SleepScore Max: Are Big Data the New Digital Doctors?

In the present media landscape, big data has revolutionized the way in which we regulate, analyse and influence data across several industries — one of which is healthcare. With the ability to monitor patients based on sensors embedded in products such as watches and clothing, big data in healthcare analytics have the potential to reduce costs of treatment and improve an individual’s overall quality of life. (Beall, A L. “Big Data in Health Care”). An example where healthcare analytics is being practiced is in the field of sleep. Specifically, through a cutting-edge device called ‘SleepScore Max’.

Released in November 2017, the device claims to be the “definitive consumer standard of sleep measurement and improvement” by measuring a user’s breathing rate and tiniest body movements while they sleep through ultra-low power radio waves. In the morning, the user is then presented with a personal score between 1-100 determining how well they slept along with information such as interruptions, time to fall asleep and the breakdown of their sleep stages (SleepTrackers.io). Taking this as my primary example, I attempt to explore the extent to which big data are the new digital doctors and consequently investigate prominent ethical questions worth considering.

Privacy and the Zzz’s…

Based on three key reviews of this device — ZDNet, SleepTrackers.io and PhoneArena.com, what seems to differentiate SleepScore Max from the steady stream of new age sleep technology is the mammoth amount of data backing it. According to a review by ZDNet the device operates on data collected from 4 million nights of sleep, an algorithm based on 2.7 million nights of sleep research conducted by experts in the field and 4.8 billion sleep quality metrics (Dignan, L. “Big Data Analytics”). While this data may indeed prove useful in identifying patterns of sleep behaviour, it nonetheless brings forth my first ethical concern — Privacy. Culnan and Williams have pointed out the potential for abuse of unauthorized data and reuse of information that could culminate in privacy problems (Culnan and Williams 675). They explain that information reuse consists of legal decisions made by organizations to determine new ways of using collected personal information. Moreover, with the magnitude of data that flows through the device’s servers there is also the question of unauthorized access, whereby employees can view personal information. Significantly, Zwitter sums it up best stating that the “internet of things” further fuels the distance between the will and knowledge of one actor and the source of power and information of another, putting people at an ethical disadvantage (Zwitter 3).

Everyone wants a Piece of the Pie: The Problem with Objectivity

Apart from the ability to produce a definitive sleep-score, another key feature of SleepScore Max is its ability to provide custom product recommendations to further enhance the experience. Some of these include anti-snoring devices, mattresses, smart lights and a vast range of apps and programs that appear every 30 days of constant usage. Moreover, the creator of the device, SleepScore Labs, is a joint venture between Pegasys Capital — providing the capital, Dr. Mehmet Oz — bringing the audience and marketing aspect and ResMed — contributing the analytical backbone.

The fact that devices such as SleepScore Max are backed by several parties each with their own capitalist interests is elaborated upon by Kitchin, who mentions that big data are never objective and consist of sociotechnical systems that are complex and exist within a greater institutional framework of institutions, researchers and corporations who are vital tools in the production of governance, knowledge and capital (Kitchin 21). According to me, objectivity is a crucial ethical component of healthcare and while the move to the online sphere has made its maintenance seemingly problematic, it is nonetheless the ethical duty of e-healthcare developers to uphold this value to the best of their ability.

Blurring the Lines – The Ethical Crossover

The device clearly mentions that it cannot and will not medically diagnose a user (phoneArena.com), however, this does not seem to be the case. SleepScore Max not only tracks a user’s sleep quality but also takes definitive action by means of making dietary recommendations and psychiatric therapies such as Cognitive Behavioural Therapy.  Affordances such as these lead to the following question: should the same ethical guidelines that apply to healthcare professionals also be applied to e-health developers? Vayena et al. quote Fairchild and Bayer who state that many of the guidelines and legislation implemented by public health surveillance were developed under vastly different historical conditions and the technologies of today far supersede the framework that existed in the past (qtd. in Vayena et al. 2). Based on the potential of the technology provided by SleepScore Max, there is a consequent requirement for ethical norms in health technology to be updated, which remains more pertinent than ever before.

So, Are Big Data the New Digital Doctors?

Think about it. Why is it that after your last check-up your doctor called you — either in person or over the phone to give you your test results? Or that you had to authorize a friend to pick up your medical records that weekend you were out of town? The information we receive from health tests are sensitive and private data. However, in the context of big data, we are rarely aware of the great maze of actors and institutions that remain invisible to us while we remain visible to them. In terms of objectivity, the merging of different industries each with their own set of rules have resulted in a grey area—one where commercialization and third-party interests make it impossible to remain objective.

With the example of this blog post, SleepScore Max claims that it cannot and will not ‘medically diagnose’ a user. However, with equipment as advanced as bio-sensors and sonar, it is clearly contradicting itself. Lastly, no two individuals are the same when it comes to practices as varied as diet, exercise, medical history and sleep habits. Add this to the inherent socio-economic and cross-cultural barriers (a single device goes for $149) it is worth investigating just how representative the nature of big data in healthcare is?  While only time will tell whether or not the merging of big data and healthcare will bring with it the age of the digital doctor, for me, there is a significant requirement for the ethics surrounding healthcare to be applied to its digital equivalent.

Works Cited

Beall, A L. “Big Data in Health Care.” SAS: The Power to Know, www.sas.com/en_us/insights/articles/big-data/big-data-in-healthcare.html.

Culnan, M J, and C C Williams . “How Ethics Can Enhance Organizational Privacy: Lessons from the Choicepoint and TJX Data Breaches.” MIS Quaterly, vol. 33, no. 4, Dec. 2009, pp. 673–687., www.jstor.org/stable/20650322?seq=1#metadata_info_tab_contents.

Dignan, L. “SleepScore Max Review: Sleep Improvement System with Big Data, Analytics Backing.” Big Data Analytics , ZD Net, 11 Dec. 2017, www.zdnet.com/article/sleepscore-max-review-sleep-improvement-system-with-big-data-backing/.

Fairchild AL, Bayer R (2004) Public health. Ethics and the conduct of public health surveillance. Science 303: 631–2.

Gaskin, Corey. “SleepScore Max Hands-on: The Best Approach to Sleep Tracking? | PhoneArena Reviews.” Phone Arena, PhoneArena, 20 Feb. 2018, www.phonearena.com/news/SleepScore-Max-hands-on-best-sleep-tracking-approach_id102634#.

Kitchin, R. “Thinking Critically About Databases and Infrastructures.” The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences, SAGE, 2014.

Martin, B. “In-Depth: Cognitive Behavioral Therapy.” Psych Central, 20 Sept. 2018, psychcentral.com/lib/in-depth-cognitive-behavioral-therapy/.

“SleepScore Raises the Bar with Clever New App.” Best Sleep Trackers 2018, sleeptrackers.io/sleepscore-releases-free-app/.

Summers, J. “Principles of Healthcare Ethics.” pp. 47–62, samples.jbpub.com/9781449665357/Chapter2.pdf.

Vayena, E, et al. “Ethical Challenges of Big Data in Public Health.” PLoS: Computational Biology, vol. 11, no. 2, 9 Feb. 2015, doi:https://doi.org/10.1371/journal.pcbi.1003904.

Zwitter, A. “Big Data Ethics.” Big Data and Society, 20 Nov. 2014, pp. 1–6., doi:10.1177/2053951714559253.