Personalized Medicine: Back to the Future

Personalized Medicine

  1. The type of sing molecular analysis to achieve optimum medical outcomes in the
    management of a patient’s disease or disease predisposition,
  2. Right treatment for the right patient at the right time.

As I have mentioned in several of my posts, I have been working on a
couple of health care finance reform initiatives over the last six
months. After banging away now for awhile, I am starting to see some
emerging ideas that are starting to bring out that old revolutionary
feeling of doing something that can have an industry changing impact.
The opportunity lies in the ongoing pace of innovation, with new forms
of health care delivery, with new models of health care financing, and
that fact that eh American public and politicians are slowly waking up
to the fact that our health care system is headed toward radical surgery (not the cosmetic kind).

So lets start this out by talking about the personalization of medicine.
This is typically thought of in a genetic sense, wherein people are
customizing medications and therapies based on your individual genetic
profile. Said in other words, the “Right treatment for the right patient at the right time”.
However, most consumers already assume Right/Right/Right is happening,
and more likely consider personalized medicine as a type of practice
delivery style. This is where the physician knows the patient
intimately, their social and demographic context, and the correct
diagnostic or therapeutic approach given the patient’s preferences that
have been learned throughout the relationship. The only physician I
have ever had whom I had this type of relationship with was Dr. Richard Jones who took care of me from age 6-21 (when the front office lady finally told me that I “really should find another doctor“).

Dr. J, as he was affectionately called, had a personal interest in our family. Not only did I play football with his son throughout my
school years, but he was always available to to see us at a moments
notice. He was larger than life in our home – he expertly took care of
coughs, earaches, nosebleeds, annual physicals, immunizations,
concussions, and nearly every other ailment we could bring to him`. He
was an excellent diagnostician, compassionate clinician, and very
efficient with his time and practice. As our team physician, I got to
know him as a second coach, a counselor, and someone who could console
in times of defeat and share the joy of championships. In fact, more
than any single factor, Dr. J influenced me to go into medicine because
of the significant impact that he had in my life. I looked up to him as
a role model, as an advisor, and as a friend. The relationship was
time-tested, absolutely trusted, and he represented someone and
something that I aspired to be.

However, that was not the world that I would find years later when
going to medical school. The late nineties represented the first major
backlashes against both nationalization of health (aka “HIllaryCare
v1.0″) as well as the oppressive managed care regimes. The physicians
that trained me and my classmates were angry, bitter, decrying the loss
of the “golden era”, and just plain burned out. The Dr. J’s of the
world were being forced onto a 7-10 minute treadmill, procedure
focused, and RUC enhanced schema
that perverted the primary care practice style that has been shown to
increase health care value. The entire E&M coding concept, the fee
for service, “do more get paid more” delivery model supported by RUC
reimbursement methods (and its 24 out of 29 specialist committee
members) has led to a dramatic DECREASE in VALUE (outcomes/price) by dramatically driving up the “price” part of the equation. In addition to driving up price, (which was initially combatted and later retracted through the managed care “spasm”)
the problem has been that even with all the increasing costs there has
been very little change the overall health outcomes. Research by Wennberg, and books like Overtreated and Crisis of Abundance effectively make the case against the specialist and procedure intensive “Premium Medicine” currently practiced in America.

But all that is beginning to change. Just as data drives discovery,
medical evidence can and should drive medical practice. The evidence is
showing that our current cultural expectations, third party payment misincentive system, and malpractice litigation
environment are creating the perfect storm for healthcare reform. The
winds of revolution are being buoyed up by the pioneers of health care
delivery reform, and a return to when becoming a primary care provider
delivering true health care (preventive care and wellness) versus
“disease care” (what is currently practiced) is actually cool. Its the
“going green”, renewable wave as applied to health care. I have
documented the first wave of hip new doctors, now better equiped through technology to deliver highly personalized care (personal
health records, predictive practice analytics, and evidence based
treatment sensitive to individual cultural, demographic, and contextual
) who are reinvigorating the entire field of primary care which has unfortunately languished for decades (not for a shortage of solid physicians!). When added alongside payment reform (initially beginning as cash payment for services), and ultimately the realignment of incentives (through market forces supported by an appropriate regulatory environment) and reassignment of work tasks (appropriate utilization of physicians and other trained healthcare providers (RN’s, NP’s, etc), primary care has an opportunity to survive in a modified form.

So we are back to where we started 50 years ago. Trusted primary
care physicians using technology to delivery highly personalized and
effective medicine that their patients value and are willing to pay for
– now that’s a future Dr. J could be proud of.

