It’s that time of year where we’re busy heading into 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?

Stage 4 Clarify Data Sources and Methods to Measure the Performance

While the contract design is a key step in the development of an OBA, it is important to keep in mind that your strategy will only be as good as its execution. Hence, it is critically important to think through where and how the performance will be measured, analyzed, and potentially adjudicated during the implementation phase of the OBA. Provider claims for the health plan are the simplest and most straightforward data to use to gauge a product’s performance in the context of an OBA. Still, it might lack granularity regarding the type of information collected, like in the oncology example cited above where the outcome of interest was PFS. In these instances, a complementary data collection is required either in a systematic approach or for a representative patient sample. The sampling approach can be considered in the case of a large patient population and for population level outcomes. When the patient population is more restricted as in the case of OBAs based on patient-level outcomes, systematic data capture is needed. This complementary data collection can rely on various sources and tools such as existing EHR data, laboratory testing provider databases or ad-hoc registries. While the initial setup of such a data collection platform can be burdensome and costly, it is important to note that there is a quick learning curve and economies of scale across OBAs and products. Regarding the interpretation of the data to determine the actual product performance, it is important to clearly define who will analyze the data: the health plan only, or the health plan and the manufacturer, or a third party? If it is the health plan only, will there be a double coding or validation process to ensure quality of the output? Manufacturers who receive summarized reports about performance from the health plan – which can keep overhead costs lower and be faster – face limitations when it comes to understanding the sources of outcome performance (which would require inclusion of de-identified patient level data). Arbitration would be required if disagreements arise.

Additionally, like for a clinical study a clear analysis plan should be devised, describing the inclusion/exclusion criteria used to select the patients in scope for the analysis, as well as how exactly the outcome will be analyzed. On the latter, multiple technical issues need to be addressed such as patients switching across plans, treatment adherence, crude vs. adjusted analysis if comparing two treatments for example. The analysis plan should also specify the frequency at which the performance will be assessed. While setting up a clear analysis plan upfront should limit the risks of discrepancies and contentions, it is still important to have a strategy in place for how these issues will be ultimately adjudicated. The two partners should agree on the resources (e.g., joint team, third party…), the timing, and the decision process they will follow to get to a resolution in case of disagreement on the performance and leave the door open to potential amendments of the analysis plan if needed. Finally, parties would be well advised to include provisions in their agreement regarding potential exceptional externalities (e.g., new treatment guidelines, discontinuation of a competitor treatment…) that could significantly affect the measure and lead to a renegotiation of the methods to assess the performance or even the whole OBA.