'Change NHS' ideas: getting clarity from public commentary
(Maps viewable on desktop only)
The NHS has launched an initiative soliciting change ideas from the public. The campaign site is here: https://change.nhs.uk/en-GB/. It’s good that the campaign is asking open-ended questions, soliciting views on the “best things” as well as the challenges.
The problem comes when organizations try to make sense of the resulting haystack of responses. Reading a long list of verbatims isn’t empirical. And using tagging or topic models to organize the content provides only a narrow view of the responses – without a sufficient line of sight to reasons why.
Instead, we took 2,770 of the responses and ran them through narrative analytics - a process that took roughly 90 minutes, and which quickly reveals clear, actionable themes in context. The result is a "map" of the ideas, based on axes and clusters that are bespoke to the dataset.
To view the map, just hover over the dots with your cursor. First, look at the 5-cluster view below. This shows the axes: The talent/people vs The process on the horizontal axis, and How the system works vs What patients need on the vertical axis. All of the dots are placed based on these axes. Make sure you explore the different levels of narrative detail, by using the slider on the lower right and viewing the 34-cluster level.
What the press is getting wrong: This is not a ‘Boaty McBoatface’ moment
It’s brave to do a “Let’s hear from the public” exercise in the UK. The media have noted this – with The Guardian and other publications suggesting the effort is another mass exercise in ironic humour. (see link) The reality is the opposite. In hovering the dots and viewing the narratives, it's easy to see just how serious and well-reasoned the ideas are.
If a large number of verbatims were characterized by irony or sarcasm, narrative analytics would include a cluster specifically identifying them within the map. There is no such cluster, because there are very few such responses. People are serious about their NHS.
That said - If you would like a laugh or two, a higher concentration of light-hearted comments can be seen in the Culture/media cluster. You can find it by selecting the 34-cluster view in the map above. It is a small cluster near the middle, with dark green dots.
What types of ideas are most frequently posted?
From the 34-cluster view in the above map, the largest are shown in the bargraph below. Resourcing choices, Simpler/better info handling, and NHS funding were the top 3. Have a look at the others. How do the narratives in the graph below compare against the top priorities as you see them? Further cuts of data such as this can reveal how the clusters rank in different regions, or how they vary by age, income, gender, or political affiliation. This can be highly actionable in the formulation of new policies and reforms - particularly when changes and trends are tracked over time.
Narrative traction - what ideas are getting more vs fewer likes?
Another way to view the data is by narrative traction. Though counts are limited, this view shows which narratives draw more net likes vs less. In the below graph taken from selected clusters in the map, we can see that Transgender healthcare, Mental health, and Training & Retention have a higher proportion of ideas earning four or more likes. NHS funding, Simpler/better info handling, and Fertility and reproductive health the lowest proportion of net likes. (Net likes = the total number of likes minus the total number of dislikes).
For healthcare organisations and policy makers alike, narrative analytics is the fastest, easiest way to measure the 'outside-in' stakeholder realities related to a particular issue or challenge. This is a great illustration of how valuable it can be to ask open questions, rather than closed ended surveys. Narrative analytics transforms organizations' ability to get a fast, actionable understanding of what drives patient, stakeholder, and customer experience - either from your existing data, or through open-quant surveys. Contact us to learn more!