Drug-drug interactions that should be non-interruptive in order to reduce alert fatigue in electronic health records

OBJECTIVE Alert fatigue represents a common problem associated with the use of clinical decision support systems in electronic health records (EHR). This problem is particularly profound with drug-drug interaction (DDI) alerts for which studies have reported override rates of approximately 90%. The objective of this study is to report consensus-based recommendations of an expert panel on DDI that can be safely made non-interruptive to the provider's workflow, in EHR, in an attempt to reduce alert fatigue. METHODS We utilized an expert panel process to rate the interactions. Panelists had expertise in medicine, pharmacy, pharmacology and clinical informatics, and represented both academic institutions and vendors of medication knowledge bases and EHR. In addition, representatives from the US Food and Drug Administration and the American Society of Health-System Pharmacy contributed to the discussions. RESULTS Recommendations and considerations of the panel resulted in the creation of a list of 33 class-based low-priority DDI that do not warrant being interruptive alerts in EHR. In one institution, these accounted for 36% of the interactions displayed. DISCUSSION Development and customization of the content of medication knowledge bases that drive DDI alerting represents a resource-intensive task. Creation of a standardized list of low-priority DDI may help reduce alert fatigue across EHR. CONCLUSIONS Future efforts might include the development of a consortium to maintain this list over time. Such a list could also be used in conjunction with financial incentives tied to its adoption in EHR.

[1]  Marc Berg,et al.  Case Report: Time-dependent Drug-Drug Interaction Alerts in Care Provider Order Entry: Software May Inhibit Medication Error Reductions , 2009, J. Am. Medical Informatics Assoc..

[2]  Diane L. Seger,et al.  Adverse Drug Event Rates in Six Community Hospitals and the Potential Impact of Computerized Physician Order Entry for Prevention , 2009, Journal of General Internal Medicine.

[3]  Paul K. Davis,et al.  Advancing clinical decision support using lessons from outside of healthcare: an interdisciplinary systematic review , 2012, BMC Medical Informatics and Decision Making.

[4]  D W Bates,et al.  Preventable medication errors: identifying and eliminating serious drug interactions. , 2001, Journal of the American Pharmacists Association.

[5]  Robyn Tamblyn,et al.  Reasons for Physician Non-Adherence to Electronic Drug Alerts , 2004, MedInfo.

[6]  Thomas H. Payne,et al.  Review Paper: Medication-related Clinical Decision Support in Computerized Provider Order Entry Systems: A Review , 2007, J. Am. Medical Informatics Assoc..

[7]  Eva K. Lee,et al.  Improving Patient Safety through Medical Alert Management: An Automated Decision Tool to Reduce Alert Fatigue. , 2010, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[8]  T K Hazlet,et al.  ORCA: OpeRational ClassificAtion of drug interactions. , 2001, Journal of the American Pharmaceutical Association.

[9]  David W. Bates,et al.  Can surveillance systems identify and avert adverse drug events? A prospective evaluation of a commercial application. , 2008, Journal of the American Medical Informatics Association : JAMIA.

[10]  David W. Bates,et al.  Review Paper: What Evidence Supports the Use of Computerized Alerts and Prompts to Improve Clinicians' Prescribing Behavior? , 2009, J. Am. Medical Informatics Assoc..

[11]  Marc Berg,et al.  Review Paper: Overriding of Drug Safety Alerts in Computerized Physician Order Entry , 2006, J. Am. Medical Informatics Assoc..

[12]  M. Langdorf,et al.  Physician versus computer knowledge of potential drug interactions in the emergency department. , 2000, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[13]  Roger B. Davis,et al.  Overrides of medication alerts in ambulatory care. , 2009, Archives of internal medicine.

[14]  T K Hazlet,et al.  Performance of community pharmacy drug interaction software. , 2001, Journal of the American Pharmaceutical Association.

[15]  David W. Bates,et al.  Clinical decision support systems could be modified to reduce 'alert fatigue' while still minimizing the risk of litigation. , 2011, Health affairs.

[16]  J. Brouwers,et al.  Clinical Relevance of Drug-Drug Interactions , 2005, Drug safety.

[17]  David W. Bates,et al.  High-priority drug-drug interactions for use in electronic health records , 2012, J. Am. Medical Informatics Assoc..

[18]  Bruce Kaplan,et al.  Evaluation of Drug Interaction Software to Identify Alerts for Transplant Medications , 2005, The Annals of pharmacotherapy.

[19]  Guilherme Del Fiol,et al.  Comparison of two knowledge bases on the detection of drug-drug interactions , 2000, AMIA.

[20]  C Neef,et al.  Strategy for implementation and first results of advanced clinical decision support in hospital pharmacy practice. , 2009, Studies in health technology and informatics.

[21]  Davide Bolchini,et al.  A successful model and visual design for creating context-aware drug-drug interaction alerts. , 2011, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[22]  Roger B. Davis,et al.  Clinicians' assessments of electronic medication safety alerts in ambulatory care. , 2009, Archives of internal medicine.

[23]  Marc Berg,et al.  Research Paper: Turning Off Frequently Overridden Drug Alerts: Limited Opportunities for Doing It Safely , 2008, J. Am. Medical Informatics Assoc..

[24]  Aziz Sheikh,et al.  Prescribing safety features of general practice computer systems: evaluation using simulated test cases , 2004, BMJ : British Medical Journal.