[2026-01-28] Assessment of Pharmacist Prescription Screening Processes Using Eye Tracking Technology: A Mixed-Method Pilot Study

Authors

  • Ladawan Siriluck Department of Pharmacy, Maharaj Nakorn Chiang Mai Hospital, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
  • Kun-Pin Hsieh School of Pharmacy, College of Pharmacy, Kaohsiung Medical University, Kaohsiung, Taiwan
  • Yi-Ru Lai School of Pharmacy, College of Pharmacy, Kaohsiung Medical University, Kaohsiung, Taiwan
  • Suthinee Taesotikul Department of Pharmaceutical Care, Faculty of Pharmacy, Chiang Mai University, Chiang Mai, Thailand
  • Piyatida Panitsupakamol Doctor of Philosophy Program in Pharmacy (International Program), Faculty of Pharmacy, Chiang Mai University, Chiang Mai, Thailand
  • Kasamaporn Noomphun Department of Pharmacy, Maharaj Nakorn Chiang Mai Hospital, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
  • Sumanus Pramoolsinsup Department of Pharmacy, Maharaj Nakorn Chiang Mai Hospital, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
  • Nantawarn Kitikannakorn Department of Pharmaceutical Care, Faculty of Pharmacy, Chiang Mai University, Chiang Mai, Thailand https://orcid.org/0000-0002-0167-5849

DOI:

https://doi.org/10.33165/rmj.2027.e277029

Keywords:

Electronic prescribing system, Eye tracking, Medication error, Drug related problems, Prescription screening

Abstract

Background: Accurate medication dispensing is essential for patient safety. Electronic prescription (EP) systems are effective because they support  the cognitive functions of pharmacists. Eye tracking provides rapid, objective insights into the visual attention and cognitive engagement of pharmacists interacting with EP interfaces, offering details unmatched by other methods.

Objective: To assess prescription screening practice of pharmacists by analyzing their visual attention (fixation duration, scanpath length, and heatmaps) and cognitive engagement (qualitative responses and error detection) with EP systems using eye-tracking technology.

Methods: Ten hospital pharmacists reviewed 2 medication error scenarios using eye tracking with the Tobii Eye Tracker 4C. The interface mimicked routine hospital software, allowing free review with no time limits. Participants recorded subjective responses after identifying errors, while software logs captured their visual attention patterns (eg, fixations, scanpaths, and heatmaps) and qualitative responses to assess cognitive engagement.

Results: Ten pharmacists participated, including 5 seniors with an average of 9.4 years of hospital experience and 5 juniors with an average of 3 years. A quantitative analysis of heatmaps revealed that senior pharmacists adopt a comprehensive approach, integrating clinical data and medication details, whereas junior pharmacists primarily focus on medication names and doses. A qualitative analysis of participant responses revealed that senior pharmacists demonstrated broader attention patterns during prescription review, facilitating faster, more holistic decision-making. Although most participants correctly identified dosing errors, few participants detected interactions or duplications. These results suggest that experience influences visual focus and accuracy in prescription screening, thereby informing targeted training strategies.

Conclusions: Heatmap data revealed that senior pharmacists conducted more comprehensive reviews, with longer fixations correlating with higher accuracy. Most dosing errors were identified, and interactions and duplications were often overlooked because of over-reliance on EP tools and limited clinical judgment. These outcomes indicate the need for targeted pharmacy interventions, including enhanced clinical reasoning training and improved EP interface design for better drug interaction detection.

References

Aufegger L, Serou N, Chen S, Franklin BD. Evaluating users' experiences of electronic prescribing systems in relation to patient safety: a mixed methods study. BMC Med Inform Decis Mak. 2020;20(1):62. doi:10.1186/s12911-020-1080-9

Wright DFB, Anakin MG, Duffull SB. Clinical decision-making: an essential skill for 21st century pharmacy practice. Res Social Adm Pharm. 2019;15(5):600-606. doi:10.1016/j.sapharm.2018.08.001

Scutt G, Williams S, Auyeung V, Overall A. Clinical decision-making and dispensing performance in pharmacy students and its relationship to executive function and implicit memory. Explor Res Clin Soc Pharm. 2021;5:100096. doi:10.1016/j.rcsop.2021.100096

Tsai CC, Kim JY, Chen Q, et al. Effect of artificial intelligence helpfulness and uncertainty on cognitive interactions with pharmacists: randomized controlled trial. J Med Internet Res. 2025;27:e59946. doi:10.2196/59946

Raschke M, Blascheck T, Burch M. Visual Analysis of Eye Tracking Data. In: Huang W, ed. Handbook of Human Centric Visualization. Springer; 2014:391-410. doi:10.1007/978-1-4614-7485-2_15

Kang D, Charlton P, Applebury DE, et al. Utilizing eye tracking to assess electronic health record use by pharmacists in the intensive care unit. Am J Health Syst Pharm. 2022;79(22):2018-2025. doi:10.1093/ajhp/zxac158

Zhu M, Bao D, Yu Y, Shen D, Yi M. Differences in thinking flexibility between novices and experts based on eye tracking. PLoS One. 2022;17(6):e0269363. doi:10.1371/journal.pone.0269363

Armando LG, Miglio G, de Cosmo P, Cena C. Clinical decision support systems to improve drug prescription and therapy optimisation in clinical practice: a scoping review. BMJ Health Care Inform. 2023;30(1):e100683. doi:10.1136/bmjhci-2022-100683

Sukhanon N, Srimaphol W, Wongkhrut M, Kongnil N, Thongsri N, Supapaan T. Development of a prescription screening system for reducing medication error in an in-patient department, Sunpasitthiprasong Hospital, Ubon Ratchathani province. Isan J Pharm Sci. 2021;17(3):25-38. doi:10.14456/ijps.2021.15

Westbrook JI, Reckmann M, Li L, et al. Effects of two commercial electronic prescribing systems on prescribing error rates in hospital in-patients: a before and after study. PLoS Med. 2012;9(1):e1001164. doi:10.1371/journal.pmed.1001164

Pauszek JR. An introduction to eye tracking in human factors healthcare research and medical device testing. Human Factors in Healthcare. 2023;3:100031. doi:10.1016/j.hfh.2022.100031

Hu H, Li H, Wang B, Zhang M, Wu B, Wu X. Application of eye-tracking in nursing research: a scoping review. Nurs Open. 2024;11(2):e2108. doi:10.1002/nop2.2108

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Published

2026-01-28

How to Cite

1.
Siriluck L, Hsieh K-P, Lai Y-R, Taesotikul S, Panitsupakamol P, Noomphun K, Pramoolsinsup S, Kitikannakorn N. [2026-01-28] Assessment of Pharmacist Prescription Screening Processes Using Eye Tracking Technology: A Mixed-Method Pilot Study. Res Med J [internet]. 2026 Jan. 28 [cited 2026 Jan. 29];:e277029. available from: https://he02.tci-thaijo.org/index.php/ramajournal/article/view/277029

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Original Articles