Scott Shreeve is a physician and entrepeneur based in Laguna
Beach, California. After a long career in medicine, Scott founded the
open source electronic medical record company MedSphere. He currently
serves as entrepreneur in residence at Lemhi Ventures. If you enjoyed
this piece you may also enjoy his earlier piece examining the potential
impact of Long Tail economic theory on the healthcare industry. Scott is a frequent contributor to both THCB and the Health 2.0 Blog.

He blogs regularly at CrossOver Health.   

6 replies »

  1. It is the primary goal of the Department of Medicine to ensure that every possible effort is directed to fulfill its role in meeting the mission of the National Guard Health Affairs in providing, you can found it in this file

  2. When Doc sent Morty back to the future in a deLorean, he forgot more than just the law of physics… he forgot that its already been done !
    MYCIN: http://en.wikipedia.org/wiki/Mycin
    Statistical models outperformed Stanford faculty at 69% back in the 70s. Reasons cited for lack of implementation was hardware. In the age of mobile computing or supercomputers that can be built for a couple of thousand dollars with off the shelf components, what we need is a webserver with some really hardcore scripts (think Adam Bosworth new startup Keas) that can classify disease states better than human diagnosis. Statistical models can be created for the top ten diseases. They can optimize for diagnosis based on the cheapest available tests OR more advanced imagine or marker data, and it can tell you the accuracy of a classification base on data available.
    Consider the common scenario of being un/underinsured with high blood pressure. Rather than dealing with the inefficiency of people, simply get lab test run for $100 http://online.wsj.com/public/article_print/SB115076935218484812.html
    Then have test analyzed by a statistical model that outperforms a human. Extend this to the top ten diseases- from diabetes to heart arrythmia… now that would be a disruptive business model!
    Finally, for those of you are interested in yet another engineering milestone, last week machine learning defeats human in Go.
    Ultimately, would I want to sit back with the family Doc, marty, and talk about flux capacitors over a couple of beers. Sure, but not as a beholden patient made to wait hours contemplating the similarities between medieval trade guilds and 20/21st century medical licensing regimes. Besides, any statistical model could easily incorporate my psychological profile, remember my favorite color and song, and create a better user experience than a licensed human. (see articles on Halo3 programming team hiring a pyschologist to analyze players to create a better game)
    -i wish i was born in the future !

  3. Take a look at Interleukin Genetics, Inc. They have been on point with personalized medicine. Why have the managed care companies embraced this?

  4. I could not agree more with Scott’s focus on the important role a consistent primary care physician can play in enabling an individual to stay healthy throughout their life. It is promising to see individual physicians and entrepreneurs push against the system we know today to help facilitate change.
    It really does feel as if the time is ripe for change and hopefully once again the United States can become a leader in healthcare.

  5. Me too! That is, our family physician when I was a kid, the late Dr. Alexander Smith of Rochester, NH, actually knew us as individuals and a family.
    In my much more recent experience of a never-diagnosed disease, I experienced eleven years of shuttling myself around from specialist to specialist, with my sister and I doing all the research, to finally end up too fragile to leave the house as of the last four years and therefore without access to relevant medical care.
    When I think of the personalized care I knew as a child and the “care” I’ve experienced as an adult, it feels like I must have grown up overseas, in some different country.

  6. In the case of personalized cancer medicine, significant hurdles do need to be overcome to help physicians tailor treatments to individuals and their disease.
    Uncovering the genetic differences that determine how a person responds to a drug, and developing tests, or biomarkers, for those differences, is proving more challenging than initially hoped. As a result, cancer patients are still being prescribed medicines on a trial-and-error basis, and adverse drug reactions remain a major cause of injury and hospitalizations.
    In the new paradigm of requiring a companion diagnostic as a condition for approval of new targeted therapies, the pressure is so great that the companion diagnostics they’ve approved often have been mostly or totally ineffective at identifying clinical responders (durable and otherwise) to the various therapies.
    If you find one or more implicated genes in a patient’s tumor cells, how do you know if they are functional? Is the encoded protein actually produced? If the protein is produced, is it functional? If the protein is functional, how is it interacting with other functional proteins in the cell?
    All cells exist in a state of dynamic tension in which several internal and external forces work with and against each other. Just detecting an amplified or deleted gene won’t tell you anything about protein interactions. Are you sure that you’ve identified every single gene that might influence sensitivity or resistance to a certain class of drug?
    Assuming you resolve all of the preceeding issues, you’ll never be able to distinguish between susceptibility of the cell to different drugs in the same class. Nor can you tell anything about susceptibility to drug combinations. And what about external facts such as drug uptake into the cell?
    More thought “outside the box” needs to implemented before substantial realization of “personalized” cancer medicine.