Consumer driven health plans, which grew in enrollment by over 18% between 2011 and 2012, aim to lower healthcare costs by encouraging individual members to become savvy shoppers. How significant are these shopping opportunities? Which services have the greatest potential for savings, and how does that potential vary across regions and insurers? Castlight Health has analyzed hundreds of millions of medical claims from several dozen different insurers to answer these questions.
In this presentation, we will discuss our methodology for predicting shopping opportunities from medical claims. We will proceed with a deep dive into the results of past analyses, highlighting the procedures that exhibit great price variation. We will discuss some of the reasons for this price variation and consider when consumers can (or cannot) effectively choose high value care. Finally, we will demonstrate how we use this framework to analyze new benefit designs to promote shopping without compromising access to care.
John is a Senior Member of Technical Staff in the Pricing Research Team at Castlight Health. Prior to joining Castlight, he was a PhD candidate in Business Economics at Harvard, where he focused on econometrics and health care markets.
Jen works as a data scientist and engineer at Castlight Health. Previously she has worked as a web developer, science teacher, and equity options trader.
Arjun is a data scientist on the Pricing team at Castlight Health. Previously, he worked with data in the online advertising and scientific computing domains.
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