Healthcare IT's Achilles' Heel: Sensors 84
Nerval's Lobster writes "Tech publications and pundits alike have crowed about the benefits we're soon to collectively reap from healthcare analytics. In theory, sensors attached to our bodies (and appliances such as the fridge) will send a stream of health-related data — everything from calorie and footstep counts to blood pressure and sleep activity — to the cloud, which will analyze it for insight; doctors and other healthcare professionals will use that data to tailor treatments or advise changes in behavior and diet. But the sensors still leave a lot to be desired: 'smart bracelets' such as Nike's FuelBand and FitBit can prove poor judges of physical activity, and FitBit's associated app still requires you to manually input records of daily food intake (the FuelBand is also a poor judge of lower-body activity, such as running). FDA-approved ingestible sensors are still being researched, and it'd be hard to convince most people that swallowing one is in their best interests. Despite the hype about data's ability to improve peoples' health, we could be a long way from any sort of meaningful consumer technology that truly makes that happen."
data mongering (Score:2, Interesting)
And somewhere an NSA analyst is beating himself frantically thinking about the data collected when insurance companies require* everyone to wear one of these.
*With drastically reduced deductibles!
Wrong Context (Score:5, Interesting)
I think the author is looking at "Healthcare IT" through the wrong lens. The major advances over the next decade are going to come via "big data" (mind the buzzword) and analytics. For example, I was at an EMC presentation the other day and they were making the case for Greenplum (EMC'ized Hadoop / Map Reduce). One of the breakthroughs they were touting was cancer research. There was a woman who went through half a dozen cancer treatments that did not improve her condition. They were able to run models and simulations and ended up finding an off label drug that put the cancer into remission.
Prior to being able to simulate those complex drug interactions, they never would have been able to test an off label drug like that. Now the potential exists to research all sorts of combinations and treatments that would have been computationally impossible five years ago.
Somewhat less cool is the ability to use analytics to track treatment and billing data. The health care system is so inefficient that there is a lot of low hanging fruit there. It only starts showing up at larger scales, once the data sets get bigger. For example, hospitals cannot really correlate the effectiveness of specific treatments for specific conditions versus their peers at other hospitals. Yet with a big enough data set, statements along the lines of, "Last year, 50,000 people were treated for condition X by 50 different hospitals. Of those 50 hospitals, there were 16 different methodologies used. Of those 16, THIS 1 treatment was the most effective, based on these subsequent observations..."
Take a simple use case... the over prescription of antibiotics. With a decent data warehouse and some analytical tools, it will be possible to quickly zero in on cases where antibiotics were inappropriate prescribed. The same thing goes for everything else. "We noticed you are prescribing the brand name medication, when this generic drug is available, and 85% of your peer organizations are using the generic without any loss of efficiency in treatment."
As much as people dislike the government and feel that the Affordable Care Act is a mixed bag, I have a suspicion that when the government gets into really pinching pennies, they are going to drive down the cost of healthcare.