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5 Big Ideas from the AHIP Conference

Margaret Dick Tocknell, for HealthLeaders Media, June 22, 2011

Last week's conference for America's Health Insurance Plans featured three days of workshops, networking breakfasts, appearances by Tom Daschle, Nicholas Christakis, Mary Matalin and James Carville, and more than 30 sessions devoted to making some sense of the business of healthcare.

By the end of the conference on Friday I was almost in information overload so it took a few days to sort out what I learned and what I think are the take away points. Here is my analysis of the big ideas presented at AHIP.

1. It's all about the individual.
In 2014 the health insurance floodgates will open and everyone will be required to have insurance. Health plans are a nervous about this because they don't really like to provide individual coverage. They'll tell you it's a money-losing proposition. But now they are going to have to get very familiar with the likes and dislikes of a market segment that they have been giving the back of their hand to for years.

For a change there's going to be plenty of competition trying to woo and win the individual policyholder and the market may resemble a free for all as individuals look for the best coverage at the best price. Even group policies may feel the pinch as individual employees, tempted by lower costs, jump ship to health insurance exchanges. Be prepared to invest some serious time and money into unlocking the key to the individual market. "It will take years for the healthcare industry to figure out how to influence consumers," said Sarah Rittman, a senior industry consultant for SAS, a Cary, N.C.-based business analytics firm.

2. Actionable intelligence is the way to go.
Actionable intelligence is the new buzz phrase. It's the information you need to have available to help make a decision. A doctor's AI might be a patient's test results. For health plans and providers, AI would be i
nsights into a specific business problem that help make strategic or tactical business decisions. AI usually involves metrics, benchmarks, and complex predictive modeling techniques. The point is that there's a lot of information available out there, but it needs to be analyzed, and even then not all of it will get your company where it needs to be.

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