The Downside of the Explosion of Available Health Data

The Downside of the Explosion of Available Health Data
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Before the Information Age, much of medicine was as much art as it was science. Physicians depended on their observational skills arguably more than they do in the modern era. This is largely due to how heath technology is advancing medicine.

One of the benefits of digital health is that the doctor’s office has never been so close to home before. We have been empowered to take more responsibility when it comes to our health.

Technology supporting the “quantification of self” allows us to record a variety of personal biological measurements as well as track our physical activities. Furthermore, digitalization of medical records has improved the access to our health data, as well as improved the accuracy of our medical history.

In the midst of the positive developments concerning mHealth (mobile health) and digital health devices, some questions are arising that need to be addressed when utilizing this novel technology. Some of these important questions include:

  • Are there any concerns surrounding the widespread use of wearable devices and apps?
  • What are the consequences of sharing health data so liberally?
  • Can some groups of users become more vulnerable (than others) when exposed to a vast amount of health data they do not necessarily comprehend?

Digital Health Internet Trends in 2017

According to a report prepared by Mary Meeker of Kleiner Perkins, 25 percent of Americans now own a wearable device.

This represents a 12 percent increase from 2016. Among Millennials, the use of wearable devices is even more prevalent at 40 percent. The most popular devices by far are accelerometers—speed is measured by 86 percent of wrist wearables used today—followed by devices measuring heart rate (33 percent).

Accelerometers are usually used with other sensors, such as sleep sensors and pedometers.

Mobile health apps have been proliferating as well. Many of us are now downloading different applications that promise to improve our health and well-being, including fitness, diet and various condition-specific applications. Most consumers (88 percent) use at least one digital health tool, and one in 10 can be considered super users, using five or more digital health tools. Surveys show that we are not only eagerly collecting our health data, but we are also increasingly sharing it—willingly or unwillingly.

The increasing trend of health information digitalization can also be observed in the doctor’s office. The number of office-based physicians using electronic health records (EHR) has jumped from 21 percent in 2004 to 87 percent in 2015. An increasing amount of our data is being accumulated in digital form, including clinical results and scanned body images as well as our medical histories.

Progressive medical groups are empowering patients to become a more integral part of their own care. Once rare in clinical practice, hospitals now enable clients to either view their health care information online (95 percent) or download their data (87 percent) for offline viewing.

Only a few years ago health data was usually gated from patients, but access to data is now generally considered a patient’s right.

Simple access to data is not the only hurdle in making this information useful. In her report, Meeker presents calculations showing that a standard 500-bed hospital with 8,000 employees accumulates 50 petabytes (50 million gigabytes) of data annually. Managing this immense amount of data, and making it useful and interpretable, is also a challenge.

The Need for Smart Consumer Knowledge

Using different health platforms and digital health devices can be beneficial. However, when we use the Internet and the Internet of Things to influence our health, we are vulnerable to making personal datasets available to marketers and hackers.

We need to be aware that self-advancement in the area of health also means that other people and institutions can become privy to our data, as well as our health-related conditions.

Another concern about these datasets is the quality of the information that gets gathered. There is a growing healthy population that is using condition-specific digital health devices meant for people with chronic conditions. This group often describes their motivation as a mix of interest in the health condition and a way to monitor preventative strategies. However, people in this group do not always have the experience to correctly use health technology if they are not under the care of a doctor and have not been properly onboarded on how to use the equipment.

Erik Grönvall of the IT University of Copenhagen and Nervo Verdezoto of Aarhus University in Denmark point out that while users might be able to take their own measurements, these measurements are not necessarily valid if the digital health equipment is not used properly. The study followed people who self-monitor their blood pressure at home. To obtain a reliable measurement from health technology, certain guidelines often need to be followed. For example, with blood pressure, “sit and rest for 5 minutes before taking the measurement.” Sometimes, users that haphazardly use devices are not aware of the consequences of unintentionally reporting inaccurate results.

Grönvall and Verdezeto also note that their participants were clear about not wanting strangers involved in their health management. To most of them, exposing health practices and results was not acceptable unless it related to their personal physician. This suggests that a certain amount of digital literacy is required when collecting and using your health measurements. Many people might be unaware when they share their data and/or what happens to it once it is shared.

Motivation for Self-Monitoring and Data Practices

Professor Deborah Lupton, who works at the University of Canberra’s News & Media Research Center, distinguishes between different modes of self-tracking: private, communal, pushed, imposed and exploited.

