New findings from the 2020 NHS Staff Survey explore staff experiences of working through the first six months of the Covid-19 pandemic in their own words. Picker is proud to have coordinated the survey and this innovative new analysis on behalf of NHS England and NHS Improvement.
The NHS Staff Survey is a long-running collection that measures people’s experiences using key questions known to be associated with good experiences of work. But the Covid pandemic has been without recent precedent and has necessitated deep, rapid changes to ways of working. With organisations facing different challenges and responding in a wide range of ways, the only way to properly understand the experiences of people working in the NHS is to ask them to describe what has gone well and what lessons need to be learned.
Staff provided this feedback as part of the 2020 NHS Staff Survey. Almost 600,000 completed the survey, providing over 23 million words of written feedback – the equivalent of more than 40 times the length of JRR Tolkien’s Lord of the Rings. To read this volume of text would take an average person more than 1,600 hours so machine learning was used to identify key topics and the sentiment associated with comments. The national report released today summarises this analysis and is accompanied by detailed local reporting that supports organisations to make sense of their data.
Commenting on the publication, Chris Graham, CEO at Picker, said
Today’s release provides NHS organisations with an unprecedented depth of insight into the experiences of their workforce. The use of machine learning to process written feedback from staff shows what is possible with modern technology: it has allowed staff to identify what has worked well and what lessons need to be learned from the pandemic in their own words and enables providers to focus in on the issues most relevant to their own workforces. We call on all NHS organisations not only to review their summary reports, but also to take time to review and understand the detailed comments that support these.
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