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  • Led by Imperial College London and Imperial College Healthcare NHS Trust.
  • Will scale up and spread the use of ‘natural language processing’ technology to transform patient feedback from the NHS Friends and Family Test into usable insights.
  • Initially introduced at Imperial College Healthcare NHS Trust, this project aims to test and evaluate the usability of the technology in 20–30 other NHS Trusts.

The NHS Friends and Family Test (FFT) was introduced in 2013 as an anonymous way for patients to provide feedback on the care they have received. The form includes free-text, unstructured fields.

Across the NHS, and at Imperial College Healthcare NHS Trust, the valuable patient information data collected from the FFT was being under-utilised due to a lack of human resource and there being no systematic way of extracting useful insights.

An Innovating for Improvement project was completed, which used ‘natural language processing’ (NLP), a computer science technique that transforms unstructured text into a structured format, to analyse patient feedback and provide information to point-of-care staff and quality improvement leads.

Visually interesting, digestible, interactive reports of patient experience are now produced at ward/service level, with a dashboard accessible through Trust computers. This means staff are able to quickly identify actions that can be taken to improve patient experience as a result of patient-derived improvement opportunities.

This three-year Spreading Improvement project will test and evaluate the scalability of this NLP digital platform, in combination with quality improvement methodology, across other NHS trusts.

The intention is to partner with a variety of NHS organisations (approximately 20–30 in total) with diverse patient populations. The project team will evaluate the sustainability of Trusts using free-text patient feedback, in near real-time, as part of a culture of patient-centred working, and deriving and implementing improvement opportunities from that feedback.

The project aims to develop a language analysis toolkit that can be used across the NHS to categorise free-text patient experience data in order to support sustainable quality improvement changes for patient benefit.

Contact information

For further information about the project, please contact Erik Mayer, Transformation Chief Clinical Information Officer, Consultant Surgeon and Clinical Senior Lecturer, Imperial College Healthcare NHS Trust and Imperial College London.

About this programme

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