This appeared a little while ago:
The HIT Approach to Big Data
MAR 1, 2013
Like "The Cloud" last year or "Mobile Apps" the year before, it's the I.T. catchphrase that's considered so big it's deemed worthy of double capitalization. Computers are capturing stray scraps of information on everyone's medical conditions, shopping habits, driving records, and weekend partying patterns; data architects in every business are struggling with how to put it all together to answer big questions.
No business has bigger questions than health care, which is being pressured as never before to provide better care to more people at lower cost.
But what the heck is Big Data? What makes it different from the small data that populates spreadsheets on so many departmental desktop PCs? "Volume, velocity, variety," says Elizabeth McGlynn, director of the Kaiser Permanente Center for Effectiveness and Safety Research. Kaiser, with 9 million members in eight regions, has the volume: 30 petabytes of patient data, which McGlynn says is more than three times the amount of digitized storage at the Library of Congress.
Velocity is the speed at which the data accumulates-very quickly in the case of a hospital, which adds reams of test results, images, vital signs, and clinician notes every day.
But McGlynn says the third defining quality of Big Data-variety-is the one most people overlook.
"There's not only the data we create, but what's on social media sites, or data about people's shopping or driving habits, what's happening demographically in a given neighborhood," McGlynn says. For example, hospitals trying to reduce their readmission rates might want to know what social support networks are available in the patient's community. Maybe the neighborhood block association has a Facebook page where neighbors can check in on each other or volunteer to bring dinner to a patient who's been discharged. Combining all the available information can create a picture of which patients are at greatest risk for readmission and what interventions are most effective at keeping them healthy and out of the hospital.
As usual, health care is playing catch-up in the Big Data game. Brad Putnam, executive director of HealthShare Montana, a growing health information exchange, came from the financial industry and says banks were in the dark about their customers up until about 10 years ago. "They had all their information on slave dummy terminals, and they'd send out a survey occasionally and think that they were giving great service," he says. Once banks started tracking how customers actually behaved, they saw a gap between the services offered and the services needed. That's why today you can deposit checks via your smartphone and get pinged when a stock hits your desired price point. "It was a painful shift, but now people can actively manage their financial life instead of reacting when the monthly statement comes," Putnam says. "When we're able to look at patient populations and measure how well we're doing, we can create benchmarks and help patients change their behavior. That's when it gets fun and fascinating."
The average hospital I.T. department may feel it's drowning in data already and is not inclined to deal with more. But here are three Big Data areas to watch.
Read, at length, about the three areas to watch here:
I think some of these will take a while to get into productive delivery but clearly they will be important. Important reading.
David.
No comments:
Post a Comment