Connected Health Data Report

Gigaom published a new report earlier this week titled "The Internet of Things and the Future of Health Care." The Internet of Things is connected stuff — glucometers, TVs, thermostats, sensors, pedometers, RFID-tagged equipment, etc. The report mentions the "health IoT," a term I hadn’t heard that describes what we write about and think about with regard to connected health.

The report effectively outlines the case for connected devices in healthcare. It’s not revolutionary material, but it is well thought out with good case studies. I agree with the conclusion that connected health has potential. The 10-year horizon mentioned in the report can be seen as either pessimistic or optimistic depending on how long you’ve spent in the industry.

New data means more dimensions of a patient, which leads to more insights. Those insights can be be translated into actionable baby steps towards better health. Here’s what I got from the report.

  • Connected devices generate a lot of data.
  • Connected devices have mostly targeted fitness.
  • EHR data is stored in silos.
  • EHR data is limited in utility because it is episodic.
  • Data is just the first step. Algorithms and meaningful insights are the keys to unlocking the potential of connected health devices.
  • Data potential is that much greater when connected device data is combined with EHR data.
  • The big winners will be the integrators of all of this data. It remains to be seen who those winners will be.
  • Data security and privacy are going to be critical to success.
  • Personalized medicine has been overly focused on genomics.

Each of those bullets is a huge topic unto itself. Opinions vary widely when you start getting into the value and utility of mashing up EHR data with connected health data, driving people towards changing behaviors and getting healthier, ultimately reducing the cost of healthcare.

The most interesting aspect in the report is calling out connected health as having as much or more potential than genomics. Genomics to me is synonymous with personalized medicine, such as tailoring medications to your personal genetics. That’s awesome as long as you have insurance, have access to a provider, have your genes on file (whatever that is going to mean), and are adherent to your medications.

I’m not putting down the potential of genetics in healthcare and medicine, but concluding that connected health holds as much or more potential than genetics is framing the argument in an interesting way.

Our incredibly high healthcare costs are not all about healthcare as we think of it today. The issues are deeper, relating to socioeconomics, education, and environment.

Fixing healthcare is one thing. Making people healthier is another. Fixing healthcare means insuring more people, aligning incentives around quality instead of quantity, improving access, and making ED visits better than getting a new driver’s license. Making people healthier means giving them access to social services, schools, and healthy, affordable food.

I think of connected health in terms of improving the data of an individual and using that data to improve care, either through a provider or through self management. This report views connected health as a way to gain insights into the environmental, behavioral, and social context of individuals. Maybe this was an obvious conclusion, but I never framed connected health data in that way.

It makes sense to see this newly connected individual data as potentially more powerful than the data specifically collected by devices. Knowing that someone should take more steps in a day and then suggesting new walking routes home is one thing, but gaining knowledge that the person lives in a neighborhood without access to care or medications is another. Payers and providers already have some of this data based on demographics, but few of them use it.

Also interesting is that the interventions have little to do with traditional healthcare delivery. If you acknowledge that many of the problems with the health of US populations is based on factors outside the health system, then you have to question why we’re expecting the health system to fix them.

How much data valuable demographic data are we not using? If we start gathering more of it via devices and apps, who’s going to act on it?

TGphoto

Travis Good is an MD and co-founder of Catalyze. More about me.

  • lesterd1955

    Travis, you raise some great points here. Healthcare still seems to be very confused. On one hand, we have IBM’s Watson that is managing huge amounts of data to provide clinical decision making (good luck dealing with the regulatory hurdles!) and on the other hand the whole wearables space has completely disregarded the ridiculously complex healthcare system and is pumping out data at an incredibly fast rate. We don’t know the meaning, no clues on the accuracy, but the consumer is getting excited by it. And to your point it is disconnected from the information in the healthcare system. I think we have to start with a case study, maybe a disease, work things out there, and then see what pieces are translatable to other diseases.

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