It’s that time of year where we’re busy in the final quarter of the year. In 2018, we have witnessed a fundamental change in the concept of value, going far beyond pharmacological properties and clinical effects, to not only to include patient value, quality of life and patient management, but also to integrate systems and societal value dimensions more broadly.Where are we in our journey towards the new frontier in the ‘paying for value’ discussion in the US?
We decided to initiate a 15-part series on our blog, where our US access experts take us through the shifting landscape for innovative contracting. Come join us as we explore a new world where quality benchmarks and patient outcomes performance define reimbursement and risk, and where the ability to translate value from clinical trial results into the messy real world of clinical practice becomes the currency of market access success. We’d love to get your feedback on our thoughts below, come back every Wednesday and Friday for a new edition.
A Six-Stage-Journey to the Successful Agreement
Choose Simple Yet Specific Outcomes, Time Horizon and Performance References
Against the background of our relevant payer contracting experience, we have found that the pursuit of a systematic six-stage-process can boost the chances of achieving a successful OBA. In this chapter we will illustrate each stage with concrete business applications and examples. The experiences are based on practitioners’ insights and abstracted from our insights on the implementation of recent OBAs –some disclosed, most of them kept out of the public domain.
For anyone considering the pursuit OBAs, it is fundamentally important to be clear on the exact rationale behind the approach. As we have argued earlier, OBAs are an effective tool to manage uncertainty, but as such they are not required for just any product. Let’s revisit three typical situations where OBAs are particularly relevant:
- When there is significant uncertainty around a meaningful clinical benefit in the real-life
- When there is significant concern around the potential economic impact
- When there is significant uncertainty around the ability of the product to penetrate the market.
Identifying these situations is key, as it will provide the source for the internal support in your organization but will also be the foundation of a continuous alignment with your counterparts, making sure there is a shared interest in seeing the agreement come to fruition. Figure 16 offers a summary of core interest for payers and the manufacturers to implement an OBA in each of these situations.
These situations can be the result of different root causes. For example, the uncertainty on real-life clinical benefits can arise from limited data collected in the pivotal studies (e.g., accelerated approvals or rare disease products).
It can also be triggered by a difference in expectations between regulatory agencies and payers for what the outcomes of interest should be (e.g., use of surrogate endpoints for approval). Additionally, the patient characteristics and conditions of use can often differ significantly from those in the clinical studies and can potentially lead to poorer or better effectiveness and safety. The uncertainty on the economic impact can be a result of the uncertainty on the outcome (e.g., reduction in myocardial infarctions for cardiovascular products), but also more simply because of the lack of robust long-term data (e.g., reduction in liver transplant for HCV).
Another common cause is the high volatility in the case of rare diseases, where treatments typically target a limited number of patients, but with a high unit price. Finally, the uncertainty on market penetration is often the result of either two similar products entering
the market simultaneously (e.g., anti PCSK9 antibodies), a late entrant position with limited clinical differentiation and/ or a highly competitive environment (e.g., diabetes market). While the specific root causes are not critical to initially decide on whether to pursue an OBA, their identification is paramount to ensure the design and implementation of the OBA will be tailored to the specific situation at hand.
Once you have gathered clarity of purpose and the confidence that it might be of benefit to explore an OBA, the question
becomes “how to go about it”. What we proceed with in this chapter are practical suggestions that can guide you in the design and
implementation of an OBA that is robust and set up for success.
The first decision to be made in the design of an OBA is the choice of outcome against which performance and payments will be indexed. Manufacturers and payers often rely on the primary endpoint of the pivotal clinical study. Still, a few considerations need to be taken into account before jumping to that conclusion. First, the endpoint has to be relevant from a payer perspective. This relevance can be driven by significant population health benefits, significant quality of life improvements for the patients, or the promise of healthcare cost reductions. Second, the partners have to make sure that the outcome will have enough specificity to ensure the observed performance can be attributed to the treatment without any doubt. For example, in oncology, disease-specific mortality should be preferred to overall mortality and for cardiovascular or respiratory conditions, disease-related hospitalizations (e.g., myocardial
infarction- or stroke-related, asthma exacerbation-related) is a better choice than overall hospitalizations. Third, the selected outcome has to be measurable with reasonable effort, so that the cost of implementing the OBA does not become a significant roadblock. The typical data sources include health insurers’ claims data, readily available electronic health records, and dedicated data collection through a targeted ad-hoc study or registry. While simplicity is often an important driver, it is interesting to note that some contracts have been successfully implemented with relatively sophisticated outcomes and measures. One example is the agreement between Genentech and Priority Health for Avastin (bevacizumab) in first line treatment of non-small-cell lung cancer (NSCLC). It was based on PFS, which was measured through EHR data acquired primarily through a third party exchange platform, completed with ad-hoc direct request to the provider when needed (see Section 4 for further discussion about measure and evaluation of the outcome).
Once the outcome has been selected, the partners need to define specifically on what basis the payments will be triggered. For this a time horizon must be set, potentially along with a reference for population-level outcomes. While the time horizon must remain reasonably
short (typically within 1-2 years), multiple options exist and should be thought through carefully. For patient-level outcomes, a minimum duration of treatment can be included (e.g., cancerspecific deaths arising after at least 3 months on treatment). A maximum duration can also be included but is less common. For population-level outcomes a specific duration of treatment is typically selected (e.g., average LDL-C level after 1 year on treatment in the health plan population). Additionally, a reference has to be provided to determine whether or not the outcomes are met. Oftentimes the reference is the outcome observed in the clinical trial, but there are other options such as the
possible interest in using a comparator treatment in the plan population. The latter can be particularly relevant when there is uncertainty around the relative effectiveness of the new treatment vs. the standard of care in real-life. Another important situation is the case of combined interventions (drug combinations or drug/disease management program). In that case the reference could potentially be the outcome observed in patients receiving only one of the two interventions.
2. n=213, Lazard (2017): The Global Healthcare Leaders Study:
3. UnitedHealthcare (2018). 2nd Annual Value-Based Care
Report. Retrieved from: https://www.uhc.com/content/dam/