Complimentary from the publishers of Predictive Modeling News                August, 2014
	"I have written before about a project to develop a model developed by SCIO Health Analytics to predict patients at end of life, specifically those who are likely to be subject to over-medicalized treatment at end of life. This model was particularly successful at identifying patients in this category. A more innovative (but related) model was also developed by SCIO to address the ‘frequent flyer’ problem. One of the interesting technical problems with ‘frequent flyers’ in the Medicare population is the frequency with which patients transfer between emergency room, inpatient hospital, rehab facilities, SNFs, nursing homes and home. SCIO developed a weighted index to identify not just the number of transitions that a patient made but the weight attaching (given that some facilities are more expensive than others). For an ACO interested in trying to reduce ‘frequent flyers,’ this approach is both innovative and useful, because it doesn’t just address ER (the typical focus of analytics and programs) but what happens to the patient after discharge.” Ian Duncan, FSA FIA FCIA MAAA, Adjunct Professor of Actuarial Statistics, University of California, Santa Barbara
	In an individual patient who exhibited two of the five risk factors [for metabolic syndrome],... “researchers could predict which third factor is the most likely to develop.” The analytical models also helped identify individual variable impact on risk associated with adherence to prescribed medications... as well as adherence to routine, scheduled outpatient doctor visits. A scheduled outpatient visit with a primary care physician lowers the one-year probability of having metabolic syndrome in nearly 90% of individuals. Excerpted from: Predictive Modeling News, Volume 7 Number 8, August 2014, "Journal Review: American Journal of Managed Care Publishes Results Showing ‘Big Data’ Analytics Can Predict Individualized Risk of Metabolic Syndrome in Patients"
	Jvion Releases Top Three Lessons in Predictive Population Health Analytics StreetInsider.com, July 31, 2014
	Health care predictive analytics: Who is making choices, to what end? The Incidental Economist, July 17, 2014
	Lessons Learned: Bringing Big Data Analytics To Health Care Health Affairs Blog, July 14, 2014
	Data collection could stump next phase of predictive analytics Modern Healthcare, July 12, 2014
	Predictive analytics in healthcare: Are they safe? FierceHealthcare, July 11, 2014
	The Legal And Ethical Concerns That Arise From Using Complex Predictive Analytics In Health Care Health Affairs, abstract only, July 2014
	Speakers’ Responses to Participant Questions Round Out Analytics Webinar Information Journal Review: The Legal and Ethical Concerns That Arise From Using Complex Predictive Analytics in Healthcare; Implementing Electronic Healthcare Predictive Analytics: Considerations and Challenges; American Journal of Managed Care Publishes Results Showing ‘Big Data’ Analytics Can Predict Individualized Risk of Metabolic Syndrome in Patients Meditology Outlines Top 5 Technology Strategies for Population Health, Engagement Thought Leaders’ Corner: “What is the most innovative use of predictive modeling you’ve observed recently?" Industry News with briefs regarding Rite Aid and Health Dialog; Holy Spirit Health System and Capital Blue; Startup Health; Celanese; eCaring; Explorys; and Strategic Health Services and King's Daughters Health System Catching Up With….David Howe PhD Click here to view page one of this issue Click here to subscribe to Predictive Modeling News, or find out more
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