Evaluation of Cognitive Encoding Across Different Medication Alert Designs. (September 2015)

• Record Type: Journal Article
• Authors: Russ, Alissa L.; Melton, Brittany L.; Daggy, Joanne K.; Saleem, Jason J.
• Is Part Of: Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Volume 59:Part 1(2015)
• Page Start: 580
• Page End: 580
• Publication Date: 2015-09
• Subjects: Human engineering -- Congresses; 620.8205
• DOI: 10.1177/1541931215591127
• Languages: English
• ISSNs: 1541-9312

Abstract

As part of the Meaningful Use criteria, electronic health record systems are required to include medication alerts to warn prescribers about medication allergies and drug-drug interactions before prescriptions are dispensed to patients. There is a paucity of research on medication alert design. Additionally, studies have not evaluated how well alert designs support prescribers' cognitive encoding, even though this is a key step in human information processing for warnings. The objective of this study was to develop a methodological protocol for assessing prescribers' encoding of medication alerts and evaluate prescribers' cognitive encoding in response to two different alert designs. We hypothesized that a redesigned alert display that incorporates human factors principles would significantly increase the amount of information that is accurately encoded. A counterbalanced, crossover study was conducted with 20 prescribers in a human-computer interaction laboratory. We measured prescribers' free recall as well as their ability to identify that three warning messages were displayed. The proportion of total data elements that prescribers were able to accurately recall was significantly greater for the redesigned versus original alerts (median difference in Original-Redesign = -.09, IQR = .15, Wilcoxon signed-rank test p = .006). Additionally, with the redesigned alerts, more prescribers accurately reported that three warnings were displayed (Exact McNemar's test p = .002). Study methods may be useful for evaluating cognitive encoding in the healthcare domain and results may inform future medication alert designs.