Quantified Self and Information Asymmetry in Health Insurance

4

October

2016

5/5 (2)

With today’s technologies it is easier than ever to track and analyze your body, mood, diet and just about everything you can imagine. Tracking and analyzing data about yourself is referred to as the ‘Quantified Self’. The information can be used to make an inference about your health and how your decisions affect your health. Potentially, this data can also be used by healthcare insurers, to decrease the information asymmetry and moral hazards in the health insurance industry.

At first sight, no. In the Netherlands, it is not allowed to charge different premiums for the same package, regardless of personal differences like health or age. So it seems that the concept of Quantified Self cannot be used at all.

Healthcare insurer Menzis however has a clever way of dealing with this problem. With the ‘SamenGezond’ program customers of Menzis can save points by living healthy. The program accepts a wide range of activities that are rewarded with points. A run that is tracked with Runkeeper is an example of Quantified Self data that can award the customer with points. These points can used as a currency in the Menzis webshop. In this webshop a wide range of products and services can be bought: from portable speakers to a relaxing day in a welness resort.

In a way, this is not different at all from charging different premiums to customers with different health levels. The baseline premium could be high but, as long as the products in the webshop are products that the customer needs anyway, can be lowered by living healthy and saving points. To give a more accurate representation of customer health Menzis could expand the data that earn the customer points. With smart wristbands the activity level, sleep quality and quantity and even the heart rate of the customer could be used to reward points.

It is important to consider that the healthcare system of the Netherlands is based on social solidarity. With that in mind it would be unfair to charge those with a genetic health disadvantage or the poor higher premiums. But it also means, in my opinion, that it is unfair that those who invest in making healthy choices every day face a higher premium due to individuals that are not making those decisions. The data resulting from the Quantified Self could be used to align the health insurance premium with the actual health of the applicant.

What do you think? Is the Quantified Self a solution for the information asymmetry and moral hazard in the health insurance market?

Sources/Interesting Links:

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Ted Talk on the Quantified Self

Menzis SamenGezond progam

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3 thoughts on “Quantified Self and Information Asymmetry in Health Insurance”

  1. Dear Emiel, thank you for your blog! While I believe the Quantified Self is a good way to track your health, with regards to insurance, I believe it is only beneficial for generally healthy people. If an unhealthy person uses the quantified self to track their health, insurances may find out they are unhealthier than they said to be, causing their premium to go up. However, this does reduce information asymmetry in the health industry, and some people would benefit, while others won’t.

  2. Dear Emiel,

    I think you wrote an very interesting article. I agree that this could be a solution for the information asymmetry in the health insurance market. However, we deal here with sensitive information of clients. Therefore, I would like to add that this is only justifiable if clients are not forced to sign up and are completely made aware of the reasoning behind the ‘Spaarplan’.

    If Menzis would do so, it would result in only healthy people signing up and profiting from lower insurance prices. One could think this will destroy the business model of Menzis. Nevertheless, if it is true that the healthiest people will not spend an amount larger than their payed premiums, Menzis would not face financial trouble.

    I would say that the conversed lemon principle applies. Risky, less healthy people exit the Menzis market and more healthy, less risky people enter. The average premium drops, but the risk drops too. In the end, I would not be surprised it Menzis profits from this movement.

  3. Hey Emiel!

    First of all, thanks for this interesting post. The healthcare industry, if we can call you that, is still a bit unexplored and suffers from some tabus, and it’s always good to see someone addressing so pertinent questions.

    Starting with your questions: personally, I would be interested in engaging in such a quantified self approach, if that served to lower my premium. So many companies already have access to our personal information, so why not allow the insurance market to do the same? It definitely helps reducing information assymetries (even though only until a certain extent) and that should prompt a price reduction for those that reveal to be less “risky”.

    However, there is a thin line implied here, that probably most of us isn’t willing to cross. I might be ok with providing a company with my exercising and food habits, the places I like to go, the acitivities I engage in, etc. But what about blood tests? What about CTs and X-rays? Do I want to upload to an app that kind of information? What will they do with that? Who else can access that information and what kind of implications can that have in my life?

    The reason why I’m raising these questions is because two or three years ago I heard that an insurance company in Portugal was actually trying to implement an app with this kind of details associated. Not only they wanted customers to inform them about lifestyle behaviors, but also about their blood tests results, for example. I went to their website after reading your blog post, and there is nothing about such a technology, which makes me assume that they gave up on the idea.

    The question now is: when is it too much?

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