Virtual patients: an affordable and sustainable way to teach safe prescribing to enhance clinical competence

Mohd Ismail, Nafeeza and Venkateswaran, Sunil P. and Alias, Aida Lina (2026) Virtual patients: an affordable and sustainable way to teach safe prescribing to enhance clinical competence. International Journal on E-Learning and Higher Education (IJELHE), 21 (3): 4. pp. 32-42. ISSN eISSN: 3030-6663
Identification Number (DOI): 10.24191/ijelhe.v21n3.2134
Abstract

Patient safety is a fundamental priority in medical practice, and safe prescribing is a critical component of preventing medication-related harm. Despite its importance, prescribing errors remain common, while medical students may have limited opportunities to develop and practise prescribing competencies in authentic clinical contexts. This is a global challenge, and Malaysia is no exception. Conventional approaches, including small-group teaching and simulation-based learning, can be resource-intensive and difficult to implement at scale. This project therefore proposes developing an artificial intelligence (AI)-powered virtual patient system as an innovative, scalable, and sustainable approach to prescribing education. Grounded in experiential learning principles and established frameworks for safe prescribing, the system will present students with authentic clinical scenarios that require prescribing decisions and provide immediate, contextualised feedback. The virtual patients will respond dynamically to students’ prescribing decisions, including improving when appropriate medications are prescribed or experiencing adverse outcomes when inappropriate prescriptions are made, providing a safe environment in which students can make, recognise, and learn from errors without exposing real patients to harm. The proposed system will be integrated longitudinally into the undergraduate medical curriculum through a spiral approach, whereby students encounter foundational prescribing scenarios during the pre-clinical years and progressively revisit more complex clinical situations throughout their clinical training. Students’ prescribing competence and error patterns will be assessed longitudinally to evaluate changes in performance over time. By integrating artificial intelligence with evidence-based pedagogy and experiential learning, this project aims to provide an affordable, scalable, and sustainable solution to strengthen prescribing competence and promote a culture of medication safety among future medical practitioners.

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