Hugh Tilson1, Lisa E Hines2, Gerald McEvoy3, David M Weinstein4, Philip D Hansten5, Karl Matuszewski6, Marianne le Comte7, Stefanie Higby-Baker8, Joseph T Hanlon9, Lynn Pezzullo2, Kathleen Vieson10, Amy L Helwig11, Shiew-Mei Huang12, Anthony Perre13, David W Bates14, John Poikonen15, Michael A Wittie16, Amy J Grizzle17, Mary Brown18, Daniel C Malone19. 1. Public Health Leadership and Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC. 2. Performance Measurement, Pharmacy Quality Alliance, Springfield, VA. 3. Drug Information, American Society of Health-System Pharmacists, Bethesda, MD. 4. Metabolism, Interactions, and Genomics Group, Clinical Content, Lexi-Comp, Wolters-Kluwer Health, Cleveland, OH. 5. Department of Pharmacy, University of Washington School of Pharmacy, Seattle, WA. 6. Clinical and Editorial Knowledge Base Services, First Databank, San Francisco, CA. 7. Drug Information Centre, Royal Dutch Association for the Advancement of Pharmacy, The Hague, Netherlands. 8. Cerner Multum, Denver, CO. 9. Division of Geriatrics and Department of Pharmacy and Therapeutics, University of Pittsburgh, Pittsburgh, PA. 10. Diagnosis, Treatment and Care Decisions, Elsevier Clinical Solutions, Tampa, FL. 11. Center for Quality Improvement and Patient Safety, Agency for Healthcare Research and Quality, Department of Health and Human Services, Washington, DC. 12. Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD. 13. New Patient Intake, Eastern Regional Medical Center, Cancer Treatment Centers of America, Philadelphia, PA. 14. Harvard Medical School, Boston, MA. 15. University of Massachusetts, Lowell, MA. 16. Office of the National Coordinator for Health Information Technology, Department of Health and Human Services, Washington, DC. 17. Center for Health Outcomes and PharmacoEconomic Research, University of Arizona College of Pharmacy, Tucson, AZ. 18. Department of Pharmacy Practice and Science, University of Arizona College of Pharmacy, Tucson, AZ. 19. Department of Pharmacy Practice and Science, University of Arizona College of Pharmacy, Tucson, AZ. malone@pharmacy.arizona.edu.
Abstract
PURPOSE: Recommendations for including drug-drug interactions (DDIs) in clinical decision support (CDS) are presented. SUMMARY: A conference series was conducted to improve CDS for DDIs. A work group consisting of 20 experts in pharmacology, drug information, and CDS from academia, government agencies, health information vendors, and healthcare organizations was convened to address (1) the process to use for developing and maintaining a standard set of DDIs, (2) the information that should be included in a knowledge base of standard DDIs, (3) whether a list of contraindicated drug pairs can or should be established, and (4) how to more intelligently filter DDI alerts. We recommend a transparent, systematic, and evidence-driven process with graded recommendations by a consensus panel of experts and oversight by a national organization. We outline key DDI information needed to help guide clinician decision-making. We recommend judicious classification of DDIs as contraindicated and more research to identify methods to safely reduce repetitive and less-relevant alerts. CONCLUSION: An expert panel with a centralized organizer or convener should be established to develop and maintain a standard set of DDIs for CDS in the United States. The process should be evidence driven, transparent, and systematic, with feedback from multiple stakeholders for continuous improvement. The scope of the expert panel's work should be carefully managed to ensure that the process is sustainable. Support for research to improve DDI alerting in the future is also needed. Adoption of these steps may lead to consistent and clinically relevant content for interruptive DDIs, thus reducing alert fatigue and improving patient safety.
PURPOSE: Recommendations for including drug-drug interactions (DDIs) in clinical decision support (CDS) are presented. SUMMARY: A conference series was conducted to improve CDS for DDIs. A work group consisting of 20 experts in pharmacology, drug information, and CDS from academia, government agencies, health information vendors, and healthcare organizations was convened to address (1) the process to use for developing and maintaining a standard set of DDIs, (2) the information that should be included in a knowledge base of standard DDIs, (3) whether a list of contraindicated drug pairs can or should be established, and (4) how to more intelligently filter DDI alerts. We recommend a transparent, systematic, and evidence-driven process with graded recommendations by a consensus panel of experts and oversight by a national organization. We outline key DDI information needed to help guide clinician decision-making. We recommend judicious classification of DDIs as contraindicated and more research to identify methods to safely reduce repetitive and less-relevant alerts. CONCLUSION: An expert panel with a centralized organizer or convener should be established to develop and maintain a standard set of DDIs for CDS in the United States. The process should be evidence driven, transparent, and systematic, with feedback from multiple stakeholders for continuous improvement. The scope of the expert panel's work should be carefully managed to ensure that the process is sustainable. Support for research to improve DDI alerting in the future is also needed. Adoption of these steps may lead to consistent and clinically relevant content for interruptive DDIs, thus reducing alert fatigue and improving patient safety.
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