OBJECTIVE: To develop a set of high-severity, clinically significant drug-drug interactions (DDIs) for use in electronic health records (EHRs). METHODS: A panel of experts was convened with the goal of identifying critical DDIs that should be used for generating medication-related decision support alerts in all EHRs. Panelists included medication knowledge base vendors, EHR vendors, in-house knowledge base developers from academic medical centers, and both federal and private agencies involved in the regulation of medication use. Candidate DDIs were assessed by the panel based on the consequence of the interaction, severity levels assigned to them across various medication knowledge bases, availability of therapeutic alternatives, monitoring/management options, predisposing factors, and the probability of the interaction based on the strength of evidence available in the literature. RESULTS: Of 31 DDIs considered to be high risk, the panel approved a final list of 15 interactions. Panelists agreed that this list represented drugs that are contraindicated for concurrent use, though it does not necessarily represent a complete list of all such interacting drug pairs. For other drug interactions, severity may depend on additional factors, such as patient conditions or timing of co-administration. DISCUSSION: The panel provided recommendations on the creation, maintenance, and implementation of a central repository of high severity interactions. CONCLUSIONS: A set of highly clinically significant drug-drug interactions was identified, for which warnings should be generated in all EHRs. The panel highlighted the complexity of issues surrounding development and implementation of such a list.
OBJECTIVE: To develop a set of high-severity, clinically significant drug-drug interactions (DDIs) for use in electronic health records (EHRs). METHODS: A panel of experts was convened with the goal of identifying critical DDIs that should be used for generating medication-related decision support alerts in all EHRs. Panelists included medication knowledge base vendors, EHR vendors, in-house knowledge base developers from academic medical centers, and both federal and private agencies involved in the regulation of medication use. Candidate DDIs were assessed by the panel based on the consequence of the interaction, severity levels assigned to them across various medication knowledge bases, availability of therapeutic alternatives, monitoring/management options, predisposing factors, and the probability of the interaction based on the strength of evidence available in the literature. RESULTS: Of 31 DDIs considered to be high risk, the panel approved a final list of 15 interactions. Panelists agreed that this list represented drugs that are contraindicated for concurrent use, though it does not necessarily represent a complete list of all such interacting drug pairs. For other drug interactions, severity may depend on additional factors, such as patient conditions or timing of co-administration. DISCUSSION: The panel provided recommendations on the creation, maintenance, and implementation of a central repository of high severity interactions. CONCLUSIONS: A set of highly clinically significant drug-drug interactions was identified, for which warnings should be generated in all EHRs. The panel highlighted the complexity of issues surrounding development and implementation of such a list.
Authors: Jacob Abarca; Daniel C Malone; Edward P Armstrong; Amy J Grizzle; Philip D Hansten; Robin C Van Bergen; Richard B Lipton Journal: J Am Pharm Assoc (2003) Date: 2004 Mar-Apr
Authors: Nidhi R Shah; Andrew C Seger; Diane L Seger; Julie M Fiskio; Gilad J Kuperman; Barry Blumenfeld; Elaine G Recklet; David W Bates; Tejal K Gandhi Journal: J Am Med Inform Assoc Date: 2005-10-12 Impact factor: 4.497
Authors: Marilyn D Paterno; Saverio M Maviglia; Paul N Gorman; Diane L Seger; Eileen Yoshida; Andrew C Seger; David W Bates; Tejal K Gandhi Journal: J Am Med Inform Assoc Date: 2008-10-24 Impact factor: 4.497
Authors: Daniel C Malone; Jacob Abarca; Philip D Hansten; Amy J Grizzle; Edward P Armstrong; Robin C Van Bergen; Babette S Duncan-Edgar; Steven L Solomon; Richard B Lipton Journal: J Am Pharm Assoc (2003) Date: 2004 Mar-Apr
Authors: Kevin M Terrell; Anthony J Perkins; Paul R Dexter; Siu L Hui; Christopher M Callahan; Douglas K Miller Journal: J Am Geriatr Soc Date: 2009-06-22 Impact factor: 5.562
Authors: Allie D Woods; David P Mulherin; Allen J Flynn; James G Stevenson; Christopher R Zimmerman; Bruce W Chaffee Journal: J Am Med Inform Assoc Date: 2013-11-19 Impact factor: 4.497
Authors: Shobha Phansalkar; Heleen van der Sijs; Alisha D Tucker; Amrita A Desai; Douglas S Bell; Jonathan M Teich; Blackford Middleton; David W Bates Journal: J Am Med Inform Assoc Date: 2012-09-25 Impact factor: 4.497
Authors: Jeff L Bubp; Michelle A Park; Joan Kapusnik-Uner; Thong Dang; Karl Matuszewski; Don Ly; Kevin Chiang; Sek Shia; Brian Hoberman Journal: J Am Med Inform Assoc Date: 2019-10-01 Impact factor: 4.497
Authors: L Gschwind; V Rollason; C Lovis; F Boehlen; P Bonnabry; P Dayer; J A Desmeules Journal: Eur J Clin Pharmacol Date: 2012-08-19 Impact factor: 2.953
Authors: Serkan Ayvaz; John Horn; Oktie Hassanzadeh; Qian Zhu; Johann Stan; Nicholas P Tatonetti; Santiago Vilar; Mathias Brochhausen; Matthias Samwald; Majid Rastegar-Mojarad; Michel Dumontier; Richard D Boyce Journal: J Biomed Inform Date: 2015-04-24 Impact factor: 6.317
Authors: Olesya I Zorina; Patrick Haueis; Waldemar Greil; Renate Grohmann; Gerd A Kullak-Ublick; Stefan Russmann Journal: Drug Saf Date: 2013-04 Impact factor: 5.606
Authors: Katherine N Cahill; Christina B Johns; Jing Cui; Paige Wickner; David W Bates; Tanya M Laidlaw; Patrick E Beeler Journal: J Allergy Clin Immunol Date: 2016-07-25 Impact factor: 10.793