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

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  • Additional Information
    • Source:
      Publisher: Springer Country of Publication: United States NLM ID: 8605834 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1525-1497 (Electronic) Linking ISSN: 08848734 NLM ISO Abbreviation: J Gen Intern Med Subsets: MEDLINE
    • Publication Information:
      Publication: Secaucus, NJ : Springer
      Original Publication: [Philadelphia, PA] : Hanley & Belfus, [c1986-
    • Subject Terms:
      Drug Interactions*/physiology; Electronic Health Records/*trends ; Medical Order Entry Systems/*trends ; Medication Errors/*prevention & control ; Medication Errors/*trends; Drug-Related Side Effects and Adverse Reactions/prevention & control ; Electronic Health Records/standards ; Humans ; Medical Order Entry Systems/standards ; Reminder Systems/standards ; Reminder Systems/trends ; Treatment Outcome
    • Abstract:
      Background: 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.
      Objective: To study the effect of conversion to a commercial EHR on DDI alert and acceptance rates.
      Design: Two before-and-after studies.
      Participants: 3277 clinicians who received a DDI alert in the outpatient setting.
      Intervention: 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).
      Conclusions: 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.
    • Comments:
      Comment in: J Gen Intern Med. 2018 Nov;33(11):1954. (PMID: 30128788)
    • References:
      JAMA. 2003 Apr 2;289(13):1652-8. (PMID: 12672733)
      J Am Med Inform Assoc. 2006 Jan-Feb;13(1):5-11. (PMID: 16221941)
      BMJ. 2015 Mar 11;350:h949. (PMID: 25762567)
      Ann Intern Med. 2013 Jun 18;158(12):869-76. (PMID: 23778904)
      J Am Med Inform Assoc. 2009 Jan-Feb;16(1):40-6. (PMID: 18952941)
      Br J Clin Pharmacol. 2014 Jun;77(6):1086-7. (PMID: 23919252)
      Proc Annu Symp Comput Appl Med Care. 1994;:836-40. (PMID: 7950042)
      J Am Med Inform Assoc. 2013 May 1;20(3):489-93. (PMID: 23011124)
      J Am Med Inform Assoc. 2016 May;23(3):601-8. (PMID: 26578227)
      N Engl J Med. 1971 Jun 17;284(24):1361-8. (PMID: 4930604)
      Ann Pharmacother. 2007 Jul;41(7):1292-5. (PMID: 17565042)
      Fed Regist. 2015 Oct 16;80(200):62761-955. (PMID: 26477064)
      Clin Pharmacol Ther. 2004 Dec;76(6):598-606. (PMID: 15592331)
      J Am Med Inform Assoc. 2016 Nov;23(6):1068-1076. (PMID: 27026616)
      J Am Med Inform Assoc. 2006 Mar-Apr;13(2):138-47. (PMID: 16357358)
      BMC Med Inform Decis Mak. 2013 Jun 13;13(1):65. (PMID: 23763856)
      PLoS One. 2013 Dec 26;8(12):e85071. (PMID: 24386447)
      Conf Proc IEEE Eng Med Biol Soc. 2014;2014:5703-6. (PMID: 25571290)
      Am J Med. 2014 Jul;127(7):657-663.e2. (PMID: 24657899)
      Hypertens Res. 2005 Mar;28(3):223-7. (PMID: 16097365)
      J Biomed Semantics. 2015 May 11;6:19. (PMID: 25964850)
      J Gen Intern Med. 1993 Jun;8(6):289-94. (PMID: 8320571)
      Pharmacoepidemiol Drug Saf. 2014 May;23(5):489-97. (PMID: 24616171)
      Arch Intern Med. 2002 Nov 25;162(21):2414-20. (PMID: 12437399)
      Arch Intern Med. 1995 Oct 9;155(18):1949-56. (PMID: 7575048)
      JAMA. 1997 Jan 22-29;277(4):301-6. (PMID: 9002492)
      J Am Med Inform Assoc. 2006 May-Jun;13(3):261-6. (PMID: 16501178)
      Antimicrob Agents Chemother. 2015 Sep;59(9):5548-54. (PMID: 26124167)
      J Am Med Inform Assoc. 2012 Sep-Oct;19(5):735-43. (PMID: 22539083)
      J Am Med Inform Assoc. 2008 Sep-Oct;15(5):585-600. (PMID: 18579832)
      JAMA. 1998 Oct 21;280(15):1311-6. (PMID: 9794308)
      JAMA. 1995 Jul 5;274(1):29-34. (PMID: 7791255)
    • Grant Information:
      K23 DK097187 United States DK NIDDK NIH HHS; R01 LM011966 United States LM NLM NIH HHS; U18 HS016970 United States HS AHRQ HHS
    • Contributed Indexing:
      Keywords: adverse drug events; clinical decision support; drug-drug interactions; electronic health records; safety
    • Publication Date:
      Date Created: 20180517 Date Completed: 20191122 Latest Revision: 20191122
    • Publication Date:
      20221213
    • Accession Number:
      PMC6206354
    • Accession Number:
      10.1007/s11606-018-4415-9
    • Accession Number:
      29766382