Development of multi-criteria decision analysis (MCDA) framework for off-patent pharmaceuticals - an application on...

Off-patent pharmaceuticals (OPPs) hold vital importance in meeting public health objectives, especially in developing countries where resources are limited. OPPs are comprised of off-patent originals, branded generics and unbranded generics; nonetheless, these products are not identical and often there are differences in their equivalence, manufacturing quality standards and reliability of supply. This necessitates reconsideration of the lowest price policy objective in pharmaceutical decision making. The aim of this study was to develop a Multi-Criteria Decision Analysis (MCDA) framework through a pilot workshop to inform the national procurement of OPPs in Indonesia.

An initial list of potentially relevant criteria was identified based on previous work and a literature review. In a 2-day pilot policy workshop, twenty local experts representing different stakeholder groups and decision-making bodies selected the final criteria, approved the scoring function for each criterion, and assigned weights to each criterion.

An MCDA framework was proposed for OPP drug decision making in developing countries, which included price and 8 non-price criteria. Based on the pilot policy workshop 6 + 1 criteria were considered relevant for Indonesia: pharmaceutical price (40% weight), manufacturing quality (18.8%), equivalence with the reference product (12.2%), product stability and drug formulation (12.2%), reliability of drug supply (8.4%), real world clinical or economic outcomes, such as adherence or non-drug costs (4.2%) and pharmacovigilance (3.6%).

According to the pilot policy workshop, other criteria apart from price need to be strengthened in the tendering process. The introduction of additional criteria for OPP procurement in an MCDA framework creates incentives for manufacturers to invest into improved manufacturing standards, equivalence proof, product quality, reliability of supply or even additional real-world data collection, which ultimately may result in more health gain for the society.