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NHS Case Study

Learn more about the data innovation within the NHS.

I asked Jonathan Cameron, Head of Service (Strategic Development) at National Services Scotland NSS (the shared services arm of the NHS in Scotland) if he could give us an overview of the delayed discharge project, specifically the value to patients.

At the time of this project, around 1,200 patients were delayed from leaving hospital each month. A delayed discharge is when a patient has completed their medical treatment but is unable to leave the hospital because they cannot look after themselves at home.

Scottish Government and NHS/NSS worked with The Data Lab to perform a proof of concept that resulted in an assessment of the risk of delay when a patient presents at a hospital.

In the early stages of the project, around 125 data points were identified as candidates for determining whether a patient would become a delayed discharge or not. Through the hard work of cleaning and understanding the data, this was reduced to just six key data points. They were then used in an algorithm to predict, with 97% accuracy, the likelihood of becoming delayed discharge.

Data Value

Initially I saw this as a decision-making case study as they were asking who is likely to be a delayed discharge? But it became clear that there were operating model improvements possible when they moved on to asking what do I need to do now to avoid this becoming a delayed discharge?

Image illustrating improved NSS decision making; predicting likelihood of delay and identifying interventoons. Also shows improved NSS operations; Vital proceddures actioned earler, patient experience improvements and cost savings.Improved decision making and operations (Click to expand)

The first point I would like to draw your attention to is the fact that having a lot of data is not necessarily a good thing. Having the right data, the right small amount of data, can be much more effective. It can reduce the amount of time and effort required to clean the data and subsequently reduce the overall project duration, resulting in delivering value quicker.

The second point is that the team identified that these six key data points were captured early on in the process. This was really valuable because if you can predict which patients are likely to be a delayed discharge early on, you can intervene while they are still getting treatment and put care packages into place to allow them to be discharged when they are able to do so.

I think the NSS team achieved great things on the delayed discharge project in a short amount of time and managed to take patients, employees and stakeholders on the data journey with them.

Check out the course, “Introduction to data for business leaders” for more information on this project and some additional interview content.

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