OBJECTIVES: We develop a Markov-based model for the evaluation of the budget impact (BI) of new technologies with the aim of providing a flexible tool that can be used for multiple technologies and relies only on information typically available from registrative trials. Although Markov-models are among the tools considered in the ISPOR “Principles of good practice for the Budget Impact Analysis”, they are employed in BIAs only rarely and based on case-specific models. Our approach allows for a systematic use of a Markov-based approach, even in cases where the amount of information on the new technology is still scarce.

METHODS: By introducing a limited number of standardized inputs, the tool allows to forecast incremental expenditure per unit of time (e.g. month) over the desired time horizon, while allowing for sequences of treatments involving n alternatives. The model also allows to account for other circumstances that may affect the budget impact, such as the presence of Managed Entry Agreements (e.g. Payment by Result), the timing of market penetration, variations in the cost of the new technology over the patient treatment period. Real world data from a regional health system are used to validate the model.

RESULTS: Outcomes of the analysis include a projection of monthly (incremental) expenditure and detailas on the distribution of patients across alternative treatments at different points in time. Several real-world examples are used to illustrate the characteristics of the tool and the biases that can be introduced by more common approaches to BI analysis.

CONCLUSIONS: Real world applications and validation exercises show that the tool proposed allows for sufficiently accurate estimates even in situations where the available information is still scarce. The tool is developed with a focus on cancer care, given the complications of frequent transitions between treatments, but it can be adapted for use in other clinical areas.