ReviewJournal of pharmaceutical policy and practice2025
Impact of equivalent units of production on state-controlled unit cost calculation for fair pricing of pharmaceuticals: a scoping review.
Review in Journal of pharmaceutical policy and practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Ninety-one percent of 1500 patient groups surveyed across 78 countries perceive pharmaceutical firms' pricing policies as unfair. Despite this, there is little evidence of pharmaceutical companies adopting continuous process costing, a management accounting method that could help transparently track costs and determine fair pricing. This study investigates the link between unit costs, equivalent production units, and fair pharmaceutical pricing. To enhance transparency, fairness, and affordability, we propose mandating the disclosure of unit cost formulas, costing methods, and markup ceilings in annual reports, in alignment with UN SDG goals. Methods: This review followed the Joanna Briggs Institute's (JBI) methodology for scoping reviews to frame the research question, identify relevant studies in databases, select studies, extract the data, report the results and guide consultation sessions with stakeholders with lived experience on potential implications. The search period was January 2022 to November 2023. We used Preferred Reporting Items for Systematic Reviews and Meta Analysis (PRISMA)-Scoping Review extension to present the results. Results: 46 articles were eligible out of 1,281 initially screened. 8 articles addressed pharmaceutical unit production costs; 1 empirical study focused on Equivalent Units of Production (EUP) practices, revealing discrepancies between industry costing practices and academic models; and, the remaining 37 articles explored fair pricing frameworks, emphasising value-based pricing, ethics, and policy considerations. Three gaps emerged: no studies link pharmaceutical pricing to continuous process costing/EUP, despite extensive fair pricing research; absence of standardised methodologies for applying continuous costing in pharmaceutical contexts; and lack of state-regulated uniform costing systems or enforceable mark-up ceilings, impeding cost transparency and fair pricing. Conclusions: No evidence linked pharmaceutical pricing models to continuous process costing/EUP. Addressing this gap requires mandatory disclosures of regulated uniform costing methods and mark-up ceilings in published annual financial reports. This will improve transparency, social accountability, fair pricing, and medicine affordability - aligning with UN SDGs 3 (Good Health) and 10 (Reduced Inequalities).
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.