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Widely Available Marketing Data Used to Assess Personal Health Status

Posted May 06 2011 12:00am

In previous notes, I argued that it was largely useless to complain about the loss of privacy and confidentiality in this digital era because the horse was already out of the barn (see: On the Privacy of Health Information: The Horse Is Already Out of the Barn ; Despite HIPAA, the Privacy of Our Health Records Is Largely a Myth ). Instead, one needs to help prevent further erosion of our rights. A recent article reinforced this idea. It showed how life insurance companies are now using readily available marketing data about individuals to assess their health status and therefore risk (see: Insurers Test Data Profiles to Identify Risky Clients ). This approach will be in lieu of, or in addition to, the lab testing and health questionnaire that the companies have used for many years. Below is an excerpt from the article

Life insurers are testing an intensely personal new use for the vast dossiers of data being amassed about Americans: predicting people's longevity. Insurers have long used blood and urine tests to assess people's health—a costly process. Today, however, data-gathering companies have such extensive files on most U.S. consumers—online shopping details, catalog purchases, magazine subscriptions, leisure activities and information from social-networking sites—that some insurers are exploring whether data can reveal nearly as much about a person as a lab analysis of their bodily fluids. Life insurers are testing new ways to predict life expectancy and they're mining personal information online and offline to do it. In one of the biggest tests, the U.S. arm of British insurer Aviva PLC looked at 60,000 recent insurance applicants. It found that a new, "predictive modeling" system, based partly on consumer-marketing data, was "persuasive" in its ability to mimic traditional techniques. The research heralds a remarkable expansion of the use of consumer-marketing data, which is traditionally used for advertising purposes. This data increasingly is gathered online, often with consumers only vaguely aware that separate bits of information about them are being collected and collated in ways that can be surprisingly revealing....A key part of the Aviva test, run by Deloitte Consulting LLP, was estimating a person's risk for illnesses such as high blood pressure and depression. Deloitte's models assume that many diseases relate to lifestyle factors such as exercise habits and fast-food diets....The industry is grappling with how to get policies into the hands of middle-class families more cost-effectively. Sales of life policies to individuals are down 45% since the mid-1980s. Deloitte says insurers could save $125 per applicant by eliminating many conventional medical requirements. Under Deloitte's predictive model, the cost to achieve similar results would be $5, Deloitte says. The total underwriting costs for a policy range from $250 to $1,000, insurers say. Making the approach feasible is a trove of new information being assembled by giant data-collection firms. These companies sort details of online and offline purchases to help categorize people as runners or hikers, dieters or couch potatoes. They scoop up public records such as hunting permits, boat registrations and property transfers. They run surveys designed to coax people to describe their lifestyles and health conditions.

To briefly summarize, all of us leave fingerprints on the web documenting the extent to which we are pursuing a healthy and active lifestyle. Have you purchased sports equipment or a hunting license lately? Similarly, we may also be providing evidence of our chronic diseases such as diabetes, obesity, or hypertension by our information-seeking behavior. Companies such as Aviva and Deloitte Consulting are developing "predictive modeling systems" based on marketing data to make a determination about our health status. These systems can be made even more accurate when combined with pharmacy benefit management (PBM) databases that document prescription drug purchases from which the presence of various diseases can be predicted. From the perspective of life insurance companies, it's much cheaper to use these "public" database-driven  models to identify potential healthy, lower-risk potential customers than conventional, medical screening techniques.

So, what can you do about all of this? I am not about to alter my web-browsing activities for fear that these data are being collected. I do, however, favor initiatives such as "do not track" legislation that is popping up in various states and at the federal level (see: California Do-Not-Track web privacy law moves forward ). Frankly, I am also not optimistic that such legislation will have much teeth in it because more money will be spent on lobbying by commercial interests opposed to such legislation than privacy advocates. This situation can only get worse as the web becomes even more ubiquitous in our lives.

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