Transparent and Relevant Evaluations of Value: An Active Role for Pharma

With the advent of health technology assessment (HTA) across much of the world, paralleled by the successes of the biopharma and medical device industry in developing and commercializing new drugs and devices, the onus is on the innovator to demonstrate the value of a new product. In many countries assessment of the value of healthcare technology is made at a national level by a single HTA agency on the basis of cost-effectiveness analyses. After 25 years the incremental cost-effectiveness ratio (ICER) that form the basis for the judgement of value remain essentially impenetrable to all but the academic health economist, the technical specialists who perform the analyses – in pharma that’s your HEOR team – and their equally technical counterparts within the HTA agencies.

Recently, the US has made a jumble of efforts to distill the complex world of pharmaceutical science to meet American demands for a definition of “value” with the end result being half-a-dozen “Value Frameworks” ranging from complex cost-effectiveness analysis to more user-friendly approaches that are at one-and-the-same-time similar and contradictory.  Given the decentralized decision-making environment in the US, cost-effectiveness analyses or any other analysis about value performed by different stakeholders have only relevance for decision-makers when there is total transparency and they have confidence in the analysis.

We argue that biopharma and the medical device industry should embrace the developments about value assessment in the US, and take a leading role in defining and demonstrating what can be considered credible and relevant cost-effectiveness studies, rather than opting for a passive approach where they just respond to evaluations reported by third parties and ultimately lose control of the discussion.

The challenges with quantifying value

Assessing the value of a medical technology is a matter of comparing its benefits, risks, and costs to available alternatives for a particular patient population. However, this is not easy to implement. There is frequently no single empirical study available that compares all relevant competing technologies regarding their attributes that define value. As an alternative, we rely on rather complex mathematical models to combine information from multiple studies and sources to quantify value, e.g. calculate the cost-effectiveness. The mathematical model describes the course of disease over time, and the impact of treatment on this trajectory is captured along with the incidence of adverse events, associated healthcare resource use, and costs. Historically, modeling the progression of a disease was the domain of the discipline of epidemiology, supported by healthcare professionals who treated the patients.  However, with the exception of only a handful of well regarded, much cited clinical predictive models in several common diseases e.g., Framingham for cardiovascular health and the Cardiff Model for diabetes, such modeling efforts have been dominated by product-specific cost-effectiveness models developed to define, describe and defend the value of a sponsor’s asset in discussions with clinical and methodological experts from country-specific HTA agencies. Historically there has not been much of an incentive to develop cost-effectiveness analysis or models relevant for the US setting. However, with the discussion about value becoming more prominent and an increased interest in formal quantification of value in the US, pharma now has a stronger interest to perform these kinds of US specific modeling studies and communicate their findings. The challenge though is the multitude of decision-makers in the US. Unlike in many other countries where it is sufficient that the analyses are convincing the national HTA agency, US-specific analyses need be understood and accepted by a multitude of decision-makers at the local level with different levels of expertise regarding cost-effectiveness analysis and value assessment.

What should pharma do?

As mentioned, communication of US-specific cost-effectiveness analyses or evaluations of the value of innovative interventions is becoming increasingly important. However, just publishing the findings in scientific peer-reviewed journals has limited relevance. Model-based cost-effectiveness evaluations are complex and the typical journal article does not provide sufficient information for readers to verify the analysis, thereby raising questions about its validity in the context of the perceived conflict of interest of the study sponsor. In addition, the typical healthcare provider or decision-maker reading the paper may not have sufficient expertise to judge the credibility of the evaluation and interpret the reported findings. Or they may discard the published analyses because it is perceived of questionable relevance given the differences of their local setting and context. Hence, pharma needs to do more than just publish a paper in order to be perceived as a credible party in the discussion about the value of their products (Figure 1).

Figure 1. Communication of US-specific cost-effectiveness evaluations by pharma - A transition to increase credibility and relevance

To overcome the perceived conflict of interest, pharma needs to improve the transparency of their cost-effectiveness evaluations.  Typically, there is no access to the model programming code for readers to verify a published cost-effectiveness analysis. Pharma should break with this practice. Releasing the model programming code to the public at time of publication demonstrates that they are serious about value assessment.

Several authors have outlined the benefits of a so-called open-source approach to cost-effectiveness analysis, but has only gained meaningful momentum in recent months.  Perhaps the tipping point for the recent shift is frustration with the number of Frameworks currently floating around the US, each with different advocates and detractors. An open-source approach to cost-effectiveness modeling effectively neutralizes challenge from third-parties who develop their own cost-effectiveness model and use this to develop a contrary perspective on the value of innovation – noting that the opinion may be more open to challenge when the underlying mathematics are transparent to all.

In its favor are the long-term ability of an open-source approach to generate broad agreement on how to characterize a disease mathematically and thus quantify the value that a novel treatment may offer.  This is a significant and long-awaited advance.  In our opinion perhaps the strongest arguments favoring adopting an open-source approach to cost-effectiveness modeling

However, just providing access to modeling code is not sufficient for transparency because the audience may not have the expertise to understand model programming code. Given the complexity of the typical cost-effectiveness model, it is important to make the model accessible as well.  By providing a web-based interface to interact with the model, the reader can “pressure test” the model by modifying assumptions and certain input values. In addition, the interactive interface allows a decision-maker or provider to tailor the evaluation to their local setting, for example by using specific information regarding the patient population and unit cost estimates. As a result assessment of value becomes more concrete, interesting, and relevant.

Now what …

For a biopharma executive pondering how to be an active participant in the discussion about value assessment in the US we offer the following:

Lead don’t follow – Take a proactive role in performing cost-effectiveness analysis of innovative treatments and communicate findings in way that is relevant and understandable for the different stakeholders in the US healthcare setting characterized by  decision-making at the local level.

Transparency builds trust – in parallel with the expected shift to release clinical trial data into the public domain (Ref), do the same for cost-effectiveness analysis.  In one step, defuse the criticism of a lack of transparency in how efficacy and safety from an RCT are assumed to translate to effectiveness and tolerability in routine practice, and thus value for patients, and take a bold step to enhance the trust between biopharma R&D innovators and the customers they serve.

Ross Maclean, M.D, Ph.D, is senior vice president and head of medical affairs at Precision Health Economics. Jeroen Jansen, Ph.D, is scientific advisor at Precision Xtract.