Tsuji Toshikazu, Nagata Kenichiro, Tanaka Masayuki, Iwane Shiori, Hasebe Shigeru, Nishiyama Yuto, Yoshikawa Nana, Watanabe Hiroyuki, Ishida Shigeru, Hirota Takeshi, Ieiri Ichiro, Uchida Mayako
Department of Clinical Pharmacy, Setsunan University, Osaka, Japan.
Department of Pharmacy, Kyushu University Hospital, Fukuoka, Japan.
J Pharm Health Care Sci. 2025 May 5;11(1):37. doi: 10.1186/s40780-025-00443-4.
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.
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, F-F (same-name drugs) and G-G (similar-name drugs), to compare the differences between the two location display methods in the designated area.
Significant differences in gaze movements of pharmacists between the models F-F were observed in Gaze 2, Passage, and Time (F > F, P < 0.001, respectively), with similar results between models G-G (G > G, P < 0.001, respectively). Furthermore, the error rates in models F and F were 10.0% (11/110) and 6.4% (7/110), as well as 13.6% (15/110) and 5.5% (6/110) in models G and G, respectively. A significant difference in error rates was observed between the models G-G (G > G, P = 0.020), but not between the models F-F (P = 0.286).
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.
与“同名药物”和“相似名称药物”相关的配药错误很常见，会对患者产生负面影响。本研究使用两对错误诱导模型，通过眼动追踪方法分析药剂师配药时的注视运动，以解读他们的思维过程。因此，我们旨在通过使用错误诱导模型检查右脑功能来评估配药过程的效率和安全性。
我们创建了用于在处方监视器和三个药架监视器上显示的验证幻灯片。处方监视器显示配药信息，包括药品名称、用法、位置显示和总量。三个药架监视器上共显示了180种药物，包括五种目标药物。我们测量了处方区域的总注视点数（注视1）、药架区域的总注视点数（注视2）、两个区域之间的总垂直眼动次数（通过次数）、配药所需时间（时间）以及每次验证的错误率（错误）。首先，我们定义了两种位置显示方法：“数字组合”和“颜色/符号组合”。然后，我们建立了两对错误诱导模型，F-F（同名药物）和G-G（相似名称药物），以比较指定区域中两种位置显示方法之间的差异。
在注视2、通过次数和时间方面，观察到模型F-F之间药剂师的注视运动存在显著差异（F＞F，P分别＜0.001），模型G-G之间也有类似结果（G＞G，P分别＜0.001）。此外，F和F模型中的错误率分别为10.0%（11/110）和6.4%（7/110），G和G模型中的错误率分别为13.6%（15/110）和5.5%（6/110）。在模型G-G之间观察到错误率存在显著差异（G＞G，P = 0.020），但在模型F-F之间未观察到显著差异（P = 0.286）。
将视觉信息纳入处方内容不仅能更顺利地完成一系列配药任务，还能减少药剂师的错误发生。换句话说，在配药过程中利用右脑功能提高了效率和安全性。
