Market Access Uncertainty
Kurt R. Müller
Optimizing Market Access by bridging & aligning life science expectations with payers & decision-makers requirements & needs. ADVISOR I CONSULTANT I CHALLENGER
Most people feel uncomfortable in a situation of uncertainty because, unlike risk, uncertainty is subjective and not measurable [1]. They need more time for evaluations and postpone decisions in the hope of getting even more information. Many people do not make rational decisions under uncertainty [i]. Irrational decisions are unpredictable and lead to unforeseen outcomes that impact the business.
Decision Making under Uncertainty
There is no consensus about the definition of uncertainty, but the HTAi-DIA Working Group has elaborated a key concept with twelve building blocks [2]. Uncertainties arise from clinical and economic inputs. While marketing authorization regulators weight clinical benefit and harm, HTA bodies weight incremental clinical benefits and costs against a benchmark (Relative Efficacy / Relative Effectiveness Assessment - REA) considering willingness to pay (WTP) and e.g. medical need. Consequently, uncertainties about safety are a bigger concern for regulators (85-94%) than for HTA bodies (53-59%), while in terms of relative effectiveness they are 12-32% and 88-100% respectively. In contrast, uncertainty about the patient population is similar between regulators and HTA bodies (60-95%) - see figure 1. The average number of uncertainties are 7.4 (SD 3.8) per drug and institution [3] (US/EU). The degree of uncertainty has an impact on both the assessment of the REA and total reimbursement (RRs 1.9 and 1.6). However, the differences could only be demonstrated for high vs. low uncertainty levels. Interestingly, a high level of uncertainty was associated with faster time between EMA approval and HTA recommendations (NICE, SMC, ZIN) than with a low level of uncertainty (HAS) [4]. The degree of unexplained uncertainty is higher for medicinal products with a conditional marketing authorization (CMA) and their recommendations for inclusion in the positive list are limited and very heterogeneous (29-95%). The reasons for this are mainly uncertainties regarding clinical benefits, study design and questions of economic modelling [5].
?Uncertainty may or may not influence decisions but needs always to be considered? [6]. There is no standard method for representing uncertainty [6]. ?The presence and impact of uncertainties must be communicated to all relevant stakeholders during the HTA output stage? [7]. Communication methods for uncertainty include quantified representations such as efficiency limits, acceptance curves, tornado diagrams [8] and others like ICER Value Framework [9].
Clinical Uncertainties are forwarded to HTA for Pricing and Reimbursement
The evidence requirements of regulators such as the EMA affect what data is shared with HTA Decision-Makers and with what uncertainty; these facts are then correlated against CEA and BIA, considering unmet medical needs and other elements [4]. This task is complicated by the fact that the evidence requirements of regulators in terms of benefits and harms are insufficient for a comparative assessment of HTA authorities [3] especially since the majority of the new studies submitted to the regulatory authority lack active comparators or are not available at all [3]. Moreover, there is limited additional evidence generated in the multi-year post-approval phase. This is especially true in oncology [3].
Uncertainty in Pricing & Reimbursement
The clinical data for the P&R application are largely identical to the pivotal studies that have been made available for marketing authorization. This means that such data are predefined for P&R issues and the value base case of a new drug (Table 1: red boxes). Deliberative argumentation is possible for HTA, SOC, WTP and additional value elements the so-called “Value Flower” [10] (Table 1: yellow boxes). The initial price of a new drug will be adjusted by mutual agreement (Table 1: green box). Medical uncertainty has a much greater impact on pricing than economic uncertainty (Figure 2) because it influences decision-making based on both clinical benefit assessment and cost-effectiveness.
Uncertainties in Market Access are mainly due to the data gaps between regulatory and HTA authorities and institutions. The yellow boxes (Table 1) are areas where the value of a new intervention leaves different interpretations open, leading to uncertainty in decision-making for pricing & reimbursement. This is also the reason for the variability of decisions. The fundamental value of a new intervention is given by regulatory clinical data and can be increased by the acceptance of additional benefit elements.
It is imperative to distinguish between medical and economic uncertainties at both the patient and population levels. Medical uncertainties lower the value and thus also the price level; they are mainly data-based, and additional evidence is needed to reduce uncertainty and thus increase the negotiated price level. On the other hand, economic uncertainties can be reduced through specific pricing models while maintaining value and price levels. For example, cost caps at the individual level or price/quantity agreements at the aggregate population level.
It is imperative to distinguish between medical and economic uncertainties at both the patient and population levels:
Uncertainty is one of the main issue for Cell and Gene Therapy (CGT) [11]. CGTs should be handled somewhat differently for the following reasons: significant uncertainty about benefit and durability, very small clinical database compared to historical control, no reversible high upfront costs, claim for lifetime value, no future savings from generics, often very cost-effective, resulting in a high price that requires savings to be shared with society [12]. The uncertainty with CGTs is mainly at the patient level and is usually much higher than with "conventional" drugs. Pricing models (MEAs) for CGTs tend to focus on Outcome-Based Agreements (Pay for Performance) and recent publications on this topic are recommended for reading [13], [14].
Managing Uncertainties in four Steps
In the end, uncertainties should not come as a surprise, but should appear as unavoidable residual uncertainty (Uncertainty GAP) after a planned reduction in uncertainty. Uncertainty can be avoided or reduced e.g. by early dialog with adequate trial design and evidence generation (Step 1). Residual uncertainty is a basket of one or more medical, economic, and resource uncertainties. Identifying and differentiating between them is crucial, as different pricing models can be applied with fixed or reduced prices (step 2).
