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The digitisation of everything to do with health is about real-time collection and interpretation of information. Principally, it’s about the precision, accuracy and the accountability of data.

The digitisation of everything to do with health is about real-time collection and interpretation of information. Principally, it’s about the precision, accuracy and the accountability of data.

The word revolution means a forcible overthrow of a social order, in favour of a new system. In healthcare, the word is used all the time but has anyone actually explained what this new system might look like? Does anyone actually know?

Try asking the question at the next gathering of uber smart, tech savvy people who know about the so called healthcare revolution. See if they can define the healthcare revolution and explain this new system. I guarantee the answers will be circular, not linear. There will be lots of “if” and “then” and “could” and “should” words. Their comments will be difficult to contextualise. They will most likely terrify or excite you but for sure they will confuse you.

What most of us want to know is will this revolution be a good thing or a bad thing?

The answer is “maybe”.

The digitisation of almost everything is creating a form of revolution everywhere. It’s causing a revolt amongst a number of healthcare stakeholders. Clinicians and physicians fear their role will be replaced by bots and algorithms. Breaking news; it’s already happening.

Regulators are having to scratch their heads to find ways to qualify outcomes and claims because the validity of the old ways is weakening every day as new paradigms surface and are adopted as mainstream.

Providers of digital solutions in the form of bots, apps, medical devices, algorithms and therapeutics are subject to excessive yet often unproductive scrutiny. This delays their adoption and blocks the building of the data set and the ultimate integration of data and devices.

Fear not; we have witnessed other revolutions. The industrial revolution which affected so many sectors, like manufacturing and supply chain, created a major disruption and a new world order. Nothing to be affeered of there.

Then during the ’50s and ’60s IT revolutionised things like accounting, payroll and HR.

So when it comes to healthcare, be prepared because this particular revolution is tantamount to the deconstruction of medicine as we know it.

Thanks to movements like Quantified Self, the Human Genome Project and other health hacking organisations, the patient and their personal profile are starting to determine decisions.

No cookie cutting here. “I am as unique as my DNA” … So, don’t try clustering me into the group of 200 patients who formed the research cohort that secured the FDA approval in 1963. I either want big data to justify the protocol (i.e., millions if not billions of data points on the subject to prove its efficacy) or I want it to be about me and just me.

And not forgetting that trusty GP, Doctor Google; medicine is now patient directed rather than doctor directed.

The digitisation of everything to do with health is about real-time collection and interpretation of information. Principally, it’s about the precision, accuracy and the accountability of data.

Personalised, digitised and democratised.

Big data collects such a huge amount of information, it requires algorithms and machine learning to interpret it. The collection and interpretation might seem messy, but the sheer amount of data collected makes it worthwhile to forgo exactitude, especially when it comes to healthcare.

Bed-less hospitals, mobile virtual treatment, bots taking the place of surgeons, radiologists, oncologists and every other specialist you can name. Greater accuracy with diagnostics and big data making decisions which were once made by the doctor at the bedside. A single decision maker versus a billion decision makers.

I’m not so clear; so who do I sue?

To this extent, Artificial Intelligence is the cornerstone of this revolution. It isn’t yet an entity in its own right (one whom you can sue, yet) but it is becoming as respected as the health professional. AI is becoming the doctor of choice because it able to coalesce the data that is being collected from “a billion brains” to analyse across data sets of such magnitude, it eradicates the need for individualisation by comparing and contrasting the individual against a huge and continually growing data set.

Your chest x-ray or the MRI on your brain will be interpreted based on billions of other x-rays and MRIs. So the opinion expressed as to diagnosis and therapy is not just that of your doctor and his or her limited experience but that of the tens of thousands of doctors and their patient records collected over decades, integrated into one diagnostic tool.

So, there we have it; big data is the collective intelligence generated by billions of brains and growing. It’s counter intuitive to the notion of individualisation, but on the contrary, personalised medicine somehow does fit into this world.

Confused? Let me explain a bit more.

Think about the commercially bought wearable.

The Fitbit is collecting billions of data points across the globe about fitness and movement. It also knows where you are, where you live, your social media status, your sleep patterns, weight and height and with a very simple stretch of data analysis, your risk of diabetes or cardiac disease. It might hold more valuable and powerful healthcare data than a government. Will corporations hold more information about you than the government or your insurer?

Mobile, body-worn healthcare devices are the fastest growing sector of wearables. They will outstrip all other wearables by 2019, just two years from now. The question is, what happens to all the so called big data they collect?

The underpinning system that is fuelling the healthcare revolution is big data. To understand big data and its power, you have to first understand what small data was.

Small data was part of the analogue world. Since the 19th century, it’s what science, research and medicine was based on. The protocol of taking small samples and investigating against that small sample was regarded as acceptable and even robust. Where n might equal 30 or 50 or 100, things were easy to prove. Getting a therapy, diagnosis or treatment protocol was simple when the test group was a few hundred or even a few thousand.

 The invention and development of Electronic Healthcare Records has been done by corporations who see this as a business rather than a critical strategy for healthcare. Are they fit for purpose? Depends what purpose you are referring to.

