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How Data Science Is Transforming Health Care by Julia Steele, Tim O'Reilly, Mike Loukides, Colin Hill

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Chapter 2. Making Health Care More Effective

What, specifically, does data allow us to do that we couldn’t do before? For the past 60 or so years of medical history, we’ve treated patients as some sort of an average. A doctor would diagnose a condition and recommend a treatment based on what worked for most people, as reflected in large clinical studies. Over the years, we’ve become more sophisticated about what that average patient means, but that same statistical approach didn’t allow for differences between patients. A treatment was deemed effective or ineffective, safe or unsafe, based on double-blind studies that rarely took into account the differences between patients. With the data that’s now available, we can go much further. The exceptions to this are relatively recent and have been dominated by cancer treatments, the first being Herceptin for breast cancer in women who over-express the Her2 receptor. With the data that’s now available, we can go much further for a broad range of diseases and interventions that are not just drugs but include surgery, disease management programs, medical devices, patient adherence, and care delivery.

For a long time, we thought that Tamoxifen was roughly 80% effective for breast cancer patients. But now we know much more: we know that it’s 100% effective in 70% to 80% of the patients, and ineffective in the rest. That’s not word games, because we can now use genetic markers to tell whether it’s likely to be effective or ineffective for any ...

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