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Sundown Services

Patient Data Award

Sponsored by Sundown Services
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.

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.


Patient Data Award 2019 Winner: NHS Arden & GEM CSU - Population Health Management System


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.


Patient Data Award 2018 Winner: Milton Keynes University Hospital NHS Foundation Trust


East Cheshire NHS Trust
Leeds Teaching Hospitals NHS Trust


2017 Winner


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.


Patient Data Award 2017 Winner: NHS Arden & GEM CSU


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.

Patient Data Award 2016 Winner: Royal Cornwall Hospital Trust


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.


Bath and North East Somerset CCG
Poole Hospital NHS Foundation Trust