Development of a web-based observational tool for detecting intravenous medication errors with smart infusion pumps.
Computerized smart infusion pumps have been widely implemented to decrease the rate of intravenous (IV) medication errors in hospitals. However, these devices have not always achieved their potential, and important IV errors still persist. Findings from a previous study [1] that assessed the frequency of IV medication errors and the impact of smart infusion pumps identified major issues related to use of smart infusion pumps in a single facility, but generalizability of these results is uncertain. Additionally, lack of standardized methodology for measuring these errors remains an issue. In this study, we developed an observational tool to capture IV medication errors through iterative participatory design with interdisciplinary experts and then tested the tool by using incident cases regarding smart pump errors. We found that the tool could capture all smart infusion pump errors and is ready for testing for use as standard data collection tool in different hospital settings.
General Internal Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Kumiko
K
Ohashi
Patricia
P
Dykes
Kathleen
K
McIntosh
Elizabeth
E
Buckley
Matt
M
Wien
Kevin
K
Kreitzman
Michael
M
Dumais
David W
DW
Bates
D061605:Administration, Intravenous / Q000706:statistics & numerical data; D016907:Adverse Drug Reaction Reporting Systems / Q000458:organization & administration*; D004360:Drug Therapy, Computer-Assisted / Q000295:instrumentation / Q000706:statistics & numerical data; D019544:Equipment Failure Analysis / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D007260:Infusion Pumps / Q000145:classification / Q000706:statistics & numerical data*; D020407:Internet; D008508:Medication Errors / Q000145:classification / Q000517:prevention & control* / Q000706:statistics & numerical data*; D012984:Software; D014481:United States