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Resources > Using SSNAP data in research > Data requests > Research projects using SSNAP data

Research projects using SSNAP data

The table below lists external research projects using SSNAP data following an approved data request. 

Approval date

Title

Contact name

Organisation

Summary

May 2022

The Health and Social Care Artificial Intelligence (AI) Award  

Dr Matthew Epton

Oxford Academic Health Science Network, Oxford University Hospitals NHS Foundation Trust

The Health and Social Care artificial Intelligence (AI) Award
The Artificial Intelligence (AI) in Health and Care Award is one of the programmes of the NHS AI Lab at NHSX and is run by the Accelerated Access Collaborative (AAC) in partnership with the National Institute for Health Research (NIHR). Oxford Academic Health Science Network (AHSN), part of Oxford University Hospitals (OUH) NHS Foundation Trust, has been commissioned by NHSX to evaluate the impact of the ‘e-Stroke’ software (acute stroke AI decision support tools), made by the company Brainomix, in their function to facilitate the interpretation of imaging scans in patients with suspected acute stroke and to assist clinicians in making decisions for reperfusion therapies, leading to a reduction in long-term impairment of surviving patients.
December 2022 SAMueL-2: Use of simulation and machine learning to identify key levers for maximising the disability benefit of intravenous thrombolysis in acute stroke pathways Michael Allen University of Exeter SAMueL-2: Use of computer simulation and machine learning to maximise the benefit of clot-busting medicines in stroke

We will develop a computer-based tool for doctors to help them improve the speed and use of life-changing treatment for stroke. It compares their stroke pathway with other hospitals, and helps to answer the question “What treatment would this patient receive in other hospitals?” 
April 2023 What factors influence the inpatient length of stay and discharge destination for survivors of stroke with severe disability? Lal Russell University of Nottingham This evaluation builds on our previous work exploring the home-based rehabilitation of survivors with stroke with severe disability (HoRSSe). Work package 1 has been previously completed in which an expert panel consensus detailed key components of a home-based intervention for survivors of stroke with severe disability (Ethics reference: 27-0520). Work package 2 explored the current provision and barriers and facilitators for implementation. This final stage (work package 3) aims to describe the cohort and explore factors influencing their hospital length of stay.
June 2023 Which variables predict EQ5D in community dwelling stroke survivors: an exploration of national clinical audit data Dr Niki Chouliara University of Nottingham This study would firstly explore any associations between patient characteristics e.g. age / disability and EQ5D at six-months, for the regions containing pilot sites. For example, if age associated with the level of pain reported by stroke survivors, this may have implications for those services with relatively older populations e.g. coastal towns compared to inner city.

Secondly, this study focusses on the pilot