Abstract
Healthcare information systems (e.g., Bar Code Medication Administration [BCMA] system) have been adopted to deliver efficient healthcare services recently. However, though it is seemingly simple to use (scanning barcodes before medication), users of the BCMA system (e.g., nurses and pharmacists) often show noncompliance behaviors. Therefore, the goal of this study is to comprehensively understand why such noncompliance behaviors occur with BCMA system. Through comprehensive literature review, 128 instances of causes were identified, which were categorized into five categories: Poor Visual and Audio Interface, Poor Physical Ergonomic Design, Poor Information Integrity, Abnormal Situation for System Use, and User Reluctance and Negligence. The results show that successful use of a BCMA system requires supportive systems and environments, so it is more like an issue of the system rather than that of an individual user or a device. It is believed that the proposed categories could be applicable in investigating noncompliance behaviors in other healthcare information systems as well.
Notes
1 A number in brackets represents the cause identification number; a corresponding quote can be found in Appendix A.
Additional information
Notes on contributors
Byung Cheol Lee
Byung Cheol Lee is a postdoctoral researcher in the School of Industrial Engineering at Purdue University. He received his Ph.D. degree specializing in healthcare engineering and human factors at Purdue University in 2013. His main research interests include healthcare engineering based on human factors principles and human cognitive modeling.
Sukwon Lee
Sukwon Lee is a Ph.D. student specializing in human factors in the School of Industrial Engineering at Purdue University. His research interest focuses on human factors and human–computer interaction. Recently, he is interested in visualization literacy and human decision-makings with information visualizations.
Bum Chul Kwon
Bum Chul Kwon is a postdoctoral researcher in the Data Analysis and Visualization Group at the University of Konstanz. He received his Ph.D. degree specializing in information visualization and human–computer interaction at Purdue University in 2013. His main research interests include information visualization, visual analytics, and human-based computation.
Ji Soo Yi
Ji Soo Yi is an associate professor specializing in human factors in the School of Industrial Engineering at Purdue University. He founded the HIVE Lab in March 2009. He received his Ph.D. degree from the School of Industrial and Systems Engineering at Georgia Institute of Technology in August 2008. His research topics include human–computer interaction, information visualization, and decision science.