Then the crucial question is whether to opt for permanent or temporary discounts and rebates [ii] on the original product price. In the majority cases, permanent uncertainty discounts are offered with different pricing models (Step 3). However, no, or only temporary discounts are possible with result-oriented outcome-based models or additional clinical data (evidence); however, these can lead to a delay in market entry and high additional costs (Step 4).
[ii] The goal for rebates may be: a) price differentiation for access, compensation for uncertainty, or c) compensation for treatment failure.
领英推荐
Don't treat uncertainties as a surprise, but as unavoidable residual uncertainty:
Limitation
This newsletter deals with uncertainty in Market Access. No claim is made to completeness and correctness; additions, corrections and comments are welcome.
References
1. Jedynak P, B?k S. Understanding Uncertainty and Risk in Management. J Intercult Manag. 2020;12(1):12–35.
2. Hogervorst MA, Vreman R, Heikkinen I, Bagchi I, Gutierrez-Ibarluzea I, Ryll B, et al. Uncertainty management in regulatory and health technology assessment decision-making on drugs: guidance of the HTAi-DIA Working Group. Int J Technol Assess Health Care [Internet]. 2023 Jun 16;39(1):e40. Available from: https://www.cambridge.org/core/product/identifier/S0266462323000375/type/journal_article
3. Vreman RA, Naci H, Goettsch WG, Mantel-Teeuwisse AK, Schneeweiss SG, Leufkens HGM, et al. Decision Making Under Uncertainty: Comparing Regulatory and Health Technology Assessment Reviews of Medicines in the United States and Europe. Clin Pharmacol Ther. 2020;108(2):350–7.
4. Bloem LT, Vreman RA, Peeters NWL, Hoekman J, van der Elst ME, Leufkens HGM, et al. Associations between uncertainties identified by the European Medicines Agency and national decision making on reimbursement by HTA agencies. Clin Transl Sci. 2021;14(4):1566–77.
5. Mills M, Kanavos P. How do HTA agencies perceive conditional approval of medicines? Evidence from England, Scotland, France and Canada. Health Policy (New York) [Internet]. 2022;126(11):1130–43. Available from: https://doi.org/10.1016/j.healthpol.2022.08.005
6. Parsons JE. Communicating the findings of health technology assessments: Considering uncertainty. Med Writ. 2021;30(3):56–9.
7. Trowman R, Powers A, Ollendorf DA. Considering and communicating uncertainty in health technology assessment. Int J Technol Assess Health Care. 2021;37(1).
8. Otten TM, Grimm SE, Ramaekers B, Joore MA. Comprehensive Review of Methods to Assess Uncertainty in Health Economic Evaluations. Pharmacoeconomics [Internet]. 2023;41(6):619–32. Available from: https://doi.org/10.1007/s40273-023-01242-1
9. Institue for Clinical and Economic Review. Value Assessment Framework [Internet]. Value Assessment Framework. 2023. Available from: https://icer.org/wp-content/uploads/2023/10/ICER_2023_VAF_For-Publication_101723.pdf
10. Neumann PJ, Garrison LP, Willke RJ. The History and Future of the “ISPOR Value Flower”: Addressing Limitations of Conventional Cost-Effectiveness Analysis. Value Heal [Internet]. 2022 Apr;25(4):558–65. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1098301522000857
11. Frederix GWJ, Ham RM ten. Gene therapies, uncertainty, and decision-making: thinking about the last mile at the first step. Expert Rev Pharmacoeconomics Outcomes Res [Internet]. 2023;23(8):853–6. Available from: https://doi.org/10.1080/14737167.2023.2245138
12. Pearson SD, Ollendorf DA, Chapman RH. New Cost-Effectiveness Methods to Determine Value-Based Prices for Potential Cures: What Are the Options? Value Heal [Internet]. 2019;22(6):656–60. Available from: https://doi.org/10.1016/j.jval.2019.01.012
13. Phares S, Trusheim M, Emond SK, Pearson SD. Managing the Challenges of Paying for Gene Therapy?: Strategies for Market Action and Policy Reform [Internet]. 2024. Available from: https://icer.org/assessment/managing-the-challenges-of-paying-for-gene-therapy-2024/
14. Horrow C, Kesselheim AS. Confronting High Costs And Clinical Uncertainty: Innovative Payment Models For Gene Therapies. Health Aff. 2023;42(11):1532–40.
?
Author of the newsletter:
Kurt R. Müller, PhD, MSc, BBA
Principal and Managing Director
pharmaLevers GmbH
Download Newsletter: https://www.pharmalevers.com/news---downloads.html
?
Adviser and Board Chair at Biointelect, Sydney Australia
6 个月Thanks for posting this excellent summary of uncertainty in HTA and valuation of medical technologies. From observing HTA practices for many years it is clear that certainty has a value when it comes to pricing and reimbursement (when linked to HTA). The call from industry to widen the dimensions of value for HTA purposes needs to keep uncertainty in mind. Considering productivity or care givers impacts ( for example) may be worthy, but is fraught with uncertainty. This is a factor in the reluctance of many payers to attempt to include such factors in economic evaluations. That said, it also underscores the importance of quality consideration of patient and carer perspectives, separate to quantitative attempts to broaden value estimates. These comments are my own and not attributable to Biointelect.