Researchers using innovative technology to ‘unlock’ health records and transform patient care

Researchers are applying AI technology to ‘unlock’ data held in patients’ health records so that it can be used to improve care, planning and research.

The team from the UCLH BRC, NIHR Maudsley BRC and King’s College Hospital have developed an innovative platform called CogStack, which uses a type of AI called natural language processing which is able to interpret information in records that is held in an ‘unstructured’ way.

The team, led by UCL’s & KCL’s Professor Richard Dobson, recently won an AI in Health and Care Award to do the work.

Electronic health record systems are important for both patient care and research. However, records include a large amount narrative text which, while rich in information, can be difficult to make use of because it is unstructured.

Narrative text is challenging to analyse, and the process of assigning standardised codes to records based on particular words, conditions or treatments – also known as “clinical coding” – is normally performed manually by NHS staff. However, this is time-consuming, expensive and carries a risk of mistakes.

With the government funding received from the AI Award, this CogStack project will apply natural language processing to read clinical language in the NHS and assess the magnitude of efficiency savings and improved performance if the process of clinical coding is augmented by this technology.

This work will build on the CogStack technology to establish a more efficient way to read and code records in collaboration with five NHS Foundation Trusts: South London and Maudsley, King’s College Hospital, Guy’s and St Thomas’, University Hospitals Birmingham and UCLH.

Professor Dobson, who is Group Lead for CogStack and Professor of Health Informatics at the Institute of Health Informatics, UCL, and Dept of Biostatistics and Health Informatics, KCL said:

"When you visit your doctor or attend hospital a lot of information is collected about you on computers including your symptoms, tests, investigations, diagnosis, and treatments. Across the NHS this represents a huge amount of information that could be used to help us learn how to tailor treatments more accurately for individual patients and to offer them better and safer healthcare. The challenge we face is that most of the information held within these records is in written form which is difficult to use and learn from.

”We have developed the CogStack AI tools to read and understand this information and as part of this project will scale this capability across the NHS."

Dr Wai Keong Wong, UCLH Chief Research Information Officer, said: “As a fully digital large NHS Trust UCLH routinely collects huge amounts of data, and it is vital that as much of this data as possible can be put to use for the purposes of improving healthcare, research and hospital planning.

“Use of natural language processing is an incredibly important way of making sure that data that has so far been unstructured can be put into a format that we can best make use of as clinicians and researchers. Ultimately this will mean better research, improved treatment approaches for our patients and more efficient hospital operations.”

Dr James Teo, Clinical Lead for CogStack and Clinical Director of Data Science and Consultant Neurologist at King’s College Hospital NHS Foundation Trust and King’s Health Partners, said:

“Doctors’ handwriting may be deemed illegible – but to a computer, their typing isn’t much better! A lot of the information a patient tells their doctor is currently stored as typed text, which is inaccessible to other healthcare professionals. Patients therefore end up repeating the same story to different doctors which can be frustrating and time-consuming for everyone concerned.

“We, the Cogstack team, are building Artificial Intelligence which will read and summarise doctors’ notes so that they are easily understood by those that require them. In turn, this will reduce administrative burden for the NHS and provide richer, standardised patient-centred data summaries.”

The Artificial Intelligence in Health and Care Award is one of the NHS AI Lab programmes, led by NHSX. The competitive award scheme is run by the Accelerated Access Collaborative (AAC) in partnership with the National Institute for Health Research (NIHR).

Patients and the public are central to this project and informed its design. A coordinated, cross-site PPIE group will provide input to the CogStack learnings, building a patient involvement toolkit, ensuring public members are equipped to review NLP projects, and can embed patient priorities into the future use of this tool.