Insurance companies are experimenting with two strategies for motivating you to share your health information with them.
Digital Actuaries
Actuaries manage risk by using data to predict the future. Insurance companies rely on actuarial science to estimate the likelihood of death and sickness among those they insure.
In the old days, this kind of prediction was done using actuarial tables. Today, big data drives those predictions, and so the new race in insurance is gaining access to your health data.
The 1996 Health Insurance Portability and Accountability Act (HIPAA) established privacy guidelines for any information about health status, provision of health care, or payment for health care that might be collected by a healthcare organization. Even in the face of these constraints, insurance companies are now exploring various approaches for getting at the explosion of data coming out of activity-tracking and health-monitoring devices like those from Fitbit and Apple. These new windows into our bodies represent a treasure trove of actuarial data with the potential to revolutionize insurance.
New Incentives for Your Health Data
A few insurance companies have come to the conclusion that it is worth sharing some of the financial upsides of this data with end users. There are difficult questions surrounding insurance companies’ use of this kind of data for discriminatory and otherwise unethical behavior. Part of solving this societal challenge lies in understanding the new incentives insurance companies are now beginning to use to obtain that user data in the first place.
The first approach is that taken by Humana through its Go365 rewards program, which aims at creating incentives for healthy behavior. Various activities give you points. Taking a health exam, for example, is worth 500 points, while keeping a sleep diary is worth 25 points per week. Points translate into a kind of pseudo-currency called “Bucks,” which can be redeemed for things like Amazon gift cards and other rewards. As your points increase, you also increase your status from Blue to Bronze, Silver, Gold, and Platinum, and with each bump in status, your benefits grow. All of this activity is of course designed to generate very detailed flows of data about your health behavior.
The second approach to motivating end users to share health data is the promise of lower health insurance premiums. This is the approach taken by Health IQ. The company uses a health quiz to help it identify lower-risk individuals and save those individuals up to a purported 25% on their health insurance premiums. They are, in effect, a digital actuarial service for helping insurance partners to better understand their risks. I’m not sure how they pull this off within HIPAA guidelines, as one of the things specifically allowed in their privacy policy is the ability to use individually-identifiable health information to “qualify you for insurance products” as a “business associate” for their healthcare providers.
Which Strategy Will Win?
So here we see two emerging incentives for end users to contribute their data to lower the risks and costs of health insurance. One rewards users with prizes, the other with lower rates. Both strategies amount to passing on a portion of the savings generated by better predictions from more data.
Which strategy will win in the market place is still an open question and there may well be room for both. Lowering rates is something that is easy for most end users to understand, but in a complex business like health insurance, true apple-to-apple comparisons between plans can be difficult and that may make rate discounts hard to meaningfully quantify for users. When done right, awarding prizes can tap into human psychology and the behavioral economics and “gamification” strategies so common in Internet businesses. It is more complex, however, and may simply require more attention than most end users are willing to invest in insurance.
The reasons for paying attention to these experiments are two-fold. The first is that these incentive programs are shaping the future of the insurance industry in ways that could lead to undesirable social consequences. The second is that these two approaches could hold lessons for companies in other industries too as they struggle to motivate end users to contribute their data to their ever-growing organizational intelligence.