Challenge
A pharmaceutical company was preparing the reimbursement submission for a new treatment for a renal disease and needed to adapt a cost-effectiveness model (CEM) and a budget impact model (BIM) to the Portuguese setting.
However, there was uncertainty regarding clinical practice in Portugal, particularly concerning treatment patterns, patient monitoring, healthcare resource utilization, and the therapeutic positioning of the new medicine. This limitation compromised the robustness of the assumptions used in the economic models and their suitability to support the health technology assessment process.
Solution
Clevidence was engaged to support the adaptation of the CEM and BIM to the national context through the collection and validation of clinical and economic evidence.
1. Coordination of an expert panel
Clevidence organized and coordinated a structured expert elicitation process involving clinicians experienced in the management of the renal disease in Portugal.
Clevidence performed the processing and consolidation of the data collected from the experts, transforming qualitative and quantitative information into structured inputs for the economic models.
This analysis enabled:
- Refinement of the clinical and economic assumptions used in the CEM and BIM.
- Adjustment of parameters related to healthcare resource utilization.
- Reduction of uncertainty associated with the estimates used in health economic modelling.
Adaptation of the CEM and BIM to the Portuguese setting
Based on the data obtained through the expert panel, Clevidence adapted the economic models to more accurately reflect real-world clinical practice in Portugal.
- This analysis enabled:
Determination of the incremental cost-effectiveness ratio (ICER), based on the comparison of costs and quality-adjusted life years (QALYs) between the treatment under evaluation and available alternatives. - Estimation of the budget impact associated with the adoption of the medicine within Portuguese NHS hospitals.
Impact
The involvement of Portuguese clinical experts significantly reduced the uncertainty associated with health economic modelling and strengthened the credibility of the models presented during the reimbursement process.
The adaptation of the CEM and BIM to the national context provided the client with a more robust basis to support the economic evaluation of the medicine, facilitate interactions with decision-makers, and strengthen the therapeutic value proposition presented to health authorities.
By leveraging the expertise of the participating clinicians, Clevidence contributed to a more accurate representation of real-world clinical practice in Portugal, increasing confidence in the outcomes of the economic evaluation.