
As healthcare costs continue to rise, accurate cost-effectiveness estimates are crucial. However, estimating the costs and outcomes of different interventions is complicated by uncertainty.
In model-based health economic evaluations (HEEs), uncertainty can arise from limited data, methodological limitations, and variability in clinical outcomes.
A recent review identified 80 methods for identifying, analyzing, and communicating uncertainty in HEEs. Quantifying uncertainty wherever possible is crucial to ensure accurate and unbiased cost-effectiveness estimates, ultimately leading to optimal allocation of healthcare resources
Recent Posts
Impact of Insulin Copay Caps on Medicare Beneficiary Health and Spending
In this update, we highlight a JAMA Internal Medicine article that analyzed the real-world impact of insulin copay caps on Medicare beneficiaries with type 2 diabetes. According to a new study, these policies have successfully lowered out-of-pocket insulin costs and improved adherence among exist...
Advancing the Biosimilar Approval Framework: A Shift Towards Analytical Comparability
Below we highlight how the European Medicines Agency (EMA) is reshaping the biosimilar approval framework by prioritising advanced analytical characterisation over traditional comparative efficacy studies. A recently finalized reflection paper outlines a science-based, tailored clinical develo...
Current Challenges in Outcome Transparency Healthcare in Dutch Medical Specialist Care
In this update we highlight the persistent shortcomings in outcome transparency in Netherland's healthcare system. The 2026 baseline measurement report published by Zorginstituut Nederland and Patiëntenfederatie Nederland shows that national ambitions for transparency of care outcomes in medical ...