Predicting medication wastage using machine learning based on patient beliefs
This study is the first to apply ML to address medication wastage in a Southeast Asian context, filling a critical research gap. The proposed model provides a foundation for developing targeted interventions to reduce medication wastage and supports policymakers and healthcare providers in optimising the allocation of subsidised medications. The insights are broadly applicable to other countries with similar healthcare resource challenges.
Authors
- Sharifah Mumtazah Syed Ahmad (ORCID: https://orcid.org/0000-0002-5498-8451)
- Muhammad Firdaus Aziz (ORCID: https://orcid.org/0000-0002-2090-4336)
- Sorayya Malek (ORCID: https://orcid.org/0000-0001-6450-6404)
- Chong Wei Wen
- Adliah Mhd Ali (ORCID: https://orcid.org/0000-0003-1306-8330)
- Putri Nur Fatin Amir Rudin
- Shubathira Sooriamoorthy
- Ilham Asyilah Mahamood
Institutions
- Universiti Putra Malaysia (MY)
- University of Malaya (MY)
- Tengku Ampuan Rahimah Hospital (MY)
- National University of Malaysia (MY)
Publication Details
- Journal
- Digital Health
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1177/20552076251355127
- Primary Topic
- Pharmaceutical Practices and Patient Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministry of Higher Education, Malaysia