PRM32 One Day Money Will Only Be Spent on Effective Drugs…from Payers' Aspirations to Performance-Based Risk-Sharing Operations

Abstract

To define an operational modelling framework intended to help the design of Performance-Based Risk-Sharing (PBRS) schemes. A time-to-event endpoint is used as a performance criterion. Such survival endpoints are commonly used in clinical studies, notably in oncology where PBRS schemes are gaining momentum. The framework is based on an open population model with a monthly cycle and 3-year time horizon from launch (i.e. when enrolment into the PBRS scheme starts). Entry into the model (i.e. the progressive arrival of new patients into the PBRS scheme) is determined by market diffusion assumptions and is modelled using a Logistic function. Exit from the model (i.e. patients experiencing the event or dying from any cause) is determined by survival curves from clinical/epidemiological studies and is modelled using a Weibull function. The model accommodates different treatment dosing schedules and performance levels (i.e. minimum survival times guaranteed). Multiple PBRS scenarios can be run and compared in terms of their operational and financial implications. Additionally, the effect of potential revisions of a PBRS scheme terms and conditions can also be examined as real-life information becomes available following scheme implementation (i.e. Bayesian updating). For example, assuming 1,000 patients enrolled in a PBRS scheme, with a monthly dosing schedule and given diffusion (Logistic α=5.0; β=0.4) and survival (Weibull λ=0.7; k=27.0) assumptions, the model predicts that 1937 (6970), 4050 (7861) and 9282 (4420) doses will be given to non-responding (responding) patients with 12, 18 and 24 months minimum survival time guaranteed scenarios, respectively. This framework provides both payer and manufacturer with valuable insight into the operational and financial dimensions of the potential PBRS schemes they may contemplate as they negotiate patient access conditions. Both parties can better anticipate the implications of the schemes and better plan resources, logistics and financial arrangements accordingly.