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High-Risk Drug–Drug Interactions Between Clinical Practice Guidelines for Management of Chronic Conditions

Clinicians and clinical decision-support systems often follow pharmacotherapy recommendations for patients based on clinical practice guidelines (CPGs). In multimorbid patients, these recommendations can potentially have clinically significant drug–drug interactions (DDIs). In this study, we describ...

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Detalles Bibliográficos
Autores principales: Tso, Geoffrey J., Tu, Samson W., Musen, Mark A., Goldstein, Mary K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5543385/
https://www.ncbi.nlm.nih.gov/pubmed/28815153
Descripción
Sumario:Clinicians and clinical decision-support systems often follow pharmacotherapy recommendations for patients based on clinical practice guidelines (CPGs). In multimorbid patients, these recommendations can potentially have clinically significant drug–drug interactions (DDIs). In this study, we describe and validate a method for programmatically detecting DDIs among CPG recommendations. The system extracts pharmacotherapy intervention recommendations from narrative CPGs, normalizes the terms, creates a mapping of drugs and drug classes, and then identifies occurrences of DDIs between CPG pairs. We used this system to analyze 75 CPGs written by authoring entities in the United States that discuss outpatient management of common chronic diseases. Using a reference list of high-risk DDIs, we identified 2198 of these DDIs in 638 CPG pairs (46 unique CPGs). Only 9 high-risk DDIs were discussed by both CPGs in a pairing. In 69 of the pairings, neither CPG had a pharmacologic reference or a warning of the possibility of a DDI.