AI Summary of my 30 minute, 4000 word talk at TRICON

 This is an AI summary (ChatGPT) of my 4000 word, 30 minute talk at the diagnostics TRICON conference in San Diego on March 8, 2023.

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Part 1 / 2000 words        Bruce Quinn / TRICON 

The speaker gave a talk on healthcare innovation and policy at UCLA, where he discussed three books he read recently. One book was about the history of insulin and the challenges and competition in its development, highlighting the complexity of the intersection between science, clinical practice, and industry. Another book discussed the unexpected policy directions that led to the explosion in the German chemical industry in the late 1800s. The third book was about the different ecosystems that make up healthcare and the need for better integration between them to support innovation. The speaker also shared examples of exciting advancements in healthcare, such as AI's ability to detect breast cancer and the Integrated Diagnostics Center at MGH, which significantly reduces the time from cancer diagnosis to treatment. 

The speaker then discussed the differences in how payers view diagnostics compared to drugs and devices, noting that clinical utility is often a point of contention. However, there have been recent studies showing the potential benefits of diagnostics, such as a randomized controlled trial in pharmacogenetics that found a 10% reduction in adverse events. Lastly, the speaker shared a modeling study on the impact of liquid biopsy on cancer detection and treatment, which showed a potential reduction in stage four cancers, but an overall increase in cost due to diagnostic testing.

Continuing in part 2 / 2000 words / 

The speaker discusses the importance of understanding the risk-benefit ratio of diagnostic tests and how to communicate this information effectively. They categorize tests into three categories: standard of care, recovery recovery, and novel tests. Standard of care tests are well-established and have a clear use case and risk-benefit profile. Recovery recovery tests are novel but have a well-defined use case, such as minimal residual disease diagnostics. Novel tests are in a new space and require data to reduce uncertainty about their risk-benefit profile, such as screening for liver cancer.

The speaker also discusses two tools that can be helpful in communicating the value of a diagnostic test: the Cheers template and the CDC 44 questions. The Cheers template is a detailed template that walks through every step of the pharmacoeconomic study and can be used as a checklist. The CDC 44 questions provide a framework for thinking about the value of a test and can help develop a logic chain.

The speaker also discusses the TCT saga, which is transitional coverage or emerging technology coverage. This is embedded in other big things and other big wheels that are turning at CMS. The Trump administration rolled out MCI T Medicare coverage for innovative technologies, which provided four years of guaranteed coverage for FDA pathway breakthrough devices. The Biden administration froze and then rescinded the rule but has promised to release something new. As of now, the rulemaking has been deferred until sometime in 2023, and it is expected to have a lot to do with national coverage decisions and conditional coverage.

The speaker also discusses the MedCAC on CED and how they focused only on the process for CPD and not the goals or purpose of CPD. They also discuss how CMS has done CED both well and poorly in the past.

In closing, the speaker discusses their opinion that some of the problems people worried about with breakthrough coverage were self-correcting and that understanding the risk-benefit ratio of a test is crucial for effective communication.