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ELFT Win Florence Nightingale Award for Excellence in Healthcare Data Analytics

Posted by Rowan Gill on July 19th 2022

We’re delighted to announce that East London NHS Foundation Trust (ELFT) have won the Florence Nightingale Award for Excellence in Healthcare Data Analytics.

The award, presented by the Royal Statistical Society (RSS) and sponsored by the Health Foundation, recognises “practitioners in applied healthcare data analytics who have gone the extra mile in delivering innovative improvements for the healthcare system”.

The aim of the award is to celebrate the work of healthcare data analysts who have informed a substantive change that improves patient care in a healthcare system in the UK.

The award recognises work carried out in the previous calendar year, either by teams or individuals. Entrants must demonstrate how applied analysis has resulted in positive change in the delivery of care and brought about substantial improvements in patient outcomes.

A fantastic achievement for an already high performing NHS trust.

See how you can get full visibility of all NHS Trust performance on Public View.

About the Award

Well known for her contribution during the Crimean War (1853-1856), Florence Nightingale (1820-1910) was also a pioneering statistician and the first female fellow of the RSS. Nightingale’s statistical contributions and use of data visualisation, like her Polar Area diagram, brought about revolutionary healthcare reform both on the battlefield as well as back home.

Launched in 2020, the award signified the bicentenary of Nightingale’s birth.

ELFT’s submission to the award were the collaborative efforts of Cloud2 and ELFT in developing integrated Power BI applications to help staff utilise data to aid decision-making and task management.

The apps followed a 7-step design process to allow self-service of clinical and non-clinical information, all contained within one place, making it highly accessible on multiple devices.

The apps have enabled teams to better understand quality, safety and flow in real time, as well as facilitate better management of incidents, waits and queues. In addition to offering better insights to the populations the Trust serves, resulting in more personalised care.

ELFT commented:

“Using business intelligence technology, we have created a mechanism to provide data to the fingertips of our stakeholders. Our apps cover mental health and community health services in East London, Luton, and Bedfordshire. Each apps give analysis an integrated analysis of quality, population health, flow, and team-based tasks, ensuring alignment with the Trust 5-year strategy.

The flow pages allow teams to understand capacity and demand in real-time, to help enable better management of waits and queues. The task management function allows clinical teams to view key measures for their caseload or ward, ensuring these are carried out in a timely way.

The Population Health pages give an insight into the population we serve, and the key determinants of health, enabling teams to view their patients through different dimensions such as deprivation, ethnicity, and postcode. The Quality pages allow teams to view their key quality indicators using statistical process control to monitor and act on variation. A unique early warning system has been designed with our clinicians, utilising statistical process control for a small number of indicators, enabling wards and leaders to be alerted in advance of a serious incident occurring.

ELFT has a track-record of applying best practice statistical methods to understand variation, through its quality improvement approach which is globally recognised. The organisation utilises statistical process control to help understand variation, enabling differentiation of common cause from special cause to know when to take action and how.

The integrated apps we have developed utilise statistical process control (SPC) charts for teams to view their quality, performance, population health and flow data. In total, our apps contain over 50,000 interactions of SPC charts, all able to be filtered from organisation-level to directorate and team level.

Power BI did not contain any inbuilt functionality for statistical process control. Over four years, we have collaborated with a Microsoft Gold Partner to build a suite of SPC charts and functionality in Power BI, which we have deployed across the organisation and also now made available for anyone else in the world to use.

Statistical process control also informs our innovative early warning system for wards, which we believe is unique in its design globally. In addition to SPC, we have used other analytical features to allow users to quickly identify areas of change to investigate, including safety heat maps and variation across teams.

Over the last four years we have developed SPC visuals in Power BI, in collaboration with a Microsoft Gold Partner, that are now available to anyone in the world to utilise. We have run webinars to describe our work and the development, which have been viewed by hundreds of people”.