BACKGROUND: Adverse drug events (ADEs) represent an important problem for hospital and primary care. Software that detects potential adverse drug interactions has been widely implemented in an effort to reduce the rate of ADEs. However, the impact of drug interaction detection software (DIS) on patient safety outcomes remains unknown. OBJECTIVES: To systematically review the literature on DIS in preventing adverse drug events and determine the effectiveness and cost-effectiveness of DIS. METHODS: A literature search of MEDLINE, EMBASE, CINAHL, IPA and Healthstar, using terms "Computer, Software or Decision Support" combined with "Drug Interactions, Drug Errors or Drug Monitoring" sought English language, post-1990 prospective studies that examined drug interaction (drug-drug) software as an intervention and adverse drug interactions as an outcome. Relevant studies were analyzed using a Bayesian meta-analysis approach. RESULTS: Of 5848 citations, only four studies met our inclusion criteria. Most of the excluded studies were not prospective or measured only prescriber attitudes, implementation success or changes in workflow. No study examined the impact of drug interaction software exclusively, rather as a component of decision support software. A Bayesian meta-analysis of these studies showed no significant difference in event rate between intervention and control groups (relative risk 0.66, 95% CI 0.33 to 1.18). The posterior median I-squared was 52%. CONCLUSION: No good quality studies address the specific benefits and harms or cost-effectiveness of drug interaction software on medication safety or clinical outcomes. The evidence at present does not support a benefit for these systems or support any policy to widely disseminate their use.
BACKGROUND: Adverse drug events (ADEs) represent an important problem for hospital and primary care. Software that detects potential adverse drug interactions has been widely implemented in an effort to reduce the rate of ADEs. However, the impact of drug interaction detection software (DIS) on patient safety outcomes remains unknown. OBJECTIVES: To systematically review the literature on DIS in preventing adverse drug events and determine the effectiveness and cost-effectiveness of DIS. METHODS: A literature search of MEDLINE, EMBASE, CINAHL, IPA and Healthstar, using terms "Computer, Software or Decision Support" combined with "Drug Interactions, Drug Errors or Drug Monitoring" sought English language, post-1990 prospective studies that examined drug interaction (drug-drug) software as an intervention and adverse drug interactions as an outcome. Relevant studies were analyzed using a Bayesian meta-analysis approach. RESULTS: Of 5848 citations, only four studies met our inclusion criteria. Most of the excluded studies were not prospective or measured only prescriber attitudes, implementation success or changes in workflow. No study examined the impact of drug interaction software exclusively, rather as a component of decision support software. A Bayesian meta-analysis of these studies showed no significant difference in event rate between intervention and control groups (relative risk 0.66, 95% CI 0.33 to 1.18). The posterior median I-squared was 52%. CONCLUSION: No good quality studies address the specific benefits and harms or cost-effectiveness of drug interaction software on medication safety or clinical outcomes. The evidence at present does not support a benefit for these systems or support any policy to widely disseminate their use.
Authors: Ashly D Black; Josip Car; Claudia Pagliari; Chantelle Anandan; Kathrin Cresswell; Tomislav Bokun; Brian McKinstry; Rob Procter; Azeem Majeed; Aziz Sheikh Journal: PLoS Med Date: 2011-01-18 Impact factor: 11.069
Authors: Dionne S Kringos; Rosa Sunol; Cordula Wagner; Russell Mannion; Philippe Michel; Niek S Klazinga; Oliver Groene Journal: BMC Health Serv Res Date: 2015-07-22 Impact factor: 2.655
Authors: Eva Blozik; Hendrik van den Bussche; Felix Gurtner; Ingmar Schäfer; Martin Scherer Journal: BMC Health Serv Res Date: 2013-09-16 Impact factor: 2.655