Data science and data-driven technologies are rapidly evolving and are increasingly embedded in our everyday lives. For example, voice recognition systems and online shopping or browsing recommendations are often based on sophisticated computing technologies that learn and refine by example. As more and more data is collected by us and about us, the potential grows to link different kinds of data to produce new insights and predictions. Within healthcare and medical research, particularly as the NHS moves towards more joined-up electronic health records, there is a great deal of enthusiasm that data science could improve the system, help clinicians and provide benefits to patients.
A key focus for Understanding Patient Data is to seek to understand what kinds of emerging digital technologies may use patient data in the coming years, and the impact these may have on conversations about how patient health information is used. We want to establish what we need to do now to ensure that patients, clinicians and the public can have confidence in responsible uses of data to improve health and care.
Our work on this has three main areas:
- Understanding the opportunities afforded for health, care and research by new and emerging developments in data science;
- Exploring the ethical and social issues that are likely to arise as these technologies develop;
- Finding out what the public think about the uses of these technologies and how they use patient data.
In the UK, we have rich, diverse, cradle-to-grave datasets within the healthcare system, and genomic data is beginning to be brought into mainstream clinical care. However, this massive and highly complex data is fragmented – even within individual hospitals – and underutilised. New and emerging digital technologies, such as machine learning, appear to show great promise for enabling some of this data to be used more effectively, for example to:
- improve the speed and accuracy of diagnosis and symptom monitoring;
- improve surveillance for infectious diseases;
- provide decision-support tools for time-pressed clinicians
- provide analysis to predict disease progression or treatment responses so that treatments can be tailored to individuals
- help predict health service uses to enable better commissioning of services
However, new digital technologies that are developed using patient data or that are used to help provide care may well raise ethical and social issues that must be clearly addressed if clinicians, patients and the public are to have confidence that they are being used for public benefit and in a responsible way. There are important questions about the governance of these technologies, accountability for the decisions or predictions they make, their trustworthiness, and the risks of unintended consequences, for example, if they inadvertently lead to inequalities in who gets access to health services.
To begin to understand both the potential benefits of new and emerging digital technologies for health care and research, and the issues that need to be taken seriously if this potential is to be realised, Understanding Patient Data will be co-hosting a meeting with the Wellcome Trust in June, bringing together experts from industry, academics, clinicians and policymakers. We will report the broad themes of the discussion and publish any outcomes and next steps from the meeting.
We will also use the meeting to feed into public dialogue research that we will join with the Academy of Medical Sciences to conduct later in the summer. This work will explore public, patient and clinician views about new technologies that may use patient data, in the delivery of care, for running the health service or for research purposes. Understanding more about public views on these issues is absolutely essential if we want to ensure a trustworthy system for patient data is developed as digital technologies become more embedded in health care and research.
This work stream is currently in its early stages so there’ll be lots more to report as we make progress, but do get in touch if you’d like to find out more about this work. You can contact the team at firstname.lastname@example.org.