Individuals typically engage in “private self-tracking” to achieve better self-awareness. They collect data in an “n=1” type environment, so data is limited to the individual and kept private. Private tracking can be combined with “communal self-tracking” where their data is anonymized, then compared and shared using platforms and social media. This type of exchange of information has been associated with citizen science, social contagion and community development.

Next, Lupton mentions the “pushed self-tracking” where the initiative often comes from another agency and external encouragement is provided to collect and share your information. We can observe this type of tracking with some insurance companies offering incentives to customers if they agree to share their personal data.

“Imposed self-tracking” is another form of tracking that provides more benefits to other parties than the user. For instance, employees can be required to wear sensors that monitor their behavior and health. Lastly, Lupton talks about “exploited self-tracking” where our data (gathered in any of the above ways) is repurposed for commercial benefits. Data is productized and becomes a commodity with commercial value.

There is evidence that an increasing number of agencies, commercial institutions and organizations are becoming interested in harvesting data collected through different types of sensors and wearables. Lupton argues that the issue becomes more controversial when people are coerced or nudged into sharing their data.

What Are Our Rights?

Even when data is gathered anonymously or in a congregated form, the provider might be able to sell or share it with other parties. Therefore, it is very important to check the company’s privacy policy before using any tool that has the ability to collect personal data. Clicking the “I agree” button on the software that makes these devices operational turns you into a rich data source. Worse, the software might not allow you to use and/or protect your data in the way you intended.

“Ownership” over your data is a contentious subject. Our digital data trail is very accessible, but sometimes that access is denied to the one creating it. Generally, it is not difficult to copy or transfer someone’s data. Cloud servers are often run by firms that have legal claims over the datasets they collect. Their interest in Big Data is different from that of individual health enthusiasts. While many consumers are simply seeking small-scale insights into their personal health, corporations and governments are interested in gaining large-scale insights by processing our health data and applying it to whole populations.

Neil Richards and Woodrow Hartzog, two distinguished professors of law, point out that when it comes to Big Data and online privacy, most people are substantially less powerful than governments and corporations. In a nutshell, it can be challenging to protect our digital lives from monitoring. This unequal relationship has been described as another form of the “digital divide.” The evolution of digital health, the proliferation of available health data, and the increasing complexity of health technology means ensuring consumer data literacy is more essential than ever.

Not Understanding the Data You Are Given

Abundance and accessibility of health data can easily overload some users. People who are predisposed to anxiety may find understanding their health data overwhelming, especially when they receive bits of information that sound potentially alarming. Ryen White, PhD, and Eric Horvitz, PhD, conducted a study of cyberchondria—a modern-day version of hypochondria—that showed the Internet can have an ambiguous effect. For about 50 percent of people, the web does reduce anxiety. However, 40 percent of those who surf the Internet to understand their health problems become more worried after their research.

When complex data sets become easily accessible in a format foreign to the user, health-anxious individuals might have a proclivity to constantly examining their data. A Dutch study led by associate professor Martin Tanis suggested that there is a relationship between health anxiety and online health information seeking. Therefore, it can be argued that certain people are likely to become overly occupied with their data, especially if they do not fully comprehend its meaning.

A concern on the other end of the spectrum is that it has been observed that some users are starting to perhaps trust their tracking devices too much. Most of us develop natural regulation of our appetite and weight. In normal circumstances, these biological systems should keep us in check. However, these days, some prefer to consult their dieting app before eating a meal. While the data and information on many health apps are valuable and accurate, there is a lot of information that is inaccurate. If your diet app is underestimating your caloric intake and your activity tracker is overestimating your caloric burn, that is a recipe for weight gain. Ultimately, in these situations it is up to the end user to determine the degree of accuracy from any given app or data source.

Sources:

Lupton D. Self-tracking modes: reflexive self-monitoring and data practices. 2014.

Poel F, Baumgartner S, Hartmann T, Tanis M. The curious case of cyberchondria: A longitudinal study on the reciprocal relationship between health anxiety and online health information seeking. Journal of Anxiety Disorders, 2016:32-40.

Richards N, Hartzog W. Privacy's trust gap: a review. Yale Law Journal, 2017; (4):1180-1224.

Verdezoto N, Grönvall E. On preventive blood pressure self-monitoring at home. Cognition, Technology & Work, 2016; 18(2):267

White R, Horvitz E. Cyberchondria studies of the escalation of medical concerns in web search. ACM Transactions on Information Systems, 2009; (4):23.

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