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.
| Item Type: | Article |
|---|---|
| Creators: | Creators Email / ID Num. Mohd Ismail, Nafeeza UNSPECIFIED Venkateswaran, Sunil P. UNSPECIFIED Alias, Aida Lina UNSPECIFIED |
| Subjects: | R Medicine > R Medicine (General) > Medical education. Medical schools. Research R Medicine > RM Therapeutics. Pharmacology > Study and teaching |
| Divisions: | Universiti Teknologi MARA, Shah Alam > Institute Of Continuing Education & Professional Studies (iCEPS) |
| Journal or Publication Title: | International Journal on E-Learning and Higher Education (IJELHE) |
| UiTM Journal Collections: | UiTM Journals > International Journal of e-Learning and Higher Education (IJELHE) |
| ISSN: | eISSN: 3030-6663 |
| Volume: | 21 |
| Number: | 3 |
| Page Range: | pp. 32-42 |
| Keywords: | Artificial Intelligence, Patient safety, Prescribing competence, Prescribing errors, Virtual patients |
| Date: | 30 September 2026 |
| URI: | https://ir.uitm.edu.my/id/eprint/147796 |
147796.pdf
