Global trends in demographics, politics, and public health are ushering in an economic moment of truth for the healthcare and life sciences (HCLS) industry. Last year, biotechnology R&D expenditures for discovering and developing new therapies outpaced industry revenue growth by a factor of ten. This increase in development costs is pushing life sciences companies to price new therapies at a premium, which then clashes with public policies focused on decreasing the total cost of care. 

One market mechanism to reconcile the divergence between industry cost structures and affordability regulation is the value-based agreement (VBA), in which healthcare providers and pharmaceutical manufacturers receive payment tied to successful patient outcomes. In the United States, the Biden administration has proposed continuing the Centers of Medicare & Medicaid Services’ progress towards value- or outcome-based payments. In a recent report sponsored by AstraZeneca, such VBAs between payers and biopharmaceutical manufacturers are estimated to potentially generate $36 billion in healthcare cost savings in the United States alone. In aging societies with public systems under acute budgetary strain—such as Europe and Japan—adoption of value-based contracts has become widespread. 

VBAs are intended to align the incentives of payers, providers, and manufacturers to patient health, especially for personalized gene and immunotherapy treatments that can be both costly to develop and difficult to scale. In practice, the adoption of value-based care faces a number of challenges. These include defining an appropriate methodology used to measure outcomes, agreeing on the appropriate proportion of risk born by actors responsible for different steps in the delivery, and reimbursement of treatment. 

Above all, there is the challenge of securely collecting and analyzing the right data to prove which factors influence the outcome—and to what degree. Given the high number of cybersecurity breaches in the industry, this must be done with the highest levels of data security possible. In a study performed by The American Journal of Managed Care (AJMC), over 70% of manufacturers cited “data and evidence” as the most common reason for the failure of VBA negotiations. Similarly, payers have cited data collection and sharing as a common roadblock to implementing value-based contracts.  

On the other hand, successful VBA negotiations have often resulted when the necessary infrastructure for data collection, sharing, and analysis are in place. Brendan Shaw, senior lecturer at the University of New South Wales’ Pharmaceutical Management Unit, has observed that advancements in analytics and AI are starting to address traditional data collaboration challenges. In the same AJMC study, over 90% of manufacturers indicated that “necessary data collection and analysis capabilities” were a critical factor in successful VBA negotiation and implementation. This data includes real-world evidence, the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from analysis of real-world data including electronic health records, claims, product and disease registries, and patient-generated data from in-home-use settings, mobile devices, and wearables. Accordingly, both payers and manufacturers expect that new data sharing and analytical capabilities will unlock higher volumes of more sophisticated agreements. 

Shared access to real-world evidence based on data collected by payers, providers, and manufacturers is just the first step. The reality is that healthcare is delivered within the highly complex context of patient lifestyle habits. How we eat, exercise, work, rest, and so on all play a role in influencing outcomes. In order to more accurately understand the isolated influence of medical treatment on patient outcomes, the industry is in need of a radically different approach to data collection, analysis, and sharing.

Leading HCLS organizations are leveraging Snowflake’s Healthcare and Life Sciences Data Cloud for real-world evidence. To learn more, read our white paper, The Healthcare & Life Sciences Data Cloud for Real-World Evidence.

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