Managed Entry Agreements (MEA)

DSU report

Framework for analysing risk in Health Technology Assessments and its application to Managed Entry Agreements (January 2016)


Recent changes to the regulatory landscape of pharmaceuticals may require reimbursement authorities to issue guidance on technologies with an evidence base that is less mature than has previously been the case. The greater uncertainty regarding the clinical and cost-effectiveness of new technologies at the point of decision making in a Health Technology Assessment (HTA) translates into a larger risk to the health-care payer. Decision makers need to be aware of the magnitude of those risks and the potential to manage it through assessment of a broad range of decision options, including so-called Managed Entry Agreements (MEAs).

Objective: The aim of this work was to present an analytical framework that can both quantify the need for an MEA, and assess the value of different MEAs for their reduction in the risk to the payer.

Methods: We developed the MEA risk analysis framework, an updated taxonomy of MEA schemes and the MEA design guidance questionnaire. Within this framework, we developed the concepts of Payer Uncertainty Burden (PUB), a measure of the risk associated with decision uncertainty in a HTA; and the Payer Strategy Burden (PSB) which quantifies the additional risk linked to each strategy in the HTA, given the proposed price and available evidence. We called the sum of the two the Payer Strategy and Uncertainty Burden (P-SUB). Both can be calculated with commonly used cost-effectiveness models, probabilistic sensitivity analyses (PSA) and the Sheffield Accelerated Value of Information (SAVI) online tool. We applied the MEA risk analysis framework to eight past NICE technology appraisals. One of these case studies was an application to pazopanib for treatment of advanced renal cell carcinoma that included the assessment of different competing schemes. In the other seven case studies, we quantified the P-SUB associated with different decision options (without analysing specific MEA proposals). In three of these, we also examined the decision context in detail and described the rationale for, and the potential design of, possible MEA schemes.

Results: The application of the framework in past NICE technology appraisals confirmed its feasibility within relatively short timelines. In the application to the pazopanib case study it was shown that recommending cost-ineffective technologies was associated with a great risk of making the wrong decision and consequently a cost to the payer that could reach much larger magnitudes than the cost of decision uncertainty alone. The value of different price reduction and evidence collection schemes depended on the uncertainties present in the appraisal and the magnitude of the PSB. In this case study, a combination of price reductions and research achieved the greatest impact in terms of reducing the payer risk as quantified by the P-SUB.

Conclusion: This report concludes that coherent, consistent and transparent assessments of proposed MEA schemes are critical. The MEA risk analysis framework proposed to routinely evaluate the decision risk in terms of Payer Uncertainty Burden and Payer Strategy Burden in HTA offers a consistent and transparent method of assessing the need for and the value of MEA schemes that is feasible within standard HTA timelines.