Abstract:

Objective: Using decisions from the Pharmaceutical Benefits Advisory Committee of Australia (PBAC), we propose a simple informal game theoretic model of bargaining to generate hypotheses about factors that determine the relative bargaining power of the funder and manufacturer: (value, risk, time, and outside options) and test these in an empirical model of the time to an agreement on price. Data sources: Evidence presented at meetings of the PBAC that makes recommendations on coverage of drugs under the Australian Pharmaceutical Benefits Scheme (PBS) between July 2005 and November 2012 (n=618 submissions) if one of the outcomes measured quality-adjusted life years (QALYs) gained (n=292 submissions). From public summary documents of meetings, we extracted data on drug characteristics including the cost per QALY, the opportunity cost of funding and quality of the evidence. Data from Google Trends was used to measure the level of public interest in the decision as a proxy for the external pressure on the committee to recommend the drug for listing. The Food and Drug Administration (FDA) fast track drug designation was used as an objective measure of both disease severity and the potential of the drug to address an unmet clinical need.

Methods: A Cox proportional hazards survival model was used to analyse the duration of time between first submission and receiving a positive recommendation from the PBAC controlling for bargaining relevant time varying drug characteristics at each decision point.

Results: The median time to positive recommendation from first submission for drugs was 16 months. Consistent with the bargaining model, each $10,000 Australian dollar fall in value (increase in cost per QALY) reduces the risk of positive recommendation at a point in time by 17% (95% CI: 10-24, p<0.001). The risk of positive recommendation significantly reduces if there was considerable uncertainty around the clinical or economic evidence, hazard ratio (HR (95%CI): 0.60 (0.36-0.99) and 0.22 (0.13, 0.37) respectively, but increases if the drug had a clinically important effect (HR (95%CI: 1.68 (0.99-2.83)) or could addressed an unmet clinical need in treating a serious condition (HR (95%CI): 1.99 (1.04, 3.81). Each 100% increase in internet searches for the drug as estimated by Google Trends in the year leading up to the PBAC meeting, increases the risk of a positive recommendation by 44% (95% CI: 9-90). Conclusion: Evidence from Australia suggests that decisions on public funding for pharmaceuticals are consistent with a strategic bargaining process. Time to a recommendation to cover a drug on the national formulary depends on the quality of the evidence, patient need disease severity, and perceived net benefit. In cases where there is a significant surge in public interest, a drug is predicted to have a shorter time to positive recommendation.

Bio:

Professor Anthony Harris is Director of the Centre for Health Economics, Monash University. He has held previous academic positions at the University of Aberdeen, Murdoch University and the University of Western Australia. He has been awarded numerous competitive research grants including an NHMRC funded program modeling the economics of the health care system in Australia, a macroeconomic model of the impact of an influenza epidemic, and an ARC grant on drug pricing.