Predicting pharmaceutical prices. Advances based on purchase-level data and machine learning.

ABSTRACT:

Background

Increased costs in the health sector have put considerable strain on the public budgets allocated to pharmaceutical purchases. Faced with such pressures amplified by financial crises and pandemics, national purchasing authorities are presented with a puzzle: how to procure pharmaceuticals of the highest quality for the lowest price. The literature explored a range of impactful factors using data on producer and reference prices, but largely foregone the use of data on individual purchases by diverse public buyers.

Methods

Leveraging the availability of open data in public procurement from official government portals, the article examines the relationship between unit prices and a host of predictors that account for policies that can be amended nationally or locall

SUBMITTER: Fazekas M 

PROVIDER: S-EPMC11247880 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature