Three ways COVID-19 contact tracing has changed the way we think about patient data management

• Patient data management has been an increasingly important – and hotly debated – issue for Healthcare, Pharmaceutical and Life Science organisations in recent years

• However, the outbreak of the COVID-19 pandemic has rapidly accelerated the conversation, and forced organisations around the world to make big decisions about how to manage patient data 

• One of the areas that’s seen the most rapid development, and the most variation in approaches, is COVID-19 tracing apps

• In this post, we discuss the lessons we’ve learned from how the world has approached COVID-19 contact tracing, and what it means for how we think about patient data management going forwards

Since the outbreak of the COVID-19 pandemic, we’ve seen countries around the world racing to develop contact tracing systems within extremely short timeframes. But has this accelerated demand changed the debate around patient data? We look at three ways the pandemic has changed the way we think about patient data management.

Patient Data Management: An unexpected global experiment

Some countries have opted for highly sophisticated, decentralised digital tracing protocols that handle a wealth of data ranging from individual patient inputs to device locations.

Others have decided to implement more traditional, manual methods of contact tracing – sometimes with no digital component at all. 

While it’s been an anxious and unpredictable time for every country across the board, and a challenge that’s nowhere near solved yet, this race to develop appropriate contact tracing protocols has actually facilitated one of the most wide-scale testing grounds for patient data management and innovation to date.

At this year’s Intelligent Health Summit – where we talked about the rapidly growing opportunity of federated learning in healthcare – the topic of contact tracing was covered extensively, and today, we thought we’d share some of the insights with you. 

It turns out, many of the lessons learned about success and failure in the world of contact tracing are actually highly relevant to the kinds of questions today’s Healthcare and Pharmaceutical companies will be asking about how best to manage patient data. Especially when it comes to building digital healthcare apps for patients.

In this post, we’re going to talk about three of those lessons – with the caveat that this global experiment in patient data management is still very much ongoing.

We urgently need to reconcile patient data privacy rights and public health needs

One of the biggest issues that’s arisen since the wake of COVID-19 is the conflict between the interests of individual patients and wider healthcare organisations. For example, public health practitioners are often mandated reporters – meaning, it’s their obligation to track and contain outbreaks, while warning individuals of their exposure. 

In countries like the UK, this hasn’t been particularly problematic. But as we heard from Anurag Agrawal, Director at the CSIR Institute of Genomics and Integrative Biology, the same can’t be said for countries like India, where stigmatisation is still a very real barrier to getting patients to willingly hand over their data. He explained that even the fear alone of being identified as ‘infected’ has been enough to put people off being tested in some areas. 

Since every patient has the right to their own data privacy, there clearly isn’t a solution in enforcing the handing over of patient data. So how can today’s healthcare organisations get around this issue?

One potential solution is what’s known as the ‘DP-3T protocol’ – short for ‘Decentralized Privacy-Preserving Proximity Tracing’. It’s a method created to preserve data privacy – by not sharing data over a centralised reporting server – while still providing access to critical insights about the evolution of COVID-19 over time. Being able to explain the value of this kind of approach to the general public could help alleviate fears about data sharing. 

However, until that happens, this kind of protocol still relies on patients willingly submitting their data for analysis. So, although the protocol is showing success in countries like Switzerland, Austria and Finland, there’s little chance that it’ll have the same success in a region like India – unless public perception around COVID-19 dramatically shifts. It’s why, Anurag argued, the priority for organisations facing the stigmatisation challenge going forwards should be on encouraging different, more inclusive societal norms, and being more discreet in how COVID-19 patients are notified. 

Why is this an important issue for Healthcare and Pharmaceutical companies to consider outside of a COVID-19 context? Well, if you’re planning on creating a diagnostic healthcare app for patients, for example, then these issues, particularly around stigmatisation, should be front of mind when thinking about how best to manage the data you’re working with – and more importantly, how to communicate your interpretation of it. 

In fact – any kind of digital service or product you create going forwards should be completely centered around providing the best, most comfortable experience for your users. Otherwise there’s a high risk it won’t be accepted or used. On the patient data privacy front in particular, you might want to consider federated learning: a new approach to machine learning that produces valuable insights from patient data – without risking your users’ privacy, 

Transparency of Patient Data Usage Will Be Key Going Forwards

Another issue that Anurag emphasised at the Summit was the need for more transparency and accountability around patient data management. He stressed that it’s critical that people know exactly what their data is going to be used for when they sign up to things like contact tracing apps, and even more critically – when it’s going to be deleted.

