Prescription: Issue No. 12 (Disember 2023)
The Global Patient Safety Challenge: Medication Without Harm initiated by the World Health Organization, aims to reduce the level of severe, avoidable harm related to medications by 50% within a span of 5 years (1). Over the years, substantial progress has been made in improving medication safety, y...
Saved in:
| Main Author: | |
|---|---|
| Format: | Monograph |
| Language: | English |
| Published: |
Faculty of Pharmacy, Universiti Teknologi MARA, Kampus Puncak Alam
2023
|
| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/101420/1/101420.pdf https://ir.uitm.edu.my/id/eprint/101420/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Teknologi Mara |
| Language: | English |
| Summary: | The Global Patient Safety Challenge: Medication Without Harm initiated by the World Health Organization, aims to reduce the level of severe, avoidable harm related to medications by 50% within a span of 5 years (1). Over the years, substantial progress has been made in improving medication safety, yet challenges persist (2). Majority of current patient safety approaches were developed prior to the healthcare digital revolution. Significant advances in healthcare practises can be achieved by adopting modern technological tools and digital advancements which hold the potential to substantially improve the prediction and prevention of patient safety risks.
Artificial Intelligence (AI) has rapidly transformed industries, notably in healthcare. AI implementation in the domain of medication safety is not, however, new. Using inputs from databases containing known effects, patient parameters, and drug information, a neural-network analysis with a high Latest news and updates from the Faculty of Pharmacy, UiTM accuracy, was implemented in the early 1990s to forecast adverse effects of antidepressants (3). Recent years have witnessed AI, particularly machine learning, predominantly employed in patient safety and pharmacovigilance, notably in identifying adverse drug events and extracting insights from safety reports and clinical narratives (4). |
|---|