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The digital health data race

Four lessons: The digital health data race

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Four lessons from the global digital health data race

By: Dr. Edward Fitzgerald

The health sector has long been recognized as a leader in amassing data, from comprehensive Hospital Episode Statistics to world-class clinical registries - but without necessarily harnessing its full potential. As digital transformation finally catches up with healthcare, and productivity and efficiency pressures grow around the world, now is the time to double-down and deliver on this potential if patients, and providers are going to benefit from the advent of digital health.

Data as a precious resource

Technology companies in particular have long viewed data as `the new oil' and healthcare is starting to recognize its huge promise. Across the healthcare spectrum, an enormous amount of data is generated via medical health records, test results, diagnostics and wearables, coupled with demographic data from multiple sources. The NHS's data warehouse, for example, contains details of all admissions, outpatient appointments and Emergency Department attendances at hospitals in England.

Patients are also generating more and more data from wearable devices related to exercise, lifestyle and chronic conditions. Such a fragmentation of sources begs the question as to who owns and/or controls the data. Producing meaningful insights is another big task, to collate data and use it to improve individual and population health.

Understanding the true clinical and financial value of health data is also difficult when its future application is uncertain. Yet a number of health systems, and indeed nations, are arguably ahead of the game. Israel recently announced an investment of US$280 million to digitize population health data and make it available to researchers and private companies. Tellingly, Prime Minister Benjamin Netanyahu estimated that the country as a whole could earn as much as US$600 billion from the digital health market, representing a healthy return on their forward-thinking investment.

The South Korean government is expanding subsidies and support for medical big data initiatives, consolidating its hospital data to establish a national database - including collecting genetic and biometric data for 10 million patients. Again, the goals are economic as well as health-related, with an aim to create 35,000 jobs in health and medical research and grow the country's share of the lucrative global bio and healthcare sector from the current 1.8 percent to 4 percent by 2022.

In a new global healthcare data race, health systems - and economies - need to be careful they aren't left behind.

Harnessing health data for the national benefit is likely to require some bold decisions, and considerable resources, all of which takes time and political will. Based on my work with clinicians, managers, and researchers internationally, I've identified four key areas of focus:

  1. Calculate the value of healthcare data: It's hard to know how much to invest in digital - and where to focus investment - without understanding the value that is generated. As we've discussed, both Israel and South Korea have attempted to quantify the value of health data. As further evidence of data's worth, Pharma giant Roche is paying out US$1.9 billion to acquire Flatiron Health, an oncology data company that captures data from hospitals and health centers. Roche is confident that the insights from this data can boost its R&D by accelerating drug development, better identifying candidates for interventions, understanding the impact of drug treatments more clearly and, ultimately, reducing the time taken to develop new products, thus getting drugs to market faster with a longer effective patent life.

    The perception of this value naturally depends on whether you are a patient, provider, industry, or government. Nevertheless, it is essential to try to quantify the benefits of greater prevention, improved diagnostics, more personalized therapies and efficiency gains from data-enabled self- and remote care. A good starting point is to calculate the current costs of collecting, cleaning, linking, curating, storing, and sharing data. Some of the principles behind value based pricing should also enable the NHS to gain a clearer picture of the value generated.

  2. Create a single access point: The fragmented way in which health data is acquired and held makes it difficult for academia or industry to access and work with health information. Different organizations each hold different layers of data, with variable linkage across the full continuum of care. It's a major challenge to find out where relevant data presides and who to ask to get hold of it. Simplifying the access procedure should be good for the NHS, for patients and for those looking to work with the data. With a single access point, and an agreed protocol for accessing and using data, researchers and other professionals are more likely to consider turning to a particular health service for data. Standardising in this way would also accelerate access, avoiding the back-and-forth as a new access agreement or contact is drawn-up every time, and having to deal with multiple organizations. In South Korea, central consolidation of health data is underpinning the country's strategy to grow market share of health and life sciences research.

  3. Get a fair deal for everyone: Health data is a unique and precious asset, with added complexity in public health systems like the NHS, where it is collected from patients at taxpayers' expense. However, many external organizations are likely to pay for this data to boost innovation, and will be looking to make a reasonable return on their investments. Some may be large, established international businesses while others may be small start-ups, and all will want a fair deal. For instance, a research company that processes data via AI may seek patents for their insights - but at the same time the health service may expect some reward for its contribution as overall data owner. One size won't fit all, so a range of transparent business models for intellectual property need to be agreed, in the form of data licensing, equity or revenue shares. Exclusivity is to be avoided where possible, to ensure that data can be re-used by multiple parties - whilst respecting the outputs. Providers should learn carefully from good practice globally, while recognizing that the legal position around data ownership and confidentiality can vary markedly.

  4. Demonstrate value to patients: International research by the European Commission recommended a communications strategy covering big data in healthcare, to encourage a positive public mindset. Communication on enabling the digital transformation of health and care in the Digital Single Market; empowering citizens and building a healthier society, European Commission, 25 April 2018. To get the most out of data, healthcare providers should first ensure that patients understand and support the use of aggregated, anonymized health data. Yet trust has already been undermined by adverse media headlines, such as the theft by hackers of personal data of 1.5 million people from a government health database in Singapore.

    The good news is that a recent KPMG survey (PDF 1.14 MB) shows that of all the organizations trusted by the British people to use AI, the NHS is number one, with 56 percent expressing faith in the institution. The bad news is that 44 percent do not trust the NHS - while only 15 percent trust pharmaceutical companies - the very organizations most likely to be involved in using data for innovation. In another piece of global research from Harvey Nash and KPMG, only 24 percent of healthcare CIOs rate their organizations as “very effective” at using digital to enhance the customer experience.

    An uphill battle is on the cards to convey the benefits of data sharing, which calls for more than just marketing messages. Patients should be engaged in genuine dialogue, to reassure them that they are the ultimate data owners, and that the way data is used can lead to clinical breakthroughs, improved outcomes and more efficient healthcare provision. Healthcare customers need to be treated not as data assets to be exploited, but as co-players in the quest for improved healthcare.

These four steps can only be effective if health services and their data partners have effective data governance, so they understand where their data lives and how to access it; have effective processes to protect data; and acquire and develop the right resources and skillsets to manage healthcare data (for more on this see KPMG's paper, Data governance: driving value in healthcare).

In a competitive global marketplace, healthcare providers and health systems should learn from the best international initiatives and adopt a world-leading approach to working with, and providing access to, high quality health data. Indeed, they have a duty to do so - to patients, who stand to benefit from improved treatment and administration; to payors, who have funded existing data collection in full or in part; and to academia and industry, who can drive national investment, growth and employment from developing new innovations and applications. However, time is not on our side and urgent action is required now.

Dr. Ed Fitzgerald is KPMG's Global Healthcare Executive, and brings 12 years' clinical experience of hospital-based work in the NHS and international health systems prior to KPMG. Ed leads global healthcare research and thought leadership, working internationally to support KPMG's health practice across more than 45 countries. His experience of the world's healthcare systems and services helps him share the latest best-practice insights with clients globally.

Read more from Dr. Ed Fitzgerald on Rerform, as he shares international insights to specifically help the NHS harness health data.

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