PRODUCTIVITY CONFIDENTIAL: DATA AND DOCTORS
Doctors and nurses have to remain productive under pressure. Their decisions are quite literally life-and-death, and quick access to patient data is vital to making informed decisions about patient needs. For years, that data was managed on pen and paper, but the recent revolution in healthcare data has fueled a technology-driven revolution in how healthcare providers do their jobs. On this episode of Productivity Confidential, we talk to Dr. Anil Jain, chief health information office of IBM’s Watson Health initiative, about how data is creating a brand new frontier of care from state-of-the-art hospitals to rural medical centers around the world.
HIGHLIGHTS FROM THE PODCAST:
I’m really interested in the fact that technology and data generation sort of caught up to each other and had this inflection point with each other. Now, what can the average healthcare provider, and then what can the average patients get from big data in healthcare? What’s going on behind the scenes? What’s something that happens when you go into hospital that you may not know is being driven by big data but actually is being helped along by this massive information and analysis infrastructure?
DR. ANIL JAIN:
For the most part, and I sort of talk to folks at cocktail parties about the fact that most of the time, the impact of big data on the average patient is sort of indirect. It’s invisible to the patient, and maybe in some cases it should be. So on the operational and administrative side, big data is being used to do comparisons and benchmarking and really trying to understand the patient’s journey, everything from their clinical journey all the way to how much, for example, should an episode of care reasonably cost, how much should a health system be reimbursed by a health plan who may or may not be an intermediary to the true payer of health like the employer.
So there’s a large amount of data that’s being crunched on a regular basis to sort of draw out some of these metrics, if you will, that are helping patients get better care whether they recognize that or not. And on the clinical side, which obviously as a clinician, I’m really excited about, but I’m also the most cautious about this area, patients can feel this directly when a provider for example, is able to prescribe a specific medication because large population studies show that that particular patient, given all their risk factors, would be better off with blood pressure A rather than blood pressure B.
And so this ability by using big data and creating a real world understanding of what happens to people when they’re on these different medications and these different therapeutic journeys, what might be the best for an individual given not just what the literature tells us, but also what patients like them might tell us.
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