The Quantified Self: information challenge or opportunity?
Quantified Self: a movement to incorporate technology into data acquisition on aspects of a person’s daily life in terms of inputs (e.g. food consumed, quality of surrounding air), states (e.g. mood, blood oxygen levels), and performance (mental and physical). – Wikipedia
Last Christmas, I decided to take some steps towards ridding a few pounds from my Irish meat-and-potatoes frame. I downloaded a walking app, and went to it. Immediately, I was impressed at the app’s ability to track and present back to me my location, and how well I was doing. I even started a bit of running (Usain Bolt has NOTHING to worry about).
This Christmas, FitBit revamped their app to include free tracking of activity, without the requirement to buy and wear one of their wristbands. I downloaded it, and was struck by the sheer amount of data that is now captured as we go about our daily lives. Steps taken, calories burned, calories consumed, how you slept. These devices aim to provide awareness of every aspect of your activity on a constant basis. I’m now hooked, especially since I discovered that I can rank myself alongside co-workers and friends to see who is the most active (answer: not me), it even provides me with a weekly email summary of my activity levels (or lack thereof).
While this is a relatively personal activity, or “social” amongst my friends, it has massive potential within the medical arena. If we could make use of this information within the health setting, we will have the ability to make predictions on health conditions, to spot patterns in activity levels and their effect on the person. Has the patient been taking the GP’s advice to get more exercise? Has taking a certain drug forced a more sedentary lifestyle on them? Does weight loss have a true correlation to improvement in condition? (I sincerely hope so).
Telehealth has been available for several years now, and is rapidly maturing, however it is traditionally used for a very specific segment of the population who are being treated for a specific condition. Activity trackers and “quantified self” are consumer devices, that, if used to their true potential, can give a powerful insight into everyone’s activity and lifestyle.
To make best use of the opportunity provided by this rise in detailed information, we need the tools and technology; good interoperability standards, to allow the automatic sharing of this information securely from the consumer / patient to their GP, from their GP to the Acute Trust etc.; & good patient-accessible portals to help them make sense of the information they are gathering, to choose how it will be handled and used.
Arguably, even more important are the tools to make sense of this tidal wave of information. This is the area that interests me most. Within Evolve, we are taking great strides in the Information Analysis capability provided by Evolve Healthcare Analytics, enabling healthcare providers in the future to spot the patterns (and co-incidental non-patterns), and adjust the care services provided based on good, quantified, reliable information. Whilst “Big Data” has been a concept for a while now , within medicine it has been largely focussed on research, details of treatments, encounters and billing. With the potential influx of constantly-monitored population data, “Big” doesn’t begin to state the size of the body of information that is available. I believe Evolve has the right toolset to help patients send and receive their information to care providers, for care providers to store and manage that information, and for everyone to gain true insight into care needs, provision and outcomes based upon increasingly large, diverse, detailed data sets.
The Institute of Design at Illinios Institute of Technology have produced a handy “map” illustrating Quantified Self in all its forms and implications – https://www.id.iit.edu/media/cms_page_media/306/QS-EcosystemMap_2.pdf – it’s interesting to note their segregation and quantification of “activity”, “biometrics” and “mood” – again, moving the available dataset way beyond just steps taken and how you’ve slept.
The devices are only going to get smarter. This area is constantly expanding, getting ever more accurate, and will majorly disrupt how a clinicians currently provide diagnosis and treatment.
Those who can harness and use that information will be the clear winners.
For now, I’m off to clock up a few more steps, otherwise I’m going to fall further behind my friends in this week’s rankings…
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