OBJECTIVES: Decision-makers are required to legitimize their priority setting decisions in health to members of society. To assist health authorities a practical checklist was derived from operationalizing the A4R framework and reflecting on the ethical notions it invokes when addressing the imperative of treating people as moral equals. The aim of this study was to explore whether this check-list needs revision based on qualitative data on what would make the actual adversely affected stakeholders in practice accept the decision-making process they have experienced as fair.

METHODS: 10-15 semi-structured interviews will be conducted with adversely affected participants in current priority setting processes in the Netherlands to provide insight into their thoughts/reflections on how their participation in decision-making processes have been organized. We will use systematic text condensation which is a cross-case thematic analysis for qualitative data in medical research. This approach to the material is organized through four systematic steps: 1) total impression - from chaos to themes; 2) identifying and sorting meaning units - from themes to codes; 3) condensation - from code to meaning; 4) synthesizing - from condensation to descriptions and concepts. Following this step, we will extent the check-list if new, justified conditions are identified that reduce any unnecessary use of power by health authorities.

RESULTS: The theoretically justified check-list is already published while preliminary results of the empirical relevance check will become available during the first months of 2019 and will be ready to present during the ISPOR LATAM conference in September 2019.

CONCLUSIONS: Health authorities are advised to use the improved checklist to assist them in the practical organization of stakeholder participation in their priority setting processes and obtaining their moral authority. Other stakeholders can use the checklist to evaluate current priority setting processes and demand improvements based on their evaluation.