Wednesday, October 14, 2015

My Talk at PMC/BIO Solution Summit for Personalized Medicine (October 14, 2015)

On October 14, 2015, I had the privilege of being invited to give the morning keynote address at the 2nd Annual Personalized Medicine Solution Summit, held in Washington.   (The meeting's agenda is here).

The deck is here as PowerPoint, and here as PDF.  Details after the break.

The deck was designed to support a live talk rather than stand-alone, but the themes are:

  • It's not your father's "Coverage - Coding - Payment" anymore.   
    • Coding for molecular tests has gotten drastically more complex in the last 3 years and may continue to do so.  
    • Regarding payment, the era of the line item fee schedule is dying fast, with complex bundling, capitation, and mark-to-market pricing along with narrow plan networks making it difficult to be a start-up lab.   
    • Regarding coverage, its no longer the decision of a medical director or two, but a complex world of national and international technology assessments, guideline endorsements, and other factors.
    • Market survival requires more agility and savvy than ever.
  • I use the analogy that we used to think of product introduction as tweaking a few little variable regions in the health system, like your new product's CPT code, while everything else was fixed.  BUT: Today, so many parts of the health system are changing around our heads:
    • Bundling, health system consolidation, labile coding systems, high out of network barriers, ACOs, changes at FDA, complex tech assessments, aggressive payer behavior, new OIG practices, and new horizons for social media and patient engagement.  All of these are changing at once.
  • There are some surprising parallels between dHealth and Personalized Medicine.
    • Both are incredibly broad fields
      • Personalized Medicine: From NIPT testing to lung cancer gene panels, from hereditary risk to drugs like Provenge
      • dHealth: From EHR's to mobile apps to big data to digital transceivers in pills
    • Both have evidence challenges.
      • Too familiar to mention in diagnostics.
      • In dHealth, see the GE-financed startup Evidation, aiming to create evidence platforms in dHealth; see also the SF startup Omada and its evidence plan for impact on diabetes.
    • Both have payment challenges.
      • Too familiar to mention in diagnostics.
      • "Payment is our biggest challenge in dHealth," according to Bottorff at GE Ventures.
    • Both have FDA issues.
      • LDTs at FDA and on the Hill.   Mobile app, decision support, and other dHealth issues at FDA.
    • Both fields are flooded with conferences.  I think if you track both personalized medicine and dHealth, you could attend a conference somewhere every day of the year.
    • Integration is seen as key: both fields have to move from "diagnostics" or "apps" to integration in healthcare.   
  • I discussed themes emerging from two recent books, The Silo Effect (by Gillian Tett) and The Culture Map (by Erin Meyer).
    • Personalized medicine is a diverse and highly fragmented industry, from Advamed to Pharma, from Myriad and Genomic Health to Academic centers, from local doctors decisions to the President's PMI initiative.  
    • Erin Meyer discussed the sharp differences among different countries in a book on business culture.   This is also true of the many diverse players in such different silos.  This leads to frequent communications challenges where people who think very differently process the same documents in very different ways.
  •  Coverage changes are really happening, discussing the CY2015 coverage for gene panel advanced lung cancer tests at Aetna, United, and 3 Medicare contractors.
    • All the policies are somewhat different!
    • Two of them - United and MolDX - required much more elaborate validation than CLIA.  NY State in the case of United; an elaborate analytical test assessment submission in the case of MoLDX.  
  • In closing, I showed a graphic I have in a number of forums, in which the vertical axis is "Cost Savings" and the horizontal access is "Higher Provider Financial Risk."  American graphs invariable show an arrow pointing to the far right top corner.   
    • Need this be so?  Why view the ideal as the top right corner?  
    • Isn't the best spot as close as we can get (with our best systems and skills) to the top left instead?  Wouldn't personalized medicine (correct diagnostics and clear therapeutic choices) help us move to the upper left on such a graph.

Note: Deck updated after the talk to include Aetna's 6/2015 policy on 5-50 gene panels in lung cancer.