Nermina Ferizovic | Health Economics Expert

For the next blog post in my series reviewing papers in the Economics of Cell and Gene Therapies collection in Pharmacoeconomics, I review ‘Managed Entry Agreements for High‑Cost, One‑Off Potentially Curative Therapies: A Framework and Calculation Tool to Determine Their Suitability’ found at the following link: https://link.springer.com/article/10.1007/s40273-024-01433-4. 

This paper aimed to develop a framework to support decision makers in determining whether a managed entry agreement (MEA) is suitable and if so, which type of MEA would be most suitable in relation to cell and gene therapies. To do this, the authors conducted a literature review to identify detail on MEA including challenges, advantages/disadvantages, and best practise. The review findings were supplemented by the experiences of the authors and learnings from atidarsagene autotemcel. A proof-of-concept of the framework using onasemnogene abeparvovec and brexucabtagene autoleucel is presented. 

The framework, which the authors propose can be used at different points of an MEA, consists of four parts, applicable to products where an MEA may be necessary:

1. ­Considerations of the disease and its specific uncertainties and outlining of possible reimbursement models that align with the disease characteristics
2. Defining the specifics of the MEA i.e., considerations around the financial form the MEA should take 
3. Assessment of the different MEA types through scenario-based analyses to determine which is most appropriate 
4. Interpretation of the findings to determine the most appropriate course of action if a MEA was deemed appropriate in the earlier steps

The authors have also developed a user guide consisting of key questions which decision makers should ask themselves as part of the first three steps above. For Step 1, these include whether or not the uncertainty surrounding the clinical data is a make-or-break decision; for Step 2, is there agreement over the relevant outcome measure to use and can this feasibly be captured within a realistic timeframe. If the answer to any of these questions is a no, then the authors recommend a financial reimbursement model (i.e., a price discount) otherwise an outcomes-based approach with a corresponding suitable payment model (e.g., upfront payments, annuity-based, delayed payments) may be feasible and the user should follow the framework. If the user does not have enough data to use the framework including the calculation tool at Step 3, the user is advised to assess the impact of the lack of these data and whether they can proceed using the framework. 

The authors argue that this framework can be used by decision makers to support considerations over whether an MEA is suitable and how the MEA could look although note that its usefulness is only for one-off advanced therapies thereby limiting its use to a subset of advanced therapies. Indeed, there are concerns over whether one-time advanced therapies may require an additional administration. For a specific (undefined) subset of advanced therapies, the framework is well thought out and could be helpful to decision makers who are considering an MEA. 

The framework was designed to determine how useful an MEA could be under certain conditions; however, this is dependent on data availability with users not being able to use the framework (i.e., they would have to stop at Step 2/3) if there is a large gap in evidence. Given the context, it is fair to say that the framework may not be usable in many instances, especially when, as the authors point out, there are no transition probabilities or utility data to populate the calculation tool needed for Step 3. If the data to be collected as part of a proposed MEA are utility data, then this framework is limited in its usefulness although the user may define assumptive values and account for their own risk preferences when running scenarios (but there is no way to assess how likely a scenario is (the authors state this is an area for future development)). 

The framework only allows for two types of financial model (simple payment model and innovative payment model). The feasibility of an innovative payment model is questionable as these are rarely used in practise due to their unworkable nature which become even more unworkable as the degree of uncertainty increases. There are other payment models such as subscription-based models which are increasingly being discussed but are not incorporated within the framework. Regarding simple payment models, experience suggests that where a simple payment model is feasible (i.e., a price discount), then an MEA is unlikely to be attractive to stakeholders due to how resource-intensive they are. In other words, why enter into an MEA when stakeholders can agree a price which is amenable to all parties? These agreements are an implicit agreement between stakeholders that the reduced price is the price payers are willing-to-pay to accept the uncertainty. In effect, this suggests that price discounts sit outside of MEA; this is also suggested by the definition the authors use for MEA: “managed entry agreements are commonly defined as any agreement beyond a ‘yes’ or ‘no’ decision on reimbursement between the manufacturer of a therapy and a healthcare payer”. This definition suggests that a delay in the decision is needed inferring that an acceptable price could not be agreed meaning that the authors have applied an MEA definition which would suggest that a simple payment model should sit outside the framework. The framework could potentially be further developed to have ‘simple payment model’ as an initial go/no-go to MEA considerations decision point. However, notably, there is no agreed definition for MEA in the field.  

The authors suggest that their framework adds transparency to MEAs which can help the development of best practise while retaining price confidentiality. It is important to note that financial elements are not the only elements which stakeholders may require to be confidential given that back calculation may enable accurate estimation of a confidential price. There may also be structural elements of an MEA which may need to remain confidential particularly where the MEA relates to a rare disease. In addition, best practise will likely differ from country to country as MEAs will need to account for healthcare system set-up which can be accounted for to an extent within this tool but with specific nuances missing meaning that the framework may not be helpful for defining the optimal MEA. This is further scuppered by the lack of an agreed definition for MEA, as noted above; such a definition would need to account for nuanced differences between healthcare systems while being specific enough to cover the necessary concepts.  

In conclusion, the framework presented in this publication is a good starting point for developing a framework to guide decision makers in the development of an MEA. However, it is currently too general meaning that its usefulness is limited. Finally, an area of development for the field is an agreed definition for MEA although the feasibility of one remains to be assessed.