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.
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12 July 2024
4TH INTERNATIONAL CONFERENCE ON APPLIED & INDUSTRIAL MATHEMATICS AND STATISTICS 2023 (ICoAIMS 2023): Mathematics and Statistics for Technological Society
22–24 August 2023
Pahang, Malaysia
Research Article|
July 12 2024
Modeling pooled procurement of Philippine department of health drugs and medicines using OLS regression Available to Purchase
Chloe Marie M. Dy-Liacco;
Chloe Marie M. Dy-Liacco
1
Collaborative Analytics Group, Department of Mathematics, Ateneo de Manila University
, Katipunan Ave, Quezon City, 1108 Metro Manila, Philippines
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Theresa Denise C. Magsajo;
Theresa Denise C. Magsajo
1
Collaborative Analytics Group, Department of Mathematics, Ateneo de Manila University
, Katipunan Ave, Quezon City, 1108 Metro Manila, Philippines
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Kimberlee S. Say;
Kimberlee S. Say
1
Collaborative Analytics Group, Department of Mathematics, Ateneo de Manila University
, Katipunan Ave, Quezon City, 1108 Metro Manila, Philippines
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Clark Kendrick C. Go;
Clark Kendrick C. Go
a)
1
Collaborative Analytics Group, Department of Mathematics, Ateneo de Manila University
, Katipunan Ave, Quezon City, 1108 Metro Manila, Philippines
a)Corresponding author: [email protected]
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Jhanna Uy;
Jhanna Uy
2
Philippine Institute for Development Studies
, 18F Three Cyberpod Centris - North Tower, EDSA corner Quezon Avenue, Quezon City, Metro Manila, Philippines
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Victor Andrew A. Antonio
Victor Andrew A. Antonio
1
Collaborative Analytics Group, Department of Mathematics, Ateneo de Manila University
, Katipunan Ave, Quezon City, 1108 Metro Manila, Philippines
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Chloe Marie M. Dy-Liacco
1
Theresa Denise C. Magsajo
1
Kimberlee S. Say
1
Clark Kendrick C. Go
1,a)
Jhanna Uy
2
Victor Andrew A. Antonio
1
1
Collaborative Analytics Group, Department of Mathematics, Ateneo de Manila University
, Katipunan Ave, Quezon City, 1108 Metro Manila, Philippines
2
Philippine Institute for Development Studies
, 18F Three Cyberpod Centris - North Tower, EDSA corner Quezon Avenue, Quezon City, Metro Manila, Philippines
a)Corresponding author: [email protected]
AIP Conf. Proc. 3128, 030002 (2024)
Citation
Chloe Marie M. Dy-Liacco, Theresa Denise C. Magsajo, Kimberlee S. Say, Clark Kendrick C. Go, Jhanna Uy, Victor Andrew A. Antonio; Modeling pooled procurement of Philippine department of health drugs and medicines using OLS regression. AIP Conf. Proc. 12 July 2024; 3128 (1): 030002. https://doi.org/10.1063/5.0213405
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