Guest Blog by Dr Michelle Tempest, Partner at Candesic, Health & Social Care Consultancy
One of the most important paradigms in healthcare is the fundamental shift in the doctor-patient axis. The old fashioned paternalistic doctor-patient relationship, where the doctor held the balance of power and only shared information with the patient when they thought it was relevant, has been completely turned on its head by digital healthcare. Now each individual can harness the power of technology to store, measure and monitor pretty much everything about themselves, often innocuously via their mobile phone. This means that an individual can collect all the information they want and personalise it to measure fitness, wellness, mood, weight, menstrual cycles; there is not much you cannot track about yourself, if you so wish. In fact there is so much interest in health consumer apps that a central National Information Board has been set up to accredit and kite mark apps, devices and digital services.
This inescapable, irreversible shift to ‘patient power’ means that every person has the ability to become an expert about their own health. Professor Eric Topol in his book ‘The patient will see you now’ describes this paradigm as the death of medical paternalism and the democratisation of healthcare via the ‘quantified self’.
How will medical teams cope with the on-coming tsunami of information?
The development of this personalised digital explosion poses the frequently quoted data quandary of the 3 V’s: Volume, Velocity and Variability. Such vast data quantities will soon reach Exabytes amounts. To put this in context it would take a single doctor several lifetimes to read this amount of information, let alone process it. So, ‘Artificial Intelligence’ learning algorithms will naturally come into play employing parallel computation and parallel processing. Medical teams will want immediate access to ‘what has changed’ or ‘what is an outlier’, whilst healthcare consumers will want to link their own personal data feeds to help with early diagnosis. Similar such feats are already emerging in financial technology (FinTech) by linking professionals and customers more directly to banking algorithms.
The doctor of the future will have to be more like Sherlock Holmes rather than his associate, Dr Watson, who was frequently sent to check up on one variable at a time. Future Sherlock’s will need to build up pictures of data to help solve medical riddles.
As yet clinical teams and IT systems are not set up to do this, so how will they succeed?
One current stumbling block is that data is stored in siloes with little inter-operability. Data is collected in a linear fashion as if it is preparing to help solve a 2D puzzle. But Sherlock Holmes would never have found ‘who done it’ unless he had developed a 3D way of problem solving. To solve such riddles there is a journey that is yet to be taken.
It is actually a similar journey that is currently underway across the rest of the health and social care setting, where separate, siloed disciplines of: Specialist, hospitals, mental health, community, care homes and care-in-the-home need to be integrated. Data should be at the forefront of this journey and as care moves from being reactive to proactive, the same step change has yet to happen in MedTech.
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