A graphic of a finger touching an interactive screen

With the rise of digital technologies, there are more data available than ever before. Healthcare is no exception. And not only are there more data, but they are coming from different places. Alongside the more traditional sources such as government, healthcare systems and academia, data are being churned out from medical devices, mobile apps and websites.

We need to be able to link up and consolidate these increasingly complex data, and turn them into useful information that can improve healthcare and inform policy, both locally and globally.

We were established in response to this need. We’re a strategic unit within the Institute of Global Health Innovation that aims to enhance patient care through a more effective use of health data. Our hub gathers, houses, interprets, and analyses health datasets, to make impactful discoveries about both individual people and whole populations. It also ensures that the data is stored and managed appropriately, in compliance with data protection regulations.

Our work

All of our work is facilitated by our Big Data and Analytical Unit Secure Environment (BDAU SE), a platform for our analytics. Through the BDAU SE we can use techniques like machine learning and natural language processing to answer big questions: Are we performing as well as other healthcare systems? How can we generate national approaches to disease prevention? How best can we use genetic data to make medicine more personalised?

These are just a few of the areas our team is interested in. Find out more about some of the work our researchers are doing to use data to influence policy and improve healthcare.

Find out more about our work

Global COVID-19 survey

Two people wearing face masksWorking with YouGov, we’re tracking how people across the world are responding to the coronavirus pandemic. Our fortnightly survey is looking at public behaviours and attitudes across 29 countries. The data and insights from these are being made freely available to all through an open data dashboard (accessed here at CovidDataHub.com), so that leaders can better plan their actions to tackle the crisis.

As part of this work, we’ve partnered with the co-editors of the World Happiness Report, published by the UN Sustainable Development Solutions Network, to explore life satisfaction during COVID-19.

Life satisfaction provides a powerful umbrella measure of the quality of people’s lives. In the annual World Happiness Reports, differences between countries and over time are explained by good health, income, and four aspects of social environments: trust, generosity, having someone to count on, and freedom to make key life decisions. All of these elements are changing under COVID-19, often in ways never experienced before. The life satisfaction data we are collecting regularly as the pandemic evolves should provide a valuable barometer reading of life during COVID-19, reflecting each country’s institutions and policies.

The project is being led by Sarah P Jones, IGHI doctoral researcher, Melanie Leis, director of our BDAU, and Gianluca Fontana, director of operations at the Centre for Health Policy.

We’re grateful to our collaborators from the World Happiness Report, who are leading the analysis on life satisfaction levels: Professor John F Helliwell, Professor Jeffrey D Sachs, Professor the Lord Richard Layard, and Associate Professor Jan-Emmanuel De Neve.

Data at doctors' fingertips

A tablet computer with health dataWe helped develop Streams, a mobile app for medical information and alerting. Streams stores important patient data, like blood test results, in one easy-to-access place so that professionals have the information they need to act quickly should problems arise. Early studies showed how Streams leads to more efficient responses than traditional pager systems.

Now, as part of an HDR UK-funded study, we’re analysing new data from Streams as it’s trialled in hospitals. We’re looking at whether the app can reduce the length of time it takes for patients to receive treatment, compared with standard care. With more rapid responses, Streams could lead to better outcomes for patients and improve their care.

Spotting safety incidents

We’re analysing reports of patient safety incidents to highlight issues in hospitals so that they can be responded to in a timely manner. Typically these static reports take months to be generated, meaning problems can escalate before they’re even realised.

We’ve teamed up with the Data and Intelligence Hub of an NHS Acute Trust to test an interactive data visualisation tool we’re developing that could improve hospitals’ ability to monitor patient safety. By automatically highlighting problems to staff as they arise, this innovative data dashboard will allow hospital managers and clinicians to rapidly identify issues, and where they’re occurring in the hospital. This will allow trusts to quickly address any issues, prevent them from escalating, and improve patient safety.

Guiding patient data sharing

We’re examining connections between hospitals to optimise data sharing strategies, streamlining care for patients and potentially freeing up vital NHS resources.

