Will Feeding Watson $3 Billion Worth Of Healthcare Payment Data Improve Its Decisions? So ask Ross Kopell and Frank Meissner, MD, at The Health Care Blog. It's tempting to reply off the bat: Hey, it's worth a shot. What have you got to lose?
IBM just paid $2.6 billion for Truven Health Analytics, following other acquisitions in the field. Watson can now chow down on data for around 300 million patients. The authors write a fascinating and detailed account of why current patient data is lousy and unreliable. IBM's project may be an expensive exercise in garbage in, garbage out. Yet the authors conclude just like my gut reaction to their headline: Why not try?
They say: “All data are abstractions and the 'bad data' also reflect a reality. We may not like it, but it's there. Thus, these data will predict things within this reality that we don't care about (e.g., more redheads are slightly more likely to have heart attacks on Thursdays than would be expected by chance.) But, we can't rule out the possibility that Watson will predict something we do care about. Science is full of serendipity, Watson's logical crunching may lead to some discoveries that are useful.”
This is truly interesting. We normally dismiss analyses made with bad data. But Kopell and Meissner are saying bad data reflects a reality. So Watson may uncover systematic distortions in our current data sets. This would help to reveal – and perhaps prioritize – the areas where data standards are most urgently needed, as well as bringing dysfunctional processes and relationships into focus. In other words, “Doctor” Watson's first act of healing could apply to the healthcare data landscape itself. Healthcare Blog
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