Los Angeles, June 3, 2019 - Members of the Lydion Research Alliance including Jennifer Hinkel, MSc, Rahul Lalmalani, Sirtaj Singh Brar, and Arka Ray presented their work on using a blockchain-based approach to the management and adjudication of oncology outcomes-based agreements at the annual meeting of the American Society for Clinical Oncology (ASCO), one of the largest medical conferences in the world with over 42,000 attendees, in Chicago, IL.
The published abstract described the distributed software application, built using the Lydion Data Economic Operating System (Lydion DEOS), and the process to model the adjudication of a theoretical contract comparing fee-for-service Medicare reimbursement to an outcomes-based reimbursement paradigm for bevacizumab (a commonly used anti-cancer biologic agent) in the treatment of non-small cell lung cancer (NSCLC), one of the most prevalent cancer diagnoses in the United States.
“Having worked on behalf of numerous oncology drug manufacturers on market access, health economics, and innovative pricing options, particularly for drugs that cost potentially hundreds of thousands of dollars a year, I’m excited by the transformative potential of outcomes-based agreements to expand broad access to novel treatments while giving patients and insurance companies a discount or refund if the drug doesn’t work for that patient as expected. While these agreements are of great interest to pharma, insurers, and others, they have historically been difficult and expensive to implement and adjudicate; our method attempts to solve for these problems and greatly reduce the barriers to implementing outcomes-based, value-based, and other innovative contracting methods for pharmaceuticals using a Data Economics-based approach,” said Jennifer Hinkel, MSc, the lead author and a member of the Lydion Research Alliance, who is also a Senior Partner in life sciences consulting and has held management roles at Roche, Genentech, and National Comprehensive Cancer Network.
The published abstract can be found online here. The text of the abstract follows.
Modeling an oncology outcomes-based contract using a blockchain database approach: Cost and technology considerations.
Jennifer M. Hinkel, Arka Ray, Sirtaj Brar, Rahul Lalmalani
Background: Cost of care is an ongoing concern for all oncology stakeholders. Outcomes Based or Risk Sharing contracts are increasingly discussed, but difficult and costly to implement. The literature notes barriers of outcomes definition, reliable data sources, and technology enablement. The authors sought to design and test software that could enable faster, lower-cost, and auditable administration of such contracts.
Methods: The authors developed software using blockchain databases and transactional proof of work to simulate such a contract and to compare the financial result to usual fee-for-service reimbursement (FFSR). The software processed a synthesized Medicare claims dataset and Average Sales Price (ASP) data from 2008-2010, looking for use of the Bevacizumab(BV)/Carboplatin/Paclitaxel(CP) regimen in non-small cell lung cancer (NSCLC). The contract hypothesized a scenario that offered payers a discount for “underperforming” BV doses (defined as doses given to a patient with < 9 mo. BV duration) and required a bonus payment for “overperforming” BV doses (defined as doses given to a patient with > 14 mo. BV duration). These parameters were selected based on survival data supporting the 2007 FDA approval of BV/CP in 1L tx of advanced nonsquamous NSCLC.
Results: The software successfully processed the claims dataset and projected financial results (additional/saved cost) to the payer in this hypothetical contract compared to FFSR. The software also enabled comparison of different hypothetical contracts, inclusion/exclusion rules for claims, and discount structures. The software accurately categorized doses according to the defined logic.
Conclusions: Outcomes based contracts have potential for better aligning oncology reimbursement with meaningful results, particularly for costly therapeutics and where patient response or outcome is difficult to predict. While such agreements are recognized as difficult to implement, a software platform that facilitates efficient and scalable design, simulation, and implementation of such agreements, under constraints of real world data availability and sharing, may advance their adoption.
About the Lydion Research Alliance:
The Lydion Research Alliance is a consortium of scientists, engineers, economists, technologists, artists, and futurists dedicated to the advancement of the scientific field of Data Economics and the commercialization of Data Economic technologies.
About the Lydion DEOS :
The Lydion® Data Economics Operating System is the Operating System for Web3.
The Lydion® DEOS is a middleware engine used to develop distributed,decentralized applications and application platforms. By capturing energy spent in completing real-world work, The Lydion® DEOS mints digital assets called Lydions that can be utilized, shared, and transacted using secure, private Lydion Data Vaults and Networks (DENETs).
Current Lydion Engine-based applications target a combined $350B addressable market across the Health Sciences, Agriculture, Climate, Industrials, Fintech, Personal Data, Gaming, and Education sectors.