Background Price negotiations for specialty pharmaceuticals take place in a complex market setting. The determination of the added value of new treatments and the related societal willingness to pay are of increasing importance in policy reform debates. From a behavioural economics perspective, potential cognitive biases and other-regarding concerns affecting outcomes of reimbursement negotiations are of interest. An experimental setting to investigate social preferences in reimbursement negotiations for novel, oncology pharmaceuticals was used. Of interest were differences in social preferences caused by incremental changes of the patient outcome. Methods An online experiment was conducted in two separate runs (n = 202, n = 404) on the Amazon Mechanical Turk (MTurk) platform. Populations were split into two (run one) and four (run two) equally sized treatment groups for hypothetical reimbursement decisions. Participants were randomly assigned to the role of a public price regulator for pharmaceuticals (buyer) or a representative of a pharmaceutical company (seller). In run two, role groups were further split into two different price magnitude framings (“real world” vs unconverted “real payoff” prices). Decisions had real monetary effects on other participants (in the role of premium payers or investors) and via charitable donations to a patient organisation (patient benefit). Results 56 (run one) and 59 (run two) percent of participants stated strictly monotone preferences for incremental patient benefit. The mean incremental cost-effectiveness ratio (ICER) against standard of care (SoC) was higher than the initial ICER of the SoC against no care. Regulators stated lower reservation prices in the “real world” prices group compared to their colleagues in the unconverted payoff group. No price group showed any reluctance to trade. Overall, regulators rated the relevance of the patient for their decision higher and the relevance of their own role lower compared to sellers. Conclusions The price magnitude of current oncology treatments affects stated preferences for incremental survival, and assigned responsibilities lead to different opinions on the relevance of affected stakeholders. The design is useful to further assess effects of reimbursement negotiations on societal outcomes like affordability (cost) or availability (access) of new pharmaceuticals and test behavioural policy interventions.

Background The necessity to measure and reward “value for money” of new pharmaceuticals has become central in health policy debates, as much as the requirement to assess the “willingness to pay” for an additional, quality-adjusted life year (QALY). There is a clear need to understand the capacity of “value-based” pricing policies to impact societal goals, like timely access to new treatments, sustainable health budgets, or incentivizing research to improve patient outcomes. Not only the pricing mechanics, but also the process of value assessment and price negotiation are subject to reform demands. This study assesses the impact of a negotiation situation for life-extending pharmaceuticals on societal outcomes. Of interest were general effects of the bargaining behaviour, as well as differences caused by the assigned role and the magnitude of prices. Methods We ran an online experiment (n = 404) on Amazon Mechanical Turk (MTurk). Participants were randomly assigned into four treatment groups for a reimbursement negotiation between two roles (health minister, pharma representative) in two price framings. Payoff to players consisted of a fixed salary and a potential bonus, depending on their preferences, their price offer and the counter offer of a randomly paired negotiation partner. Success had real social consequences on other MTurk users (premium payers, investors) and via donations to a patient association. Results Margins between reservation prices and price offers increased throughout the game. Yet, 47% of players reduced at least once and 15% always their bonus probability to zero in favour of an agreement. 61% of simulated negotiation pairs could have reached an agreement, based on their preferences. 63% of these were successful, leaving 61% of patients with no access to the new treatment. The group with “real world” prices had lower prices and less agreements than the unconverted payoff group. The successful markets redistributed 20% of total assets from premium payers to investors over five innovation cycles. Conclusions The negotiation situation for pharmaceutical reimbursement has notable impact on societal outcomes. Further research should evaluate policies that align preferences and increase negotiation success.

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