What is Lifestyle-Based Analytics? It is the analysis of lifestyle-based data, which is widely available through consumer databases. The analysis of this data creates enormous opportunities and advances strategies for detected lifestyle-based diseases before they escalate into advanced stages.

Where is this data found? The data is coming from a diverse group of data sets. Every time you use a credit card, swipe a discount card at the grocery store, transact business on the Internet, apply for a mortgage, or go to the health club, information about your consumer habits are captured in a database. Culling through these databases can deliver significant data like food purchases, fitness activities, stress indicators, family size, occupation, tobacco preferences, alcohol preferences, travel destinations, and vehicle preferences. This data, when aggregated, can be insightful to health and life insurers in predicting future risk.

How are Lifestyle-Based Analytics being used? One of the most common uses of lifestyle-based analytics is to augment the underwriting process. Currently, data is available that accurately reflects the past medical conditions of an individual. Coupling this process with Lifestyle-Based Analytics can assist underwriters in predicting non-hereditary diseases and give an underwriter access to information those individuals who are unhealthy, as well as on those that data sets that show practice lifestyle choices considered to be healthy.

Disk storage per Person (DSP) is the approximate measure of the average amount of information stored for any particular individual. In 1985 DSP was estimated at 0.02, in 2005 DSP is projected to be 3,500 per individual. There is strong momentum toward using this data to progress understanding of risk. With lifestyle-based diseases accounting for three quarters of the nation’s medical expense, it is difficult to see how this momentum could be shifted. A better question is, should it be shifted?