Quality of care is important in health care systems, and reducing medication errors is an effective approach to improve health care quality because medication errors are not rare and can cause adverse patient outcomes. Current researchers have adopted contextual, macro level methods to study the medication administration process, but the association between cognitive factors and nurses’ abilities to identify medication errors during this process remains unclear. In this research, I tested whether methods for analyzing visual scanning patterns are applicable to the study of health care processes, specifically how nurses complete the medication administration process.
The data used in this study was collected during three experiments wherein nurse participants wore an eye tracking device to record their eye movements while they performed a medication administration process, with some trials containing an embedded patient identification error. The three experiments included: Nurses administering medications in a simulated setting Nurses using barcoding technology to administer medication in a simulated setting Nurses using barcoding technology to administer medication in a real clinical setting
I focused on four types of visual scanning patterns when analyzing the eye tracking data: 1) nurses’ eye fixation distributions, 2) nurses’ maximum consecutive eye fixations, 3) nurses’ eye gaze transition ratios, and 4) nurses’ two gaze scanpaths. By using the aforementioned methods, I was able to distinguish visual scanning patterns between groups of nurses who identified and did not identify a patient identity error, assessed how barcode technology influenced nurses’ visual scanning patterns, and assessed how nurses’ visual scanning patterns differed in simulated and real clinical environments. These findings may have implications for the design of medication administration protocols, nurse training, and technology design.
Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:theses-1726 |
Date | 01 January 2011 |
Creators | He, Ze |
Publisher | ScholarWorks@UMass Amherst |
Source Sets | University of Massachusetts, Amherst |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Masters Theses 1911 - February 2014 |
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