Hospitals and care providers often use different systems to hold electronic patient data, meaning records can’t easily be transferred. This frustrates patients, creates delays in treatment, and risks patient safety if vital information is missed or forgotten. But ensuring that all healthcare providers have systems that can work together would be a costly and lengthy process.

Our researchers have been using analytics to identify groups of hospitals that share the greatest number of patients, highlighting areas where patients would benefit the most from having compatible systems. This work can help the NHS guide discussion on how to achieve better data sharing between hospitals, prioritising trusts that commonly share patients. This means that limited resources can be directed towards areas where they will have the most immediate positive impact on patients.

Road traffic injury surveillance

A highwayOur Road Traffic Injury – Analytics for Integrated Data (RTI-AID) project is using crowdsourced data to develop a road traffic injury surveillance tool to aid emergency medical systems.

Good trauma system planning requires robust traffic collision and injury data, which can inform hospital care, reduce ambulance travel time, and reduce high-risk roads.

The World Health Organization’s Injury Surveillance and Trauma Care guidelines highlight the need for good data, particularly where resources are limited. Such data is sparse in developing countries, but the boom in digital technology in developing world cities offers a potential alternative data source to help capacity-building, injury care and risk reduction, in line with the UN’s Decade of Action for Road Safety.

We’re seeking to:

  1. Collect and pool novel digital data sources relating to road traffic collisions, such as online media, news, mobile navigation apps and vehicle monitoring systems;
  2. Assess the ability of these sources to identify the real-world location, timing and severity of road traffic collisions and injury;
  3. Compare the accuracy of these sources for road collision and injury surveillance to well-established high-quality data from London’s transport, ambulance, health services; and
  4. Explore whether these sources could help developing world cities to overcome inadequate infrastructure, raise awareness and improve outcomes.

Find out more about RTA-AID here.

Our progress

A man filling in a feedback form

Listen, learn, improve

Patients’ feedback on their experience of care is a hugely valuable resource that could guide measures to improve care quality. But it’s been largely untapped as free text is difficult to analyse en masse and extract meaningful insights from.

Our researchers have used a technique called Natural Language Processing to crunch huge swathes of feedback and gain a greater understanding of patient experience. This transformative project won a BMJ Award for Digital Innovation and could lead to new measures to improve the quality of healthcare.

A stethoscope, money and pills

Determining the true cost of sickness

With an ageing population and rising levels of obesity, more and more people in the UK are living with more than one health condition (multimorbidity). We’ve been working with the Business School to facilitate their research that’s examining the financial impact of multimorbidity on health systems.

This research combined primary and secondary care data to look at the impact and costs of having more than one non-communicable (can't be passed on) disease, compared with having one illness. The work involved more than 1 million patients and forms part of a trans-European study that’s comparing the cost of illness across the continent, helping us to better understand the economic burden of disease and inform future strategies that could mitigate these rising costs.

Our network

The BDAU works across Imperial College London and beyond. To date, the BDAU SE has supported 80+ researchers working across 150+ unique datasets.

We actively seek to collaborate with internal and external parties who are interested in applying their unique areas of expertise to solving the most pressing questions in healthcare. This has led to internal collaborations with the EPSRC Centre for Mathematics of Precision Healthcare, the Centre for Health Economics & Policy Innovation (CHEPI) and the Department of Primary Care and Public Health (PCPH), among others. Our 20+ external users are from a range of organisations, including universities, NHS trusts, charities and independent research groups.

Our infrastructure

The BDAU SE is an ISO-27001 certified environment. We are also compliant with NSH IG and DSP toolkits. Compliance with data protection is our highest priority. Each user’s access is strictly restricted to the data they are allowed to view based on their project needs and permissions. All users accessing data on the BDAU SE are trained on GDPR and ISA, including Data Protection Act (DPA) training. We keep a record of training and ensure that it is refreshed on an annual basis. Access is revoked for users who do not pass annual training.

The BDAU SE offers users a variety of software to conduct their analyses. These include Stata, MATLAB, SPSS, R, Python, KNIME, SAS and command line tools. The inclusion of these platforms allows for advanced data analysis to be conducted securely within the BDAU SE.