Vanessa Candeias, Senior Director at EndHep2030 who also spoke at the Intelligent Health Summit, agreed with Anurag and added that she believes that any patient data collected by healthcare organisations should only ever be ”just enough data to answer to the purpose that the app is being designed for”. And that there should never be an excuse for an organisation going outside of those designated boundaries and collecting, say, “bluetooth data or data on my shopping patterns”. Of course, often there are valid reasons to use the same sets of data in multiple ways (for example, data from the acceleration sensor of a mobile phone could, in theory, be used to diagnose early stages of multiple sclerosis), but her point is that companies should always be transparent about what those are.

Of course, it’s one thing for organisations to set boundaries for the kinds of patient data they plan on collecting – it’s another to make a public commitment to those boundaries. 

Natalie Banner, 'Understanding Patient Data' Lead at the Wellcome Trust, who was also at the Intelligent Health Summit, explained that, “Because we’ve been in this crisis situation, there’s a risk that the established principles of good government have gone out the window. Things like transparency about how data is being used; good accountability; good oversight; clear procurement – in the UK particularly, look like they may have gone out the window.”  

This is why it’s critical that Healthcare and Pharmaceutical companies make the transparency issue a top priority going forwards – never before has patient data privacy been such a global conversation that people across all walks of life are actively invested in. For example – there are questions as to who should be responsible for ‘triggering’ the process of contact tracing when a person is found to be positive – a human user, or an app? If transparency about how organisations use, interpret and act on patient data wasn’t an issue before COVID-19, it certainly is now – and should be among the top priorities for today’s digital officers in Pharma.

Our assumptions about user behaviours are way too optimistic

We just mentioned the fact that patient data privacy has never been such an issue of public concern. 

We’ve also never experienced a global pandemic of this scale and nature before – one that’s already shown us that having good quality, high-volume, high-veracity data will be key to success in managing the situation going forwards. 

You would think, with all this considered, combined with the ongoing news and evolving rules about how best to manage the pandemic and avoid the R-rate increasing, that the vast majority of people would be willing and actively engaged in handing over their data – stigmatisation issues aside.

And yet, looking at the uptake rates for contact tracing apps around the world, this doesn’t seem to be the case:

• Australia: 22% 
• Germany: 14%
• India: 12%
• Italy 7%
• Japan 5%

So what’s going on? Well, according to Vanessa Candeias, it could be down to simply a lack of awareness about the apps themselves, or a lack of devices on hand to download apps. Or, more critically, it could be a trust issue given the transparency problem outlined above. Whatever the reason, however, there’s clearly a surprising lack of motivation in people for downloading COVID-19 contact-tracing apps. And if people are generally reluctant to download an app that could help them in the middle of a global pandemic, with demonstrable benefits and pretty significant public promotion, what does this mean for smaller-scale apps released in the future that don’t relate to an urgent issue?

It’s a challenge we’ve certainly grappled with here at Zühlke – for example, while it’s fairly easy to gain trust and secure engagement with patients who are already unwell and looking for help, it’s so much harder finding and motivating subject groups for clinical trials.

Again, these are just some things to bear in mind if you're a Healthcare or Pharmaceutical company looking to launch a patient-facing digital solution in the near future. It’s definitely worth conducting deep, comprehensive analyses on your audience and user preferences before assuming an app is always the way to go.

Best practices for Data Driven Health Solutions

We’ve only just scratched the surface of the issues surrounding patient data management that the COVID-19 pandemic has brought to light. 

Successful applications of digital health solutions indeed require the technical expertise when it comes to data governance and regulatory compliance. At Zühlke, our consulting best practice suggests the involvement of Business Designers, Humans Experience Consultants, Reimbursement Experts and representative Patient Organisations. 

We’ll give you the space and methodology you need, where expert knowledge meets creativeness, and high complexity is translated into successful marketable solutions. To see an example of what this looks like in practice, read the story on how we developed the UK’s NHS COVID-19 app.

And if you’d like concrete, one-to-one advice on how to implement best practices for digital patient solutions at your organisation, please don’t hesitate to get in touch – our experts would love to help.

Talk to our experts!