How to assess the winners and losers with disruptive technology

For healthcare payers and providers, the answer depends on more than just saving money—optimizing health should be the basis for adoption.

With wearables, artificial intelligence and machine learning all influencing the healthcare market, how do health plans decide what’s needed to thrive in today’s value-based market?

According to worldwide technology thought leader Enrique Dans, author of Everything Will Change: Technology and Evolution: Adapt or Disappear, and professor of Innovation at IE University’s Business School, in Madrid—the bottom line shouldn’t be the motivating factor.

According to Dans, to take just savings into account, when deciding how to proceed with this new technology, is extremely shortsighted. “Lower costs could be a consequence, but should never be the trigger for adoption,” he says.

In his work as a researcher, disseminator and advisor, Dans studies the effects of technological innovation on people, companies and society—as a whole. Dans expects these trends to affect health plans.

Who are the winners and who are the losers when it comes to health insurance companies and wearables? What kind of technology are you seeing as the most disruptive in healthcare, especially for health insurance companies?

Dans: The power of devices that allow us to capture our vital signs and store them in a digital repository is huge, and if we learn to analyze it successfully, the winners will be all of us. By examining these data, we could be able to learn a lot about diseases, their effects, their early detection and how to treat them. Right now, many devices can detect atrial fibrillation, and if we wear a device continuously in our wrist, such detection can be performed with a very high level of accuracy. A heart attack, in principle, cannot be detected with such level of accuracy, but this is fundamentally because of a lack of data. As soon as we learn how to do it, and we develop the proper algorithms to keep us under control, early detection could allow the avoidance of a number of casualties. I don't see any losers in such a scenario, unless we use the data in the wrong way (such as, for instance, discriminating customers according to their health patterns).

Are you seeing U.S. insurance companies using wearables to bend the cost curve in healthcare? If so, what are some good examples? If you aren't, do you think they should?

Dans: Setting such a context to take just cost into account is extremely shortsighted. Lower costs could be a consequence, but should never be the trigger for adoption. Undoubtedly, if we gain the ability to early detect a number of diseases and conditions, we will be able to treat them much better, we will move from a reactive healthcare to a proactive one, and the whole humanity will benefit significantly from that. One of the main problems of the current medical system is that you only connect with the system every now and then. We are now in the largest wave of personalization and data quantification in history, but for healthcare, we are still miserably waiting in line in an emergency room and only when problems have already manifested. Some companies are starting to demand their clients to use certain wearables in order to control their health. However, this will only become a reality when they become able to use all the raw data generated by these devices and develop algorithms that take care of their health in a proactive way.

What are the most prevalent ways that health insurers are looking into wearables for their beneficiaries?

Dans: So far, most health insurers are just trying to learn more about their beneficiaries, understand their habits, and to what extent they live a healthy life or not. If they detect potential health concerns, they might provide advice or increase the cost of the policy, even to a limit when they pretty much invite them to go someplace else. That is a totally incorrect approach, and most likely, it will become illegal at some point following the ideas outlined in the Genetic Information Non-discrimination Act (GINA). The correct approach is to try to monitor their beneficiaries in order to provide them, as the term implies, with the biggest benefit: a proactively managed healthcare, one that reduces morbidity and mortality due to an advanced, algorithmic monitorization, and suggestion the proper course of action before the illnesses and serious problems hit.

Do you think there is a cause for concern about privacy when it comes to wearables? How are providers and insurers handling privacy when it comes to wearables?

Dans: Privacy is a growing concern, and it has to be managed carefully. First of all, companies need to drastically increase the quality of their security practices. We cannot accept the aphorism "companies are divided into those that have been hacked and those that will be" when it comes to our health data, no one would trust a company that gets hacked every now and then. Second, they need to understand the value of permission: we give permission to access our data to companies that put these data to a good use. We give permission to Google because, after all, what we see is that, after gathering all of our data and getting to know us more than ourselves, all we see is better targeted ads. We don't trust Facebook anymore because we notice that they not only capture our data and share it with pretty much anyone who can create an app, which means everyone, good or evil, but also get hacked often and even allow evil actors to design massive manipulation strategies to influence elections, etc. Companies need to understand that they need to be like Google and not like Facebook. We will surrender our data when we clearly see what's in it for us in terms of benefits: better healthcare, cheaper prices, faster attention and better alerts.

How easily is data transmitted from wearables to doctors? Is interoperability still a barrier when it comes to wearables?

Dans: Wearable manufacturers need to understand the value of open data. Manufacturers that try to control our data and preclude us from exporting it or share it with other apps will fail. Apple, for instance, embraces the fact that our data is exactly that, ours, we own them and have the right to do whatever we decide to do with them. If you want to donate your data to teams of researchers, physicians or scientists that make healthcare progress, Apple provides you - and them - with a ResearchKit™ that allows them to develop specific apps, gather data, run tests, etc. The ability to offer apps that gather data from all types of wearables and their sensors, integrate them properly, discard systematic errors and draw proper conclusions will become increasingly important.

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