Comments on: Integrating Predictive Analytics and BRM to Improve Health Plan Member Experience http://jtonedm.com/2008/10/30/integrating-predictive-analytics-and-brm-to-improve-health-plan-member-experience/ James Taylor on Everything Decision Management Wed, 10 Mar 2010 22:17:18 -0800 http://wordpress.org/?v=2.9.2 hourly 1 By: Neil Raden http://jtonedm.com/2008/10/30/integrating-predictive-analytics-and-brm-to-improve-health-plan-member-experience/comment-page-1/#comment-11523 Neil Raden Fri, 07 Nov 2008 18:19:17 +0000 http://jtonedm.com/?p=634#comment-11523 I really question this. You can't apply predictive modeling to individuals for health insurance. The underlying risk follows two simultaneous curves: one of high frequency and low severity, and one of extremely low frequency and high severity, and it's the second one that chews up all the dollars. You may buy a car every few years, but you only contract a terminal disease once (hopefully). A premature infant is only premature once. You cannot model that kind of experience over one person, or even a small group. Health insurance is not a consumer product and insureds don't view themselves as consumers.   I do, however, believe that your (or Deloitte's) suggestion that predictive modeling can be used for disease management and other sorts of outreach, but these programs are often voluntary and sort of gratuitous.   You can't reach out to someone with an unhealthy lifestyle (based on your data plus 3rd party demographic data from aggregators) and tell them, "We're your insurance company and we're here to help." That is a pipe dream that starts and finishes with an unwarranted belief that technology is the solution to every problem. People didn't get that way overnight and it will take more than a decision management solution to change anything. -NR   twitter nraden I really question this. You can’t apply predictive modeling to individuals for health insurance. The underlying risk follows two simultaneous curves: one of high frequency and low severity, and one of extremely low frequency and high severity, and it’s the second one that chews up all the dollars. You may buy a car every few years, but you only contract a terminal disease once (hopefully). A premature infant is only premature once. You cannot model that kind of experience over one person, or even a small group.

Health insurance is not a consumer product and insureds don’t view themselves as consumers.   I do, however, believe that your (or Deloitte’s) suggestion that predictive modeling can be used for disease management and other sorts of outreach, but these programs are often voluntary and sort of gratuitous.   You can’t reach out to someone with an unhealthy lifestyle (based on your data plus 3rd party demographic data from aggregators) and tell them, “We’re your insurance company and we’re here to help.” That is a pipe dream that starts and finishes with an unwarranted belief that technology is the solution to every problem. People didn’t get that way overnight and it will take more than a decision management solution to change anything.

-NR   twitter nraden

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