Real-time data sharing critical to “Smart Aging” and collaborative health care

Posted on 25th February 2015 in health, Internet of Things, open data, SmartAging

It’s hard to describe to someone who hasn’t encountered the phenomenon first hand, but there’s something really exciting (and perhaps transformative) when data is shared rather than hoarded. When data becomes the focus of discussions, different perspectives reveal different aspects of the data that even the brightest person couldn’t discover working in isolation.

That transformative aspect is very exciting when it involves health care.

I’ve written before about the life-saving discoveries when doctors and data scientists from Toronto’s Hospital for Sick Children and IBM collaboratively analyzed data from newborns in the NICU and discovered early signs of infections that allowed them to begin treatment a day before there was any outward manifestation of the infection. Now, the always-informative SAP Innovation blog (I don’t just say that because they’re kind enough to reprint many of my posts: I find it an eclectic and consistently informative source of information on all things dealing with innovation!) has an interesting piece about how Dartmouth Hitchcock is sharing real-time data with patients considering knee-replacement surgery.

In some cases, that data leads patients to decide — sigh of relief — their condition doesn’t warrant surgery at this point, while it confirms the need for others.  In both cases, there’s a subtle but important shift in the doctor-patient relationship that’s at the heart of my proposed “Smart Aging” paradigm shift: away from the omnipotent doctor telling the patient what’s needed and instead empowering the patient to be an active partner in his or her care.

The key is using the data to predict outcomes:

“‘Prior to anyone ever getting surgery, we want to try to predict how they’re going to do,’ Dartmouth-Hitchcock orthopedic surgeon Michael Sparks said in an SAP video. ‘But we’ve never had that missing tool, which is real-time data.’

“D-H recently began using real-time data analytics and predictive technologies to help people suffering from chronic knee pain to choose wisely and improve their outcomes. ‘It is actually a partnership to help people get ‘through this,’ Sparks said. ‘And it’s the analysis of data that adds to their ability to make a decision.’”

For the first time, the patient’s choice really becomes informed consent.

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