Value Frameworks as a Predictor of HTA Success

How value frameworks shape clinical benefit assessment, uncertainty and reimbursement outcomes

Masterclass Details:

Health Technology Assessment is not simply a review of data – it is a structured interpretation of value, adapted to each context. Understanding the frameworks that underpin this interpretation is critical to predicting and influencing HTA success.

In this 60-minute masterclass, Professor Panos Kanavos from the London School of Economics will explore how formal methodologies such as GRADE inform clinical benefit assessment and shape the identification and interpretation of uncertainty in new product submissions.

The session will also explore the growing influence of independently proposed and validated frameworks, including ESMO-MCBS (European Society of Medical Oncology – Magnitude of Clinical Benefit Scale), in reinforcing perceptions of added benefit – particularly in oncology. These tools increasingly shape the narrative around innovation before cost-effectiveness is even considered.

Beyond the clinical data, HTA bodies may apply decision modifiers such as disease severity, unmet need and rarity to optimise decisions under uncertainty. Professor Kanavos will examine how these modifiers interact with cost-effectiveness thresholds and budget impact assessments – and how companies can proactively position within this decision space.

Finally, the masterclass will analyse the role of risk mitigation strategies, managed entry agreements and conditional reimbursement mechanisms in strengthening the probability of approval. Attendees will gain practical insight into how value frameworks can be used not just to interpret submissions – but to strategically design them for greater HTA success.

Join live to ask your questions and hear directly from LSE Professor Panos Kanavos on how value frameworks can predict and influence HTA success.

Key Learning Objectives:

Understand how GRADE and other clinical benefit assessment methodologies identify uncertainties and shape HTA outcomes;
Discuss the role of independently validated frameworks, such as ESMO-MCBS, in reinforcing perceptions of added clinical benefit;
Analyse how decision modifiers such as severity, unmet need and rarity influence HTA outcomes under uncertainty;
Using case studies, examine how cost-effectiveness and budget impact assessments interact with customer benefit evaluation in final decisions
Identify practical strategies, including risk mitigation and managed entry agreements, to strengthen the probability of HTA success