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Every day patients and staff across the NHS take the time to share their experiences. The national NHS survey programme plays a key role in making this happen and we know that many individual NHS providers go to great lengths to invite feedback from staff, patients and their carers. This information is hugely valuable as it helps us to understand how we are doing against our ambitions.
The words that people take the time to write are rich and powerful, reflecting the fact that the NHS touches people at a time when care and compassion are what matters most. This is why we are now thinking about how the NHS can make the best use of these words – technically known as “unstructured data” – the words people use to feed back in their own terms.
The 2020 NHS staff survey asked 2 COVID-19 specific questions for staff to answer in their own words.
- What worked well during the pandemic that should be continued? and
- What lessons should be learned?
We are hugely grateful to the many NHS staff who took the time to respond and take our responsibility to analyse the 700,000 comments received very seriously. All data submitted through the survey are confidential. It is impossible to identify an individual’s responses; comments are anonymised before they are made publicly available. We are committed to supporting NHS trusts to navigate, read and take any necessary actions for improvement in response to these powerful NHS staff reflections.
The NHS staff survey is one of a number of tools that generate large volumes of comments across the NHS. For us to make sense of the many millions of words written about NHS experiences at a pace that allows them to be used to make a difference, we need digital technology. While human connection and the need to listen directly to staff, patients and carers will always be necessary, machine learning, and the use of digital technology, is now also an essential component in the insight toolkit. We have a number of projects running to try and use this technology to support the system.
We recently worked with a number of NHS trusts as part of a Cancer Improvement Collaborative focused on improving the experiences of people with rare and less common cancers. To provide additional intelligence to inform and guide this work, we commissioned PEP Health (The Patient Experience Platform). Our aim was to use advanced algorithms to collect, sentiment analyse, and rate comments to form a score on the quality of care. Comments were gathered from review sites, social media and other sites where users publicly comment on the quality of care they have received It is important to note that we did not collect individual characteristics such as the age or sex of posters nor did we seek to derive it. Never before has digital data from social media been used in this way for NHS cancer services and it is encouraging that the outputs from this work show exciting potential to improve our understanding of what people say. Overall, the work found a positive picture, with cancer related comments scoring higher than all other comments. However, there were also some important key differences found, such as comments from those with rare and less common cancers were less positive on fast access compared to all other cancer and non-cancer comments. The work also showed that cancer patients talk with more frequency about continuity of care and clear information.
It is also encouraging to note that this data, alongside the National Cancer Patient Experience Survey is supporting improvement projects including work in East Lancashire to develop a database of diagnosed Neuroendocrine Neoplasm patients.
We are also really excited to be working closely with 2 NHS teams (Imperial and Nottinghamshire). We are supporting them to explore how their locally built methodologies can be used to best understand the great volumes of anonymous comments provided by staff and patients through the NHS Friends and Family Test. Following development, the methodologies will be piloted and interim solutions delivered. If we are able to find a way to scale up these methodologies, their machine learning algorithms could be game changing for NHS providers.
This work is real innovation on the edge with the potential to bring about great and meaningful improvements to patient care and staff experience through the power of words. The ambition is to share and spread this work further as well as better our understanding of what the NHS and the people who use it and deliver its services need – please do get in touch if you are interested in learning more or sharing work you are undertaking in this area.
You can contact the Insight and Feedback team using: ENGLAND.Insight-Queries@nhs.net