However, when the base line of data is small, absolute accuracy is required. Small data requires a narrow classification of investigation and therefore defines or at least limits the outcomes. But it was with small samples we have made major healthcare decisions when it comes to treatments, drugs and general protocols.

Now enter big data. It seems messy but it collects such a huge amount of information, sometimes randomly, that it requires algorithms and machine learning to interpret it. This vast volume of data is not possible without digital technology. Without digital technology we couldn’t collect it in the first place and even if we did, we couldn’t interpret it. The collection and interpretation of big data might seem, again, messy, but the sheer amount of data collected makes it worthwhile to forgo exactitude, especially when it comes to healthcare.

All this data collection and interpretation creates a new risk for society: cyber security. This element of the revolution isn’t remotely solved.

Domestic, criminal, international; the black-market risk of data leakage and data theft is a daily reality. Literally 1,000s of healthcare environments are hacked daily. It’s costing billions every year and hacking in healthcare is growing at 200% in the US. Australia is listed as second in world for healthcare data security break ins/theft, second only to the US.

Control of the information has all stakeholders up in arms because we don’t have the answers yet. We can’t guarantee we actually know who has the right to the data, who owns the data.

Should your dentist know your reproductive status? Should your insurer know your metabolic status? Should your gym know your cardiac history?

The answer is another “maybe”. But if you as the patient own the data, are you providing this data to your health professional and if so, under what legal instrument? And what about that Fitbit your wearing? Have you licensed Google to access your data from Fitbit to use on its population studies, regional data augmentation or simply to hold your personal data?

The practical challenge of harnessing big data can be summed up in one word – integration. How to corral the data collected and ask the right questions? How to centralise all the data collected from all these medical devices and make sense of it? Who is building the algorithm to interpret this information and who will have access to it? Will it be monetised and if so by whom?

The answers to these questions are not yet defined. There is no one body taking principle responsibility on these matters. Where corporations have greater data than governments and where ownership of that data is still foggy, where regulators are struggling to keep up with innovation and public demand, the control of big data is murky. You have to expect chaos.

Let’s look at one of the most practical and tangible elements of the healthcare data revolution: the Electronic Healthcare Record (EHR). When you know about the complexities of the revolution it’s no wonder we have resistance to its adoption from so many corners. That’s because it’s all about the big data; it’s collection, interpretation, diagnosis, triage, insurance, monetisation.

The collection and importantly, the actual interpretation of medical history of the patient is a fundamental element of the revolution. Knowing all about you, your conditions, surgeries, treatments and therapies feeds into risks, costs and qualifications. You may wish this information to remain private but this is unlikely. You are forming part of the billion brains; you can’t avoid it because your data will be mined. This record will follow you wherever you go within the healthcare system, for life.

The EHR risk is all about access. Will it always be anonymised? Perhaps. Will it get hacked, stolen or even sold? A resounding “yes!”.

Whilst an Electronic Health Record sounds like a sensible and easy protocol to follow and the benefits of real-time patient information are self-evident, why has it not been taken up ubiquitously around the world?

Why don’t you have one?

It should be noted that to date, the only country that has been able to implement cradle to grave electronic healthcare records is Denmark. A small population, totally government controlled country.

In the rest of the world, EHRs are fundamentally the territory of private enterprise, albeit governments are trying to implement policies and laws to control their deployment.

Their invention and development has been done by corporations who see this as a business rather than a critical strategy for healthcare. So are they fit for purpose? Depends what purpose you are referring to.

The EHR is actually an obstacle to the deployment of technology in healthcare and in particular bio feedback medical devices because they rarely integrate seamlessly with the digitally generated data.

So some data is automated or instrumented and other clusters of data are manual. Arggh…

The introduction of medical devices that collect valuable data about a human has become the one of the biggest integration challenges for the EHRs. If the EHR is attached to a person or group of patients, the data collected from the medial devices they wear must find a place on the platform.

This is where there is major dispute.

How does that data get onto the EHR platform, who owns it once it’s there? How does the big data on the EHR platform get interpreted and who gets to monetise it? Does the medical device corporation own the data generated by its device and patented algorithms? Does the owner of the device or patient own the data which is placed on the EHR? Who is the beneficial owner? Who is responsible for its security? And what about the regulators and legislators? Will they test efficacy?

In any event the integration of all the random data collected from body-worn medical devices has to be corralled somewhere, doesn’t it?

…Or does it?

The good news is that you can continue to love your GP, but realise that the billion brains are already working hard on your healthcare world and they may not agree with your beloved GP.

You could call them the serfdom of the revolution. Ready and willing to take the jobs of others and to work 365 days a year. Preparing to take over the aristocracy and change the ecosystem entirely. However whichever way to cut it, this revolution is reaching maximum entropy. It will remain so until there is consolidated consensus by the many stakeholders willing to collaborate rather than compete. This will only happen if there is agreement to base the revolution on concepts and regulations that feed the greater good and force the formation of a robust infrastructure of rules, laws, and the standardisation of efficacy and its process.

Written by Philippa Lewis, Managing Director

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