Modeling Pooled Procurement of Philippine Department of Health Drugs and Medicines Using OLS Regression

• المؤلفون الرئيسيون: Dy-Liacco, Chloe Marie M., Magsajo, Theresa Denise C., Say, Kimberlee S., Go, Clark Kendrick C, Uy, Jhanna, Antonio, Victor Andrew A.
• التنسيق: text
• منشور في: Archīum Ateneo 2024
• الموضوعات: Applied Mathematics; Data Science
• الوصول للمادة أونلاين: https://archium.ateneo.edu/mathematics-faculty-pubs/302; https://doi.org/10.1063/5.0213405

Pharmaceutical drugs and medicines are essential to modern healthcare, and in the Philippines, public healthcare facilities acquire these through the Philippine Government E-Procurement System (PhilGEPS). Economic theory and existing empirical studies show that pooled procurement can reduce unit prices for certain drugs and medicines, wherein pooled procurement occurs when buyers of the same product consolidate their separate orders into one single order. However, extensive research focusing on price-quantity relationships in the Philippine market is yet to be done. Moreover, the effects of pooled procurement on each drug have yet to be explored. As such, this study determines the extent of price changes in drugs and medicines if pooled procurement were implemented for pharmaceuticals in the Philippines. This was done using pharmaceutical bids across 2010 to 2021 from the PhilGEPS database, after pre-processing steps such as item label corrections using fuzzy match algorithms and price conversions to their equivalents in 2012 in consideration of Philippine peso inflation data. Afterwards, modeling price and quantity data was performed for 273 different medicines using the ordinary least squares (OLS) regression algorithm. The results of the modeling showed that the unit prices of 37 drugs and medicines would decrease by a median average of 18.31% and a mean average of 20.31% should orders be pooled, thereby benefiting from pooled procurement. Moreover, most of these 37 pharmaceuticals fall under the following therapeutic areas: "Anti-Infectives for Systemic Use", "Cardiovascular System", or "Nervous System". Such information may help develop recommendations for policymakers regarding which pharmaceutical orders are most appropriate for pooling in pilot runs of pooled procurement systems.