Journal of General Internal Medicine

, Volume 33, Issue 11, pp 1868–1876 | Cite as

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
Original Research



Drug-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.


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


Two before-and-after studies.


3277 clinicians who received a DDI alert in the outpatient setting.


Introduction of a new, commercial EHR and subsequent adjustment of DDI alerting criteria.

Main Measures

Alert burden and proportion of alerts accepted.

Key Results

Overall 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).


Changing 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.


clinical decision support adverse drug events drug-drug interactions electronic health records safety 



None other than the authors as listed.

Funding Information

Research reported in this publication was supported by the National Library of Medicine (NLM) of the National Institutes of Health under Award Number R01LM011966 and the Agency for Healthcare Research and Quality (AHRQ) Center for Education and Research on Therapeutics grant 1U18HS016970. The content is solely the responsibility of the authors and does not necessarily represent the official views of NIH or AHRQ. Neither NIH nor AHRQ were involved in the design or execution of the project or the decision to publish the results.

Compliance with Ethical Standards

IRB Approval

Approval for the study was obtained from the Partners HealthCare Institutional Review Board.

Prior Presentation

Early data from this study was presented as a poster at the 2016 AMIA Annual Symposium.

Conflict of Interest

The authors declare that they do not have a conflict of interest.


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Copyright information

© Society of General Internal Medicine 2018

Authors and Affiliations

  • Adam Wright
    • 1
    • 2
    • 3
  • Skye Aaron
    • 1
  • Diane L. Seger
    • 1
    • 3
  • Lipika Samal
    • 1
    • 2
    • 3
  • Gordon D. Schiff
    • 1
    • 2
    • 3
  • David W. Bates
    • 1
    • 2
    • 3
  1. 1.Division of General Internal Medicine and Primary Care Brigham and Women’s Hospital and Harvard Medical SchoolBostonUSA
  2. 2.Department of Biomedical InformaticsHarvard Medical SchoolBostonUSA
  3. 3.Information Systems DepartmentPartners HealthCareBostonUSA

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