Presentation (CTI)

OBJECTIVES: A mathematical framework is described for evaluating budget impact (BI) and cost-effectiveness (CE) models in the presence or not of dynamic (lifecycle) pricing and/or dynamic uptake (multiple cohorts). The framework has been implemented in the R package, DynamicPV, and is illustrated with examples of each model type.
METHODS: A simple CE model is described (three state partitioned survival model in an advanced oncology setting over 20 year horizon) evaluating a new treatment vs standard of care (SoC) under conventional static approach. Assumptions are then made for the expected dynamic uptake of the new treatment, if adopted, and the dynamic evolution of all drug prices. A corresponding BI model is constructed with static pricing, inherent dynamic uptake, but with a five year horizon. The ICER per QALY is calculated from the CE model, and BI from the BI model, with and without dynamic pricing/uptake assumptions, using DynamicPV.
RESULTS: The CE model had an ICER for new treatment vs SoC of $126,451 per QALY under a static model. ICERs were $124,059, $149,782 and $94,570 per QALY with dynamic pricing, dynamic uptake, and both dynamic pricing and uptake respectively. The BI was $14.041m (+109%) with static pricing and $17.020m (+148%) with dynamic pricing. CE and BI results were sensitive to the assumed rate and timing of pricing changes for both the new treatment and standard of care, as well as the timing of dynamic uptake relative to the models’ time horizons. BI results were proportional to population size.
CONCLUSIONS: The mathematical framework implemented in the DynamicPV R package enables practical, transparent, and reproducible CE and BI evaluation with dynamic pricing and/or dynamic uptake (or neither). Uptake is not a new concept for BI models; and data exists to inform dynamic pricing assumptions. Incorporating these effects can be important, and strongly synergistic, but need not be challenging.