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Patient or product?
The data universe is growing at an astonishing rate, offering unprecedented insights into every aspect of healthcare. Rob Munro examines the Big Data explosion and what it means for providers and investors
Big Data for many people equates with Big Brother. The recent exposés of dubious practices by social media companies revealed users being targeted by everyone from mainstream political parties to Russian trolls based on sophisticated analysis of online behaviours, preferences and opinions. Psychological profiling and so-called ‘microtargeting’ feels intrusive and sinister. Indeed, social media users lured into giving away every detail of their lives to platforms which offer seemingly limitless functionality ‘for free’ must now consider themselves products rather than customers.
But however uncomfortable it may make us, Big Data is here to stay. But what does that signify, what is the scale of the information circulating in the data universe? To answer that question, it’s necessary to consider a few numbers.
Just 15 years ago, The International Data Corporation (IDC) estimated the size of the digital universe to be around 130 exabytes. By 2017 it had grown to 16,000 exabytes or 16 zettabytes. In 2020, the IDC estimate the it will be in excess of 40 zettabytes.
If you’re not familiar with the taxonomy of data metrics, now might be a good time to brace yourself. Like the physical universe, the data cosmos is almost beyond comprehension in its scale. The number of bites in a zettabyte is one followed by 21 zeros – large enough to accommodate 36 million years of high definition video. And there are currently the equivalent of 5,200 gigabytes of data for every one of the seven billion human beings on earth.
And in common with our ever-expanding physical universe, the data universe is growing at a phenomenal and quickening speed. By 2025, the IDC estimate that a staggering 463 exabytes of new data will be created on a daily basis.
Big data and healthcare So what does this ineffably vast and growing universe mean for healthcare and where do the investment opportunities lie in the brave new world of Big Data?
Using artificial intelligence to analyse these huge datasets is at the heart of the coming revolution in healthcare and nowhere is there greater potential than in the area of diagnostics. For example, research recently published in Nature involving collaboration between Google Health, DeepMind, Imperial College London, the NHS and Northwestern University in the US found that computers using AI to analyse mammograms could detect breast cancer more reliably than expert radiologists.
In fact the AI algorithm outperformed both the historical decisions made by the radiologists who initially assessed the mammograms and the decisions of six expert radiologists who interpreted 500 randomly selected cases.
The potential for rapid and reliable clinical judgements made by machine is a holy grail for healthcare services worldwide and is coming ever closer. A scenario where a patient is admitted as an emergency and given a CT scan in the middle of the night with the results interpreted and treatment decisions made without human intervention is maybe five years away.
The engine driving such revolutionary change is machine learning. In the Nature research, the algorithm used was developed after analysing nearly 30,000 mammograms. ▶
DATA UNITS COMPARISON
Unit Value Size
bit (b) 0 or 1 1/8 of a byte
byte (B) 8 bits 1 byte
kilobyte (KB) 1,000 bytes 1,000 bytes
megabyte (MB) 1,000 2 bytes 1,000,000 bytes
gigabyte (GB) 1,000 3 bytes 1,000,000,000 bytes
terabyte (TB) 1,000 4 bytes 1,000,000,000,000 bytes
petabyte (PB) 1,000 5 bytes 1,000,000,000,000,000 bytes
The lure of the NHS To teach machines to make clinical decisions, they must be fed with huge amounts of information and that has to come from somewhere and that is why the UK’s universal health service, with its wealth of health data, holds such an attraction for healthcare companies.
Adam Steventon of the Health Foundation says the speed at which we are capturing personal data is a double-edged sword, providing both opportunities and challenges. Writing in his blog recently, he said: “Data are being used to drive innovation in ways that can revolutionise healthcare, helping us to detect disease much earlier, move care closer to home, and encourage health promoting behaviours. The same technology also has the potential to exacerbate health inequalities, decrease social connectedness, and increase demand on an overstretched health and social care system.” Steventon also points out the seeming anomaly that, while being one of the largest universal health systems in the world, the National Health Service is grossly inefficient in its data gathering and analysis.
“As a universal health system, the NHS should have the best health data in the world. However, currently data sets are fragmented and incomplete, offering only a partial view of the health and ▶
experiences of individuals. Social care data are underdeveloped,” he says.
Of course many commercial organisations would love to help the NHS resolve its issues in exchange for a significant slice of the data pie but there are problems with public confidence. Google for example encountered difficulties when it acquired the UK AI company DeepMind last year. DeepMind had contractual arrangements with several NHS trusts to provide services and research and there was widespread concern over the tech giant gaining access to patient data.
University College Hospitals NHS Trust, one of the organisations involved, was quick to reassure the public that their data was safe from commercial exploitation. In a statement it said: “We will retain control over the anonymised data and remain responsible for deciding how it is used,” adding: “The anonymised data is encrypted and only accessible to a limited number of researchers who are working on this project with UCLH’s permission. Access to the data will only be granted for officially approved research purposes and will be automatically audited and logged.”
Steventon at the Health Foundation says more needs to be done to build public confidence if health data sharing is to become a reality.
SIZE OF THE DIGITAL UNIVERSE
40,000
40,000+ exabytes
Data (exabytes) 35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
16,000 exabytes
130 exabytes
“The system needs to develop skills and capacity to ensure the NHS (and therefore patients) obtains the right value from any commercial data sharing,” he says. “Data outside of the health and care system can also be valuable, for example data held by social media or health technology companies, so we will need to broker new kinds of data sharing. We also need to build public trust for the use of data.”
Mindy Daeschner of Daeschner Consulting questions whether the use of AI will lead to more personalised medicine and a move from ‘sick care’ to ‘health care’ as trends and behaviours that predict illness become apparent.
