OBJECTIVE: To evaluate drug interaction software programs and determine their accuracy in identifying drug-drug interactions that may occur in intensive care units. Setting The study was developed in Brazil. METHOD: Drug interaction software programs were identified through a bibliographic search in PUBMED and in LILACS (database related to the health sciences published in Latin American and Caribbean countries). The programs' sensitivity, specificity, and positive and negative predictive values were determined to assess their accuracy in detecting drug-drug interactions. The accuracy of the software programs identified was determined using 100 clinically important interactions and 100 clinically unimportant ones. Stockley's Drug Interactions 8th edition was employed as the gold standard in the identification of drug-drug interaction. MAIN OUTCOME: Sensitivity, specificity, positive and negative predictive values. RESULTS: The programs studied were: Drug Interaction Checker (DIC), Drug-Reax (DR), and Lexi-Interact (LI). DR displayed the highest sensitivity (0.88) and DIC showed the lowest (0.69). A close similarity was observed among the programs regarding specificity (0.88-0.92) and positive predictive values (0.88-0.89). The DIC had the lowest negative predictive value (0.75) and DR the highest (0.91). CONCLUSION: The DR and LI programs displayed appropriate sensitivity and specificity for identifying drug-drug interactions of interest in intensive care units. Drug interaction software programs help pharmacists and health care teams in the prevention and recognition of drug-drug interactions and optimize safety and quality of care delivered in intensive care units.
OBJECTIVE: To evaluate drug interaction software programs and determine their accuracy in identifying drug-drug interactions that may occur in intensive care units. Setting The study was developed in Brazil. METHOD: Drug interaction software programs were identified through a bibliographic search in PUBMED and in LILACS (database related to the health sciences published in Latin American and Caribbean countries). The programs' sensitivity, specificity, and positive and negative predictive values were determined to assess their accuracy in detecting drug-drug interactions. The accuracy of the software programs identified was determined using 100 clinically important interactions and 100 clinically unimportant ones. Stockley's Drug Interactions 8th edition was employed as the gold standard in the identification of drug-drug interaction. MAIN OUTCOME: Sensitivity, specificity, positive and negative predictive values. RESULTS: The programs studied were: Drug Interaction Checker (DIC), Drug-Reax (DR), and Lexi-Interact (LI). DR displayed the highest sensitivity (0.88) and DIC showed the lowest (0.69). A close similarity was observed among the programs regarding specificity (0.88-0.92) and positive predictive values (0.88-0.89). The DIC had the lowest negative predictive value (0.75) and DR the highest (0.91). CONCLUSION: The DR and LI programs displayed appropriate sensitivity and specificity for identifying drug-drug interactions of interest in intensive care units. Drug interaction software programs help pharmacists and health care teams in the prevention and recognition of drug-drug interactions and optimize safety and quality of care delivered in intensive care units.
Authors: Isabel Spriet; Wouter Meersseman; Jan de Hoon; Sandrina von Winckelmann; Alexander Wilmer; Ludo Willems Journal: Intensive Care Med Date: 2009-01-09 Impact factor: 17.440
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: Julia Amkreutz; Alexander Koch; Lukas Buendgens; Anja Muehlfeld; Christian Trautwein; Albrecht Eisert Journal: Int J Clin Pharm Date: 2017-08-19
Authors: Kin Wah Fung; Joan Kapusnik-Uner; Jean Cunningham; Stefanie Higby-Baker; Olivier Bodenreider Journal: J Am Med Inform Assoc Date: 2017-07-01 Impact factor: 4.497