Nicola Perrin, who leads the Wellcome Trust's Understanding Patient Data initiative, discusses work underway to improve understanding about how and why patient information is used.
This presentation was recorded at our Digital Health and Care Congress 2017 on 11 July 2017.
As all of you in this room know, there are huge benefits of using data responsibly to improve health and care. You’ve heard about the importance of joining up records from GPs, hospitals, care homes to provide much safer and more effective care. But there’s also a huge number of other uses from understanding more about disease, improving diagnosis through to monitoring patient safety. Why are we seeing all the bad news when there is so much patient benefit as well?
And I think it’s partly because of the lack of awareness about how the NHS uses data at the moment and yet in general, the more information people have, the more comfortable they are with data being used for wider purposes within the NHS.
But there’s a slight caveat, if you give just a small amount of information, you actually raise concerns. These are issues that people haven’t thought about at all and suddenly they have a lot of questions, they have a lot of concerns and it’s only when you can give enough information that people feel reassured that this is actually an important thing and it’s really necessary for the NHS to function efficiently.
I would argue care dot data got us right up to that peak of concern and kind of left people hanging there, and that’s certainly why understanding patient data has been set up. We’re a new initiative to support better conversations about how health information is used. We want to provide objective evidence to help the public, the patients, healthcare professionals understand how and why data is used, what’s allowed, what’s not allowed and how personal data is safeguarded.
It’s really important to everyone that there’s a public benefit and that’s why it’s so important to talk about the why and the purposes of using data.
Can I be identified? This is one of the first things that people ask. People traditionally think either end of the spectrum; data is either fully identifiable or it’s anonymous and you wouldn’t be able to identify somebody. What we want to help people understand is that there’s a grey area in the middle where it’s still information about an individual but it’s been de-identified. The identifiers have been removed. By thinking of it as a spectrum, with a photo of somebody as an identifiable person, a blurred photo of somebody for de-personalised information and then a group silhouette photo, a silhouette picture where it really is clear that you couldn’t identify somebody, it really helps people get this concept.
And people really go the concept that you’ve blurred the photo but if you had enough time and resource and motivation you could in theory get back to the identifiable data, particularly if you have other information or existing sources of data that provides a bit more information so you can piece together the information and help unblur it, as it were.
The other thing that people always want to know is, will companies have access to data? And there’s almost a knee jerk reaction that commercial access is bad and we wanted to unpack in a bit more detail whether or not it really was so black and white or whether or not there was nuance in the middle of this as well.
There was a large survey of over 2000 people, which found that actually more people supported than opposed commercial access and that figure went up if there was no other way of conducting the research, if the commercial option was the only one otherwise the research wouldn’t happen, then 61% of people were supportive. But really importantly, there is a significant minority of people 17% that didn’t want commercial access under any circumstances, which is why an opt out approach really seems to be the most appropriate.
But this was a high level survey. We also did a number of focus groups to really sort of unpack some of these issues in a bit more detail using a number of case studies, and what we found was that the purpose was really the most important thing. People had four key tests, they wanted to know why the data was being used; who was using it; what kind of data; and how it was used. But really, the first and most important was that why. If there was a public benefit, then they were much more comfortable with the data being used.
And if there was mix of public and private benefit, then it was a bit more acceptable. They would have a conversation about the who and why and how. Solely private benefit, people were very uncomfortable with and I think that explains why insurance companies accessing data raises so many concerns, but I think we need to get much better about talking about all the different uses.
Software providers just for GPs to use electronic health records, they have a lot of control of data and they’re using.
Analytic services again, working for the NHS, but it’s still a commercial access to data, and it’s important that this is commercial access rather than necessarily commercialisation. So they’re not necessarily making a profit from the data.
But pharmacies, private health providers, there’s a lot of different companies out there using data and we need to be much better at talking honestly and openly about those. We want everyone to be able to talk about why it’s important to use data, that data has to be kept safe, that there must be transparency and we all need to get much better at helping people find out how patient data is used and why.