Measure twice, cut once.
That old idiom is usually attributed to carpenters, but there is wisdom in it for anyone working with data. Namely, make sure your data is sound before you can act on it.
Where Big Data and the Internet of Things (IoT) collide, we suddenly have an incredible capacity to put the old idiom into use. By virtue of health-oriented wearables, we can measure every conceivable biometric in real-time, or over any stretch of time, and have an unprecedented level of confidence that we have measured sufficiently to act on that data – in the event that surgery is indicated, to literally ‘cut once.’
What is missing from the wearables equation is the point where the carpenter puts down the measuring tape and takes up a saw. Many early adopters are hitting a ceiling on the usefulness of their new wearables, because once you know all your baseline information, there is little left to do with the measuring instrument. Physicians, by and large, are either unwilling or unable to make use of this patient-generated data.
Even that unwillingness is not entirely a matter of attitude. The Electronic Health Record (EHR) platforms physicians use to manage health data, and the platforms wearables use to store recorded data, are neither connected nor compatible – in the parlance of healthcare, they are not yet interoperable. For both patients and physicians, this means a lot of extra work to move data, or put it into a useful form for sharing.
The connected patient
The difficulty of sharing health data is an old problem, one that is not helped by simply adding a new source of data – the connected patient – in a new data silo. The fundamental problem is not merely technical, either.
In healthcare, all our relevant personal health data is scattered across a disjointed spectrum of specialists, clinics, networks, and fields of medicine. Within each silo of data storage there is a proprietary system for coding, arranging, and accessing that information. Until that information can be seamlessly integrated and shared, healthcare delivery itself is similarly segmented. The dream is to turn this checkerboard of disciplines and professionals into a Continuum of Care.
The biggest breakthroughs in modern medicine are likely to come not from discrete approaches to healthcare, but from collaboration. The nascent field of neurocounseling, for example, combines the physical science of neurology with the social science of therapy to make greater use of both. Active scanning of a patient’s brain allows counselors to identify exactly when and where their therapeutic approach is triggering changes. When it comes to breaking down destructive habits like addiction or repairing a psychological trauma, therapists can literally see what works, and track patient progress.
That kind of collaboration is helped by having the radiologist and the counselor in the room together. It doesn’t transcend the barriers that keep health data from being contributed to an EHR, and subsequently accessed by the various clinicians along the continuum. Unfortunately, we can’t just create a new field every time we need healthcare professionals to collaborate.
When clinicians are not the room together, they need a way to look at the same “picture” of patient health, and filter the relevant information through the lens of their respective medical specialties.
This is where the need for open APIs (Application Programming Interfaces) comes in.
Unlike other industries, opening APIs in healthcare is not about monetizing or commoditizing data, but about giving developers a way to move data – to finally link up the Continuum of Care through the sharing of data.
Every wearable device has its own optimized mobile app. APIs are what allow the data from each app to become mobile, and shareable. Absent an open API and physicians cannot easily (and legibly) bring that data into their EHR platform. At the moment, there is no standard EHR format even to allow physicians to easily share their EHRs with any other clinicians, much less integrate any information collected by an IoT device – other than doing it manually.
What this all means is that healthcare in the U.S. is struggling to bridge a communication gap. The challenges of sharing information efficiently obstruct collaboration. This leaves patients out of the loop where their own care is concerned, and segregates medical disciplines and practitioners. Holding up the free flow of open APIs is an ongoing debate over who owns – and is responsible for maintaining – patient health data.
In the meantime, the practice of medicine continues, and ad hoc solutions to the need for data mobility proliferate. The buzz around wearables and the IoT demonstrates that people are ready to participate, volunteer their data, and reap the benefits these future technologies promise. Before this promise can be fulfilled, there is still much administrative and technical heavy lifting to be done in healthcare.
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