Next Best Action in Healthcare: Save & Improve Lives Through Applied Analytics

Big Data Evangelist, IBM

The human condition is an unfathomable mystery, a complex stew of biological, genetic, behavioral, cultural, environmental, psychological, and spiritual factors.

But fathom it we must. When our personal condition stumbles from wellness to illness, we will use any resources at our disposal, especially the full repertoire of modern healthcare, to restore it. When our health issue is congenital, we'll use explore all options that might help us live as close to a normal life as we can. At the very least, we want all the facts and diagnostic tools that might help us understand what's ailing us and what, if anything, we can do about it.

The next best action is always the one that keeps us in healthy homeostasis. The greatest mystery is how we can stay well, given all the circumstances of life that might push us over the edge. When illness strikes, the more mysterious its source is, the more critical the need for advanced healthcare analytics.

For humanity, the next best action is to fund and empower the medical researchers who shine analytic light into the most stubborn mysteries. Some medical conundrums are so deep-rooted and multidimensional that we need to drill into them with our most powerful big data analytics tools, as Mike Kearney recently discussed in his blog on a State University of New York (SUNY) Buffalo team's research into multiple sclerosis. This is the sort of problem that requires breakthrough discoveries from leading researchers who use powerful in-database analytics to explore every possible facet of the problem. As Steve Hamm discusses in his blog, SUNY Buffalo researchers have harnessed a computer cluster from IBM Netezza to answer analytical queries in minutes that used to used to take days.

For every healthcare institution, the next best action is to provide caregivers with the most effective big data analytical tools for diagnosing and treating the most critical maladies. The Mayo Clinic, for example, leverages IBM's Blue Gene computing architecture to link health records with clinical, genomic, and other data to customize treatment plans to each patient's unique condition. The clinic relies on data mining, pattern recognition, and custom algorithms to sift through myriad factors that shape interactions among diverse health variables.

For each of us individually, the next best action is always to stay the course on healthy habits and to find a steady source of authoritative answers to healthcare inquiries. Evidence-based medicine and clinical decision support are key to this scenario. That's where tools such as IBM Watson are pivotal. In the daily course of their jobs, physicians must be able to perform ad-hoc, real-time, natural-language searches across the breadth and complexity of human medical conditions. WellPoint, for example, is leveraging Watson to help caregivers search through a mind-boggling volume of medical literature at the speed of thought to expedite diagnoses while boosting confidence in their treatment plans.

The promise of technologies such as Watson is that they will, inexorably, shape how each of us navigates the confusing array of life choices that impact on our wellness. Think of the possibilities. What if you could receive a steady feed of personalized health recommendations through all the gadgets, appliances, applications, portals, and other platforms that power your life? What if, with privacy safeguards, you could correlate Watson-powered healthcare analytics with real-time streams of personal metrics fed from wearable devices?

Under those (not-too-futuristic) circumstances, you might be able to program your life to conform with auto-generated recommendations that are proven to be conducive to long life and robust health. Think of this as preventive healthcare maintenance, along the lines of what Erick Brethenoux discusses in his recent blogpost.

Healthcare analytics would then become a ubiquitous, proactive force for quality of life.

For More Information:

Follow Jim On: