Scale, Spread and Embed

Scale, Spread and Embed patient experience tool: informing person-centred health and social care provision

The feedback that patients provide on the experiences of their health and social care is critical to informing the quality and safety of care provision and services. The Friends and Family Test (FFT) is one opportunity for obtaining patient insights into the experiences of their care. However the human resource and time needed to manually read through, interpret and systematically analyse all patient experience feedback across the health and social care sector prevents incorporating this valuable data source sustainably towards quality improvement (QI). This poses an ethical dilemma for health and social care providers, having solicited the feedback but not being able to use it meaningfully as a rich source of organisational insights to deliver person-centred care. There is a growing emphasis, and policy directive, for care providers to move beyond only analysing response rates for patient experience surveys, but to use patient experience feedback in near-real time for QI initiatives. 

Given the large volumes of patient experience data that need to be interpreted, artificial intelligence (AI) and in particular natural language processing (NLP) offers a practical solution to analyse patient narratives in near real-time. The Scale, Spread and Embed Patient Experience Tool uses AI to provide near real-time interpretation of patient experience free-text comments and has been developed to embed user insights into a culture of organisational person-centred care delivery. scale, spread and embed

It is now currently being used in nine Trusts across England and being tested in five more health and social care organisations. It also received the 2023 Patient Experience Network National Award for most Innovative Use of Technology, Social, and Digital Media Award. 

For more information on the product view Discover more below. To acquire a license, complete the licensing form below.

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Improving the analysis and use of patient complaints in the English National Health Service 

The English National Health Service (NHS) receives over 200,000 patient complaints annually. Complaints provide rich narratives of poor and unsafe care, and are often submitted with the aim of preventing harm from occurring to others. Inquiries into safety failures have demonstrated that complaints signal problems where internal systems fail. Yet, their insights remain under utilised due to their complex unstructured nature, a disregard for their informational value, and a complaints process designed for case-by-case redress. 

Using process modelling and realist review methods, this work generated theory on how and under what conditions healthcare settings can achieve both case-by-case redress and system-wide analysis of complaints. Using the Healthcare Complaints Analysis Tool (HCAT), our work demonstrates the need to combine patient and staff perspectives for a more holistic understanding of patient safety, and provide pragmatic evidence-based pathway towards integrating complaints into the historically staff-driven quality monitoring and improvement systems. 

Read more about the HCAT tool.