Katina Michael, in a conversation with The Register (2015), asked “How long does it take until we’re constantly being monitored and tracked, and people are predicting our next action?” – the answer is now, Katina.
In fact, the new email extension Crystal informs users on how to construct emails based on the intended recipient, by predicting the best characteristics the person would respond positively to. Crystal does this by analysing all the Big Data on the subject and producing a profile from an algorithm. But Crystal, albeit new, has its shortfalls. Lucy Kellaway, on her podcast Listen to Lucy (2015), demonstrated the tool and declared that while it described her perfectly, the suggestion to send emotions to her in an email was so far away from the truth, she believes Crystal could just be guessing. But it’s undeniable that powering Crystal is a very complicated algorithm that can find and predict a person’s preferences based on just public data.
But beyond emails, having data about someone before an interaction can be very helpful to predict other outcomes – potentially life saving outcomes. I propose the benefits of big data for the medical industry, and how shareable public (contained or anonymous) medical data can encourage a holistic approach to treating physical and physiological issues in society.
Giving medical professionals access to a patient’s medical data allows the industry to have up-to-date information on how to treat that person and others like them. This reduces the issues of seeing new doctors or giving the wrong information to different medical disciplines, encouraging a holistic approach to treating issues beyond a GP visit.
Michael Sherling, a dermatologist from Florida, changed his practice from paperwork to a digital data structure after developing his own solutions for: patient engagement tools, electronic medical record platforms, and data mining. One solution is providing “an electronic application that allows doctors to rapidly enter clinical information, and to draw on the data gathered from thousands of others doing the same” (Sherling 2014). Doctors can capture a patients data, upload it to a data aggregate as anonymous information, which can then be accessed by other medical professionals to make better decisions. Utilising digital technology and data management that can draw from large up-to-date data samples reduces documentation so “doctors can just focus on treating patients, not paperwork” (Sherling 2014).
The issue, like with all data, is privacy. Joel Dudley, director of biomedical informatics for Mount Sinai’s Icahn School of Medicine, says it’s very difficult “to [transfer] patient data from one hospital or doctor to another, let alone from all the fitness trackers floating around” (Leber 2013). The best method is voluntary participation, as John Sotos outlines in his Wall Streeet Journal article (2015). Long term participation is very important for treating the “evolution of a patient’s illness over time” (Sotos 2015). Additionally, long term data aggregation will improve the existing “coarse definitions of diseases which are not [currently] very data-driven” (Leber 2013).
In short, constantly being monitored and tracked, to allow doctors to predict our next action, can’t come soon enough, Katina.