinical usefulness and contribution to alert fatigue.

objectiveTo study the effect of conversion to a commercial EHR on DDI alert and acceptance rates.

designTwo before-and-after studies.

participants3277 clinicians who received a DDI alert in the outpatient setting.

interventionIntroduction of a new, commercial EHR and subsequent adjustment of DDI alerting criteria. MAIN MEASURES: Alert burden and proportion of alerts accepted. KEY

resultsOverall interruptive DDI alert burden increased by a factor of 6 from the legacy EHR to the commercial EHR. The acceptance rate for the most severe alerts fell from 100 to 8.4%, and from 29.3 to 7.5% for medium severity alerts (P < 0.001). After disabling the least severe alerts, total DDI alert burden fell by 50.5%, and acceptance of Tier 1 alerts rose from 9.1 to 12.7% (P < 0.01).

conclusionsChanging from a highly tailored DDI alerting system to a more general one as part of an EHR conversion decreased acceptance of DDI alerts and increased alert burden on users. The decrease in acceptance rates cannot be fully explained by differences in the clinical knowledge base, nor can it be fully explained by alert fatigue associated with increased alert burden. Instead, workflow factors probably predominate, including timing of alerts in the prescribing process, lack of differentiation of more and less severe alerts, and features of how users interact with alerts.

Indexed as

Drug InteractionsDrug-Related Side Effects and Adverse ReactionsElectronic Health RecordsHumansMedical Order Entry SystemsMedication ErrorsReminder SystemsTreatment Outcomeadverse drug eventsclinical decision supportdrug-drug interactionselectronic health recordssafety

Identifiers

PMID29766382
PMCPMC6206354

What OpenQuestion holds

Textmetadata
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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.