IMPLEMENTATION OF DIGITAL PLATFORMS FOR REFERENCE PRICING OF MEDICINES: GLOBAL EXPERIENCE AND METHODOLOGICAL APPROACHES

Аннотация

Rising pharmaceutical costs have driven many countries to adopt reference pricing as a tool for regulating medicine prices. However, the effectiveness of this approach depends heavily on access to timely and accurate data from international markets. This article explores the global experience in implementing digital platforms for calculating reference prices, compares key country-level platforms, and presents methodological approaches to selecting and analyzing reference data. Based on case studies and comparative analysis, the article identifies core success factors and outlines recommendations for developing countries seeking to implementor improvedigital tools inthis domain. Keywords: Reference pricing, digital platforms, pharmaceutical regulation, Euripid, PMPRB, e-health,global medicine pricing, case study. Introduction. The continuous rise in medicine prices presents a major challenge for health systems worldwide. Reference pricing has become a commonly used method to limit excessive pharmaceutical spending. However, traditional (manual) reference price calculations are time- consuming, error-prone, and lack transparency. In response, several countries have implemented digital platforms to automate the collection, processing, and analysis of international pricing data. This study investigates global best practices in the implementation of such platforms and provides methodological insights for countries considering digitalization of reference pricing systems. The aim of this research is to analyze the global experience of digital platforms for reference price calculation and to propose methodological principles for selecting, comparing, and applying reference data. Methods. This study employed a combination of research methods, including literature and policy review, comparative analysis, case studies, SWOT analysis, and content analysis to explore the implementation and effectiveness of digital platforms for reference pricing of medicines. Results. A quantitative comparison of selected digital platforms for reference pricing is presented in thetablebelow, highlighting structural and operational attributes: No. of Referenced Avg. Data Year Public Country Platform Countries UpdateInterval Introduced Access (%) EU Monthly (30 Euripid 32 2010 30% (Euripid) days) Quarterly (90 Canada PMPRB 7 1987 50% days) South N/A (Domestic MPR Weekly 2004 100% Africa only) page2420 INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE ISSN:2692-5206,ImpactFactor:12,23 AmericanAcademicpublishers,volume05,issue05,2025 Journal: https://www.academicpublishers.org/journals/index.php/ijai No. of Referenced Avg. Data Year Public Country Platform Countries UpdateInterval Introduced Access (%) Kazakhstan DAR 9 Monthly 2018 20% Table1. Overview ofCountry-Level Digital Platforms Countries utilizing digital platforms tend to update pricing data 2 to 4 times more frequently than those relying on manual systems, leading to improved regulatory responsiveness. In the Euripid collaboration, over 70% of participating countries have fully digitized price registration systems, promoting more accurate and standardized pricing decisions across borders. South Africa’s MPR platform provides real-time access to over 15,000 retail medicine prices, updated on a weekly basis, offering full public transparency. In Canada, the PMPRB monitors and publishes data on more than 1,300 patented medicines, maintaining a historical dataset that spans over 35 years. These numerical insights highlight how platform maturity, update frequency, and public accessibility vary significantly, shaping their impact on national pricing policyand stakeholder trust. Figure 1. Comparison of Digital Platforms for Reference Pricing Based on Key Performance Metrics Figure 1 illustrates a comparative analysis of four national and regional digital platforms for reference pricing: Euripid (EU), PMPRB (Canada), MPR (South Africa), and DAR (Kazakhstan). The platforms are evaluated across four performance metrics: update frequency (per year), numberof referenced countries, publicaccess (%), and integration score (1–5). The results show that South Africa’s MPR platform has thehighest update frequency, reflecting its weekly real-time functionality (52 updates per year), along with full public access (100%). However, it does not use external reference countries, as it is intended solely for domestic price transparency. In contrast, Euripid leads in the number of referenced countries (32), although its updatefrequency is monthly(12per year), and publicaccess islimited (30%). page2421 INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE ISSN:2692-5206,ImpactFactor:12,23 AmericanAcademicpublishers,volume05,issue05,2025 Journal: https://www.academicpublishers.org/journals/index.php/ijai Canada’s PMPRB platform references seven countries and provides moderate public access (50%), but its update frequency is lower (quarterly). Kazakhstan’s DAR platform shows a balanced profile, with monthly updates