Open Data And The Fight Against Disease

Recently the Open Data Barometer produced its fourth analysis of the state of open data around the globe.  The index ranks governments on a range of factors, including the maturity of its open data initiatives, the implementation of open data programs, and the impact those programs have had.

The index, which has the United Kingdom on top of the pile, highlights the variability in open data around the world, both within the developed world but also the developing world.

Nowhere is the importance of open data as critical as in healthcare, and a recent paper from the European Commission highlights some of the benefits, and challenges, of doing so, with a number of fascinating case studies from across Europe.

Playing catch up

Healthcare is however an industry that’s largely playing catch up in comparison to other sectors.  A paper published earlier this year by the University of York highlighted the glacial progress being made in the digitization of patient records.

“It is difficult for those outside of the NHS system to visualise the scale of this project; there are hundreds of departments and healthcare organisations, using different IT systems, trying to share important information about a patient,” the researchers say.

“One way of understanding the complexity, is if we imagine inviting a number of friends to an event using one system, a text message for example, only for them to post their answers back on several different portals, Facebook, voicemail, and so on; this would become a difficult communications exercise.”

It’s a problem that tech giant SAP are only too familiar with.  Last year they launched the SAP HANA platform to make it easier for healthcare providers to pull in data from multiple sources and help clinicians derive actionable insights efficiently.  Nowhere is this more important than in the field of antibiotic resistance, with diseases showing little respect for national borders, and the smooth sharing of data crucial in the fight against disease.

“We have a growing modern crisis on our hands when it comes to evolving antibiotic resistance, which is both costly and hazardous to our collective health,” said Dr. David Delaney, Chief Medical Officer of SAP Health. “By 2050, the global cost of antibiotic resistance could grow to 10 million deaths and equate to $100 trillion a year.  In order to address this challenge, we need to both improve stewardship of current antibiotics as well as accelerate the creation of new classes of antibiotics.  However, the roadblocks associated with developing novel classes of antibiotics are far from trivial as evidenced by the fact that every currently available antibiotic is a derivative of a class discovered prior to the mid 1980s.

The good news is that advancements in technology have enabled the collection and analysis of massive amounts of data that can help us better understand antibiotic resistance, enhance antibiotic stewardship programs, and accelerate drug development. Artificial intelligence (AI) and machine learning (ML) technologies offer the ability to help doctors more accurately diagnose and treat illness and infection.  As AI tools can more efficiently gather and analyze larger amounts of information, doctors can work in conjunction with technology to identify patterns and treat patients more effectively.  This collaboration between humans and machines demonstrates the true Heroes in the Race to Save Antibiotics.

Data driven healthcare

The improvement potential in healthcare when data is connected and open are tremendous.  A recent report from the Richmond Group of Charities underline this potential via a number of inspiring case studies of improvements to patient care when data was liberated enough to flow freely throughout the patient pathway.

“Healthcare data is one of the NHS’s most precious resources. It allows individuals to be empowered in their own care, medical professionals to improve and tailor individual treatments and the system as a whole to learn and increase its understanding of what causes disease, how it can be prevented and how it should best be treated,” the report says.

Whilst the report shows the immense potential when data is used effectively, it reminds us that the examples they share tend to be outliers rather than the norm.  The right data either isn’t being collected, or isn’t being shared with the right people.

It’s a weakness that has to fundamentally change if the promise of data and AI in healthcare is to deliver the better care and more effective medicines that we so need in order to tackle the tremendous challenges facing the industry.  As Victor Hugo famously said, there is nothing as powerful as an idea whose time has come, and the time is now for this to become less about talking and more about doing.

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