Patient Data Award
The need for timely, effective information in healthcare is key to realising the benefits of the huge investments in NHS staff and buildings. This award will recognise the most innovative introduction of new technology for secure storage, retrieval and distribution of data throughout the NHS.
2022 Winner: East London NHS Foundation Trust
East London NHS Foundation Trust’s approach to quality improvement is deeply rooted in data. Its Visual Analytics Team, part of the Informatics Department, has received much praise for the development of new apps which are easily accessible from any device, on or off the Trust network, and bring together data from different sources in a way that helps the trust’s teams understand variation and take action to improve quality.
Commended
Stockport NHS Foundation Trust
Cambridge University Hospitals NHS Foundation Trust
St. George's University Hospitals NHS Foundation Trust
Frimley Health NHS Foundation Trust
2021 Winner
South Tyneside and Sunderland NHS Foundation Trust - Great North Care Record
Hospitals, GPs, community services, mental health specialists and adult social care all hold different electronic records about patients. Health and social care services in Sunderland are the first in the North East and North Cumbria to securely view and share vital medical information. The Great North Care Record project safely and securely connects patient information across a range of health and social care organisations throughout the North East and North Cumbria. It covers the 3.6 million people living in the North East and North Cumbria.
Commended
NHS Arden & GEM CSU - Segmentation Model Individualised Towards Health (SMITH)
Midlands Partnership NHS Foundation Trust - Business Intelligence Transformation
East Lancashire Hospitals NHS Trust - BadgerNet Maternity Care
East Sussex Healthcare NHS Trust - Paper-Free Digital Patient System
2020 Winner
NHS Arden & GEM CSU
As a temporary measure to finding a definitive source for the daily reporting of deaths brought about at the start of the pandemic, providers were using a manual data return spreadsheet to record deaths over email. The NHS Chief Executive’s Office wanted to replace this with a timely and accurate system as quickly as possible and approached Arden & GEM’s Data and Systems team, with its successful track record of building, deploying and hosting similar applications.
Commended
Leeds Teaching Hospitals NHS Trust/Yorkshire Ambulance Service
South London and Maudsley NHS Foundation Trust
Cambridge University Hospitals NHS Foundation Trust
University Hospitals of Morecambe Bay NHS Foundation Trust
2019 Winner
NHS Arden & GEM CSU - Population Health Management System
Arden & GEM’s advanced analytics team has developed a population health management (PHM) approach, using segmentation and matrix modelling, that also evidences the benefits of implementing new models of care and ways of working upon the health and well‐being of the registered population. A clinically validated High‐Level Segmentation Model (HLSM) was created, driven by linking data sets from acute, mental health and inpatient community services from over 470,000 local records, which accounts for 48 per cent of the registered patient population.
Commended
Royal Cornwall Hospitals Trust - RADAR PRISM
NHS Doncaster Clinical Commissioning Group - Web based Analytics
Midlands Partnership NHS Foundation Trust - Robotic Process Automation
Nottingham University Hospitals NHS Trust - Digital Outpatient Project
2018 Winner
Milton Keynes University Hospital NHS Foundation Trust
Milton Keynes is running an app that enables patients to manage their appointments directly, with updates written directly into the trust’s patient administration system. The Trust has seen take‐up by more than half of all its outpatients, and predicts it will save over £1 million in 2018/2019. As the app can write directly to Cerner, it has the potential to provide patients with access to their medical records, as well as potentially tapping the reams of health and activity data collected by wearables. Developed and run as part of the trust’s transformation programme, the app was co‐designed with patients and clinicians. Patient surveys has revealed high levels of satisfaction with the new system, and trusts across the country are visiting Milton Keynes to learn more.
Commended
East Cheshire NHS Trust
NHS Arden & GEM CSU
Leeds Teaching Hospitals NHS Trust
2017 Winner
NHS Arden & GEM CSU
NHS Arden & GEM CSU has developed a Risk Stratification tool to help organisations predict behaviours such as unplanned admissions, and intervene earlier to improve patient care and reduce the burden on emergency services. Risk Stratification reports utilise the tried and tested Johns Hopkins Adjusted Clinical Group (ACG) methodology. Data is combined from primary and secondary care and is processed through the ACG algorithm. Rather than focusing on specific diseases or episodes, the system encourages a holistic view of the patient, including comorbidities that could affect commissioning and care management decisions. Reports have also been built with both commissioners and clinicians in mind. Features enable GPs to build registers of high-risk patients and drill down to view individual care pathways.
Commended
Cambridge University Hospitals NHS Foundation Trust
Kent and Medway NHS and Social Care Partnership Trust
2016 Winner
Royal Cornwall Hospital Trust
RADAR (RCHT Analysis Data and Reporting) has been in development for the last eighteen months at RCHT. The business intelligence tool’s modules produce live reports, such as number of patients in the Emergency Department and number of occupied beds, informing the patient flow team and on-call managers and driving decision making based on the most up to date information. RCHT was named as one of the top trust’s in the country for completeness of data on the NHS Digital Maturity Index.
Commended
Derby Teaching Hospitals NHS Trust
East of England Ambulance Service NHS Trust (EEAST)
The Christie NHS Foundation Trust
South Warwickshire NHS Foundation Trust
2015 Winner
University Hospitals of Leicester NHS Trust
Datasets developed by the winning Trust help to create predictive models that will aid future allocation of resources. The Paediatric Observation Priority Score, or POPS, quickly scores acutely ill children on a combination of risk identifiers,which can enable a hospital's capacity to be predicted 24 hours in advance.
Commended
Bath and North East Somerset CCG
NHS Arden & GEM CSU
Poole Hospital NHS Foundation Trust