102. Coin making problem to Outpatient Pharmacy Automation System
Invited abstract in session TC-3: Optimisation, stream Sessions.
Tuesday, 13:30-15:00Room: NTNU, Realfagbygget R9
Authors (first author is the speaker)
| 1. | Kiok Liang Teow
|
| Health Services & Outcomes Research, National Healthcare Group | |
| 2. | Eric Yang
|
| Tan Tock Seng Hospital | |
| 3. | Jabigo Mark Anthony Cadinong
|
| Tan Tock Seng Hospital | |
| 4. | Hong Yee Lim
|
| Tan Tock Seng Hsopital | |
| 5. | Yong Chuan Goh
|
| National Healthcare Group Pharmacy | |
| 6. | Hui Hui Wang
|
| National Healthcare Group Pharmacy | |
| 7. | Edmund Liew
|
| Woodlands Hospital | |
| 8. | Supadhara Ramaiyah
|
| Khoo Teck Puat Hospital | |
| 9. | ZHECHENG ZHU
|
| Health Services & Outcomes Research, National Healthcare Group, Singapore |
Abstract
Some major public hospitals and polyclinics in Singapore collaborated to automate their outpatient pharmacies picking processes to improve safety and efficiency. Automated pharmacy dispensing machines (ADM) could process electronic prescriptions and pick medications stored in standardized boxes. Singapore's public healthcare institutions purchased medication in bulk pack size (e.g. 1000 tables per pack), which then would be repackaged into smaller quantity packages that matched the prescribed quantity.
Our task was to optimise the re-pack configurations. This was like a coin-changing problem, but with more constraints, such as if pack sizes could be any number or had to be in multiples of blister-size, and rounding rules for medication.
This study was conducted by a team of pharmacists and operations researchers. Mixed integer programming was used. Historical prescription patterns were analysed to form the basis of the demand. The study aimed to determine the optimal medication pack size configuration for each mediation, with multiple objectives of: (1) maximising automation coverage for prescription fulfilment, (2) minimising the number of boxes used, and (3) minimising rounding of medications from the prescribed quantity. The mathematical model was applied across hundreds of medications, with each solution tailored to specific prescription patterns and drug characteristics. The resulting optimised configurations served as the foundation for inventory planning.
Keywords
- Healthcare logistics
- Strategic and operational planning
- Process optimisation
Status: accepted
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