Here are a few of my takeaways (and thoughts) from yesterday at FutureMed 2013.
We are full of sh*t
Just as gene sequencing took off these past couple of years, we will soon see analysis of microbes break new ground. Companies like uBiome are mapping the microbiome (the sum total of microbes, their genes and the environment). I learnt during Larry Smarr's lecture that 90% of our cells and 99% of our genes aren't human (whatever human is) but microbes! Our gut alone harbors 100 trillion bacteria. Depending on what species are most dominant inside us determines our physiology. So we are indeed what we put into our mouth! Read this fascinating article on how Larry quantified himself to the extreme to take control of his health.
Watson is learning about cancer at Kettering and will go live by the end of the year
IBM's Watson is at Kettering devouring knowledge from millions of its encounters. Senior oncologists at the hospital are spending 50% of their time teaching Watson. By the end this year, it'll start assisting doctors with therapeutic options for cancer. Marty Kohn said that IBM has no decision yet on their business model for Watson. Would this be a big cloud or several mini-clouds? We don't know this yet.
An inflection every 50 years
Back in 1870, there was germ theory. In 1920, advances based on medications (example is penicillin). By 1970, medicine evolved into a science (evidence based). Fast forward to 2020 and we could possibly be working in a healthcare world that's driven primarily by data. These thoughts were from Daniel Riskin, MD whose company actively culls out data from EHRs and creates meaning out of it.
A machine is possibly better than 50% of MDs (who are below average)
Vinod Khosla reflected on insights that possibly stare at us in our face. The most uncomfortable of them was the fact that half of the doctors out there are below average and could possibly provide much better medicine with assistance from a machine.
Elegant visualization and avatars
Among several other things, John Mattison, MD from Kaiser talked about elegant visualization in the world of big data. As a case in point, a recent study generated 5 terabytes of data for every patient. To put this in context most of the world's data has been created in the past two years and is unstructured (Mary Kohn). A better way to make sense of such data would be to use for example heat maps to visualize what's going on. What if you combined such visualization and connected it with actionable outcomes using avatars? If your grandma heard from your avatar in your voice, would she be more willing to get active everyday?
4 predictions for health IT
Christopher Longhurst, MD made the following interesting predictions:
1) EMR vendor consolidation and increasing federal regulation will pose challenges to rapid innovation
2) Health IT focus will shift over the next 3-5 years from EMR implementation to analytics-enabled clinical decision support
3) Over the next 5-7 years, we will see a shift from "evidence-based practice" to "practice-based evidence" through the creation of national learning healthcare systems (could HIEs be those hubs?)
4) Personal health records will evolve into personal health advisors
Trusted recommendations at the right time change behavior
Julia Hu from Lark showed the new Lark. Their approach to development involved capturing and automating expert coaching and providing behavioral alerts to users at the right time. For example, if Lark noticed that you didn't sleep well last night, have been running around all day, are still in the office at 7PM and have been sitting for two straight hours then it knows you possibly need a push to de-stress for a few minutes.
New age of innovation
Here's 16-year old Jack Andraka's video where he's screaming away joyously when he became the grand prize winner at the Intel Science Fair last year. He developed a new way to detect pancreatic cancer and is talking to Quest and other labs to commercialize his method. He closed his presentation talking about how the Internet has no cognition of who you are, your age, your gender and so on but mainly about what you have to say.
More later.
