Healthcare's Data Tsunami

There are huge opportunities to learn from this wealth of data. It can be harnessed to help solve a wide range of problems from accelerating drug discovery to optimizing treatment protocols to tackling operational challenges in healthcare delivery.

What is more, as Big Tech moves deeper into the healthcare space and Big Pharma increasingly evolves towards a “big data” business model, the competition to leverage this tsunami of information is intensifying.

Murray Aitken, the Executive Director of the IQVIA Institute for Human Data Science, believes it means the world is embarking on a new era of person-centric care that will see clinical science bond with data science in a way that has never happened before.

“There are enormous opportunities to use data for improving healthcare, whether that’s in terms of individual patient outcomes, better population health or contributing to the sustainability of healthcare systems,” he said.

“It can provide insights into the underlying biology of health and wellness, as well as help develop new therapeutics to treat diseases and ensure they are used in the optimal way.”

After more than 30 years of tracking the healthcare industry, Aitken thinks the digital transformation of the sector has now reached an inflection point, with the pandemic acting as an additional catalyst by forcing the adoption of a host of digital tools from the rollout of virtual clinical trials to the use of telemedicine for care delivery.

Yet this rapid evolution of the health data economy brings not only opportunities but also risks. Privacy concerns mean the use of digital health information is intrinsically sensitive, obliging companies involved in the field to navigate a narrow path between optimizing outcomes and building the strictest possible protections for highly personal datasets. It is a reputational tightrope—and the demands of the public are high.

A recent Brunswick Insight survey highlights the dilemma. Based on answers from more than 1,100 well-informed members of the public in seven global cities—London, New York, Singapore, Tokyo, Hong Kong, Paris and Frankfurt—the survey starkly reveals the hopes and fears engendered by the health data boom.

On the plus side, the poll found that 70% of respondents supported greater healthcare data sharing between the public and private sector, and 68% endorsed increased use of patient-level data for the development of drugs and medical treatments. But at the same time there was enormous concern about data privacy, with 87% of respondents believing that protecting patients’ data should be a priority for healthcare company CEOs—placing privacy on a par with the need to invest in research and development.

Clearly, competence in data management is a prerequisite for any business handling healthcare data and companies are under intense pressure to develop a strong privacy culture that ensures security for information, without impeding its exchange.

If the balance is right, the potential to do good is huge. Data can save lives, as demonstrated over the last two years by the scarring experience of COVID-19. Rapid data-sharing has allowed experts to track the emergence of coronavirus variants around the world, while pooled clinical and virological information has helped scientists develop vaccines and therapeutics to tackle a previously unknown pathogen at an unprecedented pace.

Applied beyond the pandemic, leveraging health information at scale could unlock fresh insights into everything from cancer to Parkinson’s disease, by spotting patterns between disparate genomic, biological, health and wellness records.

For many drugmakers, much of the investment today is focused on “real-world data” (RWD), which is collected outside traditional randomized clinical trials, the current gold standard for judging if a medicine works and is safe. The ability to capture the experience of real-world patients, who represent a wider – albeit non-randomized – sample of society than the relatively narrow selection enrolled into clinical trials, is increasingly useful as medicine becomes more personalized.

While data collected by mobile phones, wearables and other biosensors is a significant help in this RWD effort, the information generated from such devices can also generate more fundamental insights.

“The interpretation of data from our devices can open up vast opportunities to understand how diseases are triggered and how they progress,” said Aitken.

Still, harnessing the full potential of all this information remains a work in progress. Partly, this is down to not understanding exactly what data is needed to build a complete picture of an individual’s health prospects. While continuous monitoring systems offer additional datapoints, it remains difficult to objectively assess factors such as diet, stress and social interactions that are known to affect health outcomes.

Another obstacle is data quality – not only because of sometimes incorrect inputs, but also because of lack of interoperability between different systems and the challenge of making unstructured data comprehensible and usable.

“Yes, there’s a lot more healthcare data out there, but the quality of that data remains a challenge. And quality matters when it comes to health because if you don’t get it right then the consequences are significant,” said Aitken.

Working out how to overcome these issues to build a data network that is comprehensive enough to provide a wide range of answers may be feasible. But it will only become a reality if citizens are ready to participate in data collection, rather than opting out.

Since health data is inherently vulnerable to both accidental leaks and cyber-attacks, building trust in privacy and security will take more than warm words. In some cases, it may also require the development of new mechanisms to manage access. Sweden’s electronic health records model, for example, allows citizens to view their medical data and see who accessed it on a national electronic health record. In Britain, meanwhile, the OpenSAFELY open-source software platform lets researchers write code to analyze health data without ever viewing the actual raw records.

For Aitken, the bottom line is clear: there needs to be clear communication and transparency about what data is being captured, how it is being used and how privacy is being upheld.

“Trust in the eco-system is essential. There is enormous support among patients for their data to be used to improve treatments and benefit others, so it is crucial that isn’t lost because of privacy concerns.”

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Ben Hirschler is a Senior Advisor based in Brunswick’s London office and a former global pharmaceuticals correspondent for Reuters. 

Charts by Peter Hoey.