“The global AI market is expected to experience massive growth with revenues increasing from $9.5 billion in 2018 to $118.6 billion in 2025,” she says. “Corporate America is expected to capture $16 trillion in AI gains over the next decade, so AI is going to have an impact across the board. But, policy and funding will be the big drivers for changing how we view healthcare. Personalised medicine needs a holistic approach and right now healthcare is still very siloed. Culture must change as those that collaborate will be better positioned and that means governments, industry and healthcare providers. Key to all of this is data. It is not an afterthought, but how value should be derived.”
Daeschner predicts that the tech mantra to “move quickly and break things” will apply to the new healthcare landscape, but comes back to the issue of trust and confidence in who will do what with all that personal heath data. “We are going to see disruption and convergence that will challenge existing business models, so the transition is going to be painful, but ultimately rewarding. To understand the future opportunities, we first need to look at the healthcare model from the patient’s perspective verse provider or payer. Where is this data coming from? What value will it create? Can we democratise it?”
Changing the relationship So where does all this data come from and what are the barriers for companies keen to enter the market?
“There are three primary sources of big data in medicine,” says Daeschner. “The first source of big data, including electronic medical records (EMRs), claims and billing data, imaging data, and pharmacy data, is providers and payers. The second is omics, including genomics, proteomics, and metabolomics. The third is patients and non-providers, ie, data from smartphone and internet activities, sensors, and monitoring tools.” She points out that research shows that in the future, about two-thirds of all medicalrelated data will come from patient-created sources.
Daeschner feels the need to maintain accurate datasets will lead to a renewed, more equal relationship between healthcare providers and patients.
“The biggest barrier is access and interoperability, but this is changing,” she says. “There are also issues with data quality in many areas of healthcare with incomplete or up-to-date records, lack of information in key areas and generally just poor data, which also presents a legal issue as to liability; who is responsible for keeping this data up-to-date and accurate? The best person is the individual, as they have the biggest stake in owning their own health. The move to personal and portable health records will play a big role in the move forward regarding personalised medicine.
“Although social media has been in the spotlight, we should not forget there have been big data breaches from the NHS as well. Patients wants great healthcare, and they want convenience. They will give access to their data if it means they can get these. They are already doing it in many other sectors, but it must be their choice.” ▶
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Justin Crowther, head of UK healthcare at investment bank Alantra, also believes that the way providers and patients interact is due for a radical change as the data becomes increasingly commoditised.
“Health needs to start thinking about people as customers. Health and social care need to be changing their language,” he says, adding that providers will seek to foster long-term relationships with patients in the manner of banks and other service-based industries. ▶
Gazing into the crystal ball Octopus Ventures is spending a lot of time gazing into the crystal ball of healthcare investment, and Will Gibbs, a partner in the company’s future of healthcare team believes that data will drive innovation and transformation across the board. One area he points to as being ripe for AI innovation is fertility services. While traditionally the emphasis has been on female difficulties with conception, data analysis and prediction now gives clinicians the opportunity to investigate the relationship between sperm and ova and to understand the variables involved.
Gibbs cites Mojo, a UK-based start-up, as an example. The company intends to launch a service to fertility clinics this year that will automate the procedure for producing sperm counts in the first stage of a strategy that will identify which sperm characteristics are associated with successful conception.
Chief executive Mohamed Taha says that the data will help clinicians to understand “what is a good sperm, what is a bad sperm”.
Healthcare versus sick care The rise of Big Data will transform every aspect of healthcare across the globe from epidemiology, diagnostics, treatment, health economics and management, but perhaps the most significant change will be in the way we take responsibility for our own wellbeing.
The current interventionist medical model emphasizes the role of the patient as a passive recipient of care who consults a ‘expert’ clinician when symptoms of disease have become apparent. This fundamentally unequal relationship at best leads to a sense of disempowerment and at worse, an adversarial, sometimes litigious, environment. “Let’s face it, the cost of care and clinical negligence has continued to increase at an alarming rate,” says Daeschner. “We have to do things differently. Solutions will be created to drive transparency, real-time decision-making and embed continuous learning. Patients and providers will be partners, not adversaries.”
“Patient-created sources (that is, data from smartphone, internet activity, sensors and monitoring tool) will be generating about twothirds of all medical-related data in the next decade. The pendulum is swinging in the patient’s direction.
“It requires a different approach and one focused on the goal, not the transaction. It requires collaboration, as the siloed approach of today isn’t going to produce the value or the benefits we need from pharma and healthcare providers. Solutions will be tailored given our medical history, our biology and our behaviours.” All good stuff, but these goals will be affected by resource pressures and workforce issues and Daeschner for one is clear that we have a mountain to climb. “We cannot magic up more trained resource and we are heading for a crisis as there will be a global shortage of qualified healthcare workers,” she says, but adds that automation and innovation may mitigate these growing pressures.
“Referral and screen programmes are going to be transformed as are waiting times. Autonomous training and robotics will proliferate. We will have quicker access, faster diagnosis, better outcomes,” she says.
An opportunity and a challenge In the ideal healthcare world, always-on data that prioritises interoperability will promote closer collaboration between care givers and care receivers. New service models will be offered both by existing operators and disruptors. Interventions and treatments will be better targeted, simpler, safer and less expensive.
We will have access to and, crucially, own our health data, making real and informed decisions about our care and treatment.
But if this model is to work, investors must back businesses in which the public has confidence. Big Data is presenting us with a huge opportunity to change the way care is delivered, but the stakes are high and earning, and keeping the trust of increasingly empowered consumers has to be the highest priority. n
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