Ability of pharmacy clinical decision-support software to alert users about clinically important drug-drug interactions.
OBJECTIVE
Pharmacy clinical decision-support (CDS) software that contains drug-drug interaction (DDI) information may augment pharmacists' ability to detect clinically significant interactions. However, studies indicate these systems may miss some important interactions. The purpose of this study was to assess the performance of pharmacy CDS programs to detect clinically important DDIs.


METHODS
Researchers made on-site visits to 64 participating Arizona pharmacies between December 2008 and November 2009 to analyze the ability of pharmacy information systems and associated CDS to detect DDIs. Software evaluation was conducted to determine whether DDI alerts arose from prescription orders entered into the pharmacy computer systems for a standardized fictitious patient. The fictitious patient's orders consisted of 18 different medications including 19 drug pairs-13 of which were clinically significant DDIs, and six were non-interacting drug pairs.


METHODS
The sensitivity, specificity, positive predictive value, negative predictive value, and percentage of correct responses were measured for each of the pharmacy CDS systems.


RESULTS
Only 18 (28%) of the 64 pharmacies correctly identified eligible interactions and non-interactions. The median percentage of correct DDI responses was 89% (range 47-100%) for participating pharmacies. The median sensitivity to detect well-established interactions was 0.85 (range 0.23-1.0); median specificity was 1.0 (range 0.83-1.0); median positive predictive value was 1.0 (range 0.88-1.0); and median negative predictive value was 0.75 (range 0.38-1.0).


CONCLUSIONS
These study results indicate that many pharmacy clinical decision-support systems perform less than optimally with respect to identifying well-known, clinically relevant interactions. Comprehensive system improvements regarding the manner in which pharmacy information systems identify potential DDIs are warranted.
Department of Pharmacy Practice and Science, The University of Arizona College of Pharmacy, Tucson, Arizona 85721-0202, USA.
Kim R
KR
Saverno
Lisa E
LE
Hines
Terri L
TL
Warholak
Amy J
AJ
Grizzle
Lauren
L
Babits
Courtney
C
Clark
Ann M
AM
Taylor
Daniel C
DC
Malone
D001130:Arizona; D016303:Clinical Pharmacy Information Systems; D020000:Decision Support Systems, Clinical; D004347:Drug Interactions; D019538:Health Care Surveys; D006801:Humans; D008508:Medication Errors / Q000517:prevention & control*; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity; D012986:Software Validation