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East London NHS Foundation Trust (ELFT) is renowned across the UK’s public health sector as a pioneer of continuous quality improvement. ELFT now uses SPC Charts to provide its teams with intelligent insights in near real-time to support the prediction of future trends, the identification of variations and data-informed decision-making.
East London NHS Foundation Trust – Healthcare
6,300 employees working across 100 community and inpatient sites
The legacy tools ELFT was using, such as Excel Macros and Life QI, were hindering the use of SPC charts at the scale needed for operational reporting. After evaluating the market, ELFT chose to partner with BCN to create a new SPC offering. One that met all their requirements and followed Institute for Healthcare Improvements (IHI) guidelines.
In partnership with the ELFT, BCN developed custom visuals in Power BI. These unique charts have features and functionalities that no other SPC tool currently has in Power BI, enabling the trust to save in excess of 19 staff days every day to produce the same number of charts if they had continued to use their legacy system.
East London NHS Foundation Trust (ELFT) is one of the UK’s largest specialist NHS providers. It provides mental health, community, and inpatient services to children, young people, working-age and older adults, as well as forensic services to the City of London, Hackney, Newham, Tower Hamlets, Bedfordshire, and Luton. The Trust also operates 100 community and inpatient sites and has over 735 general and specialist inpatient beds.
Before our involvement with ELFT, the Trust had what it considered an automated solution. It had a data warehouse where it created procedures that automatically populated charts in Excel. It also had pre-designed templates where all the rules, procedures, and charts were already set up for inputting data into templates. Alongside this, they also had pre-designed reports ready for populating with charts.
However, ELFT recognised there was another way: Statistical Process Control (SPC).
ELFT’s aim was clear: to use SPC techniques to collect and analyse data to improve, streamline, scale, and better control its inpatient processes. ELFT worked with BCN Group and our subsidiary, Cloud2, to develop an integrated app solution in Power BI for the Trust’s inpatient SPC processes. The solution we created for ELFT provides a high-level summary containing three SPC charts. It also has four Population Health pages with 20 SPC charts. It has 10 Quality, Safety, and Flow pages with 49 SPC charts too, plus, a Value section with five more SPC charts. In all, the integrated app has 77 SPC charts.
The Trust’s six Directorates each have their own set of that 77. And within each Directorate and Trust-wide view, there are also 75 inpatient wards or inpatient areas. So just in this inpatient solution, the Trust can generate 34,650 SPC charts daily at the Board level, Directorate level, Ward level or Team level. Even better, all can digest their SPC charts at the level they need to make decisions.
For ELFT to create 34,650 SPC charts using their traditional methods would be a huge drain on time and resources. First, they would have to extract data from their data warehouse overnight, then manipulate it in Excel in pre-designed templates – assuming no chart changes – and then copy the SPC chart into a pre-set dashboard or reporting template. Based on conservative estimates of 15 seconds to create an SPC chart, it would take 19 staff working each day (141 hours) to create 34,650 SPC charts. And remember, this is just for inpatient services.
Considering the other areas, the Trust operates and ELFT anticipates it could be working with over 100,000 charts in the very near future, enabling all levels of the Trust – from Board to Directorate to Ward to Team – to represent data in a meaningful way to make better decisions faster each and every day. This simply wouldn’t be possible even using a reasonably automated method.
Testimonial
Where possible, use extra details in models – for example, cohort sizes, data types and frequency of events. If possible, run different scenarios and comparative analyses to see the added value that extra data and intelligence brings.
Demand for SPC charts can go from thousands to 10s of thousands to 100s of thousands quickly. Think about what type of automated solution you’ll need to invest in to enable their mass adoption at Ward and Team level invest.
Different chart types can provide more finely-tuned results.
Chart selection doesn’t have to be overly complicated or a reason to stick to XmR.
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