Right-brain utilization in pharmacists' dispensing processes: an eye-tracking analysis of efficiency and safety using
Toshikazu Tsuji1, Kenichiro Nagata2, Masayuki Tanaka3
1Department of Clinical Pharmacy, Setsunan University, Osaka, Japan. toshikazu.tsuji@setsunan.ac.jp.
Background:
Dispensing errors associated with "same-name drugs" and "similar-name drugs" are common, negatively affecting patients. Using two pairs of error-induction models, this study analyzed pharmacists' gaze movements while dispensing by an eye-tracking method to interpret their thought processes. Thus, we aimed to assess the efficiency and safety of dispensing processes by examining right-brain function using error-induction models.
Methods:
We created verification slides for display on a prescription monitor and three drug rack monitors. The prescription monitor displayed the dispensing information, including drug name, drug usage, location display, and total amount. A total of 180 drugs, including five target drugs, were displayed on the three-drug rack monitors. We measured total gaze points in the prescription area (Gaze 1), total gaze points in the drug rack area (Gaze 2), total vertical eye movements between the two areas (Passage), time required to dispense drugs (Time), and the error rate for each verification (Error). First, we defined two types of location display methods: "numeral combination" and "color/symbol combination". Then, we established two pairs of error-induction models, F1-F2 (same-name drugs) and G1-G2 (similar-name drugs), to compare the differences between the two location display methods in the designated area.
Results:
Significant differences in gaze movements of pharmacists between the models F1-F2 were observed in Gaze 2, Passage, and Time (F1 > F2, P < 0.001, respectively), with similar results between models G1-G2 (G1 > G2, P < 0.001, respectively). Furthermore, the error rates in models F1 and F2 were 10.0% (11/110) and 6.4% (7/110), as well as 13.6% (15/110) and 5.5% (6/110) in models G1 and G2, respectively. A significant difference in error rates was observed between the models G1-G2 (G1 > G2, P = 0.020), but not between the models F1-F2 (P = 0.286).
Conclusions:
Incorporating visual information into prescription content not only performs a series of dispensing tasks more smoothly, but also reduces the error occurrences by pharmacists. In other words, leveraging right-brain utilization in dispensing processes has led to improvements in both efficiency and safety.
More Related Videos
07:36Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects
Published on: November 30, 2018
10:43Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
Published on: June 10, 2021
Related Concept Videos
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
Model Approaches for Pharmacokinetic Data: Compartment Models
Two primary types of compartment models are recognized: mammillary and catenary. The more...
Pharmacokinetic Models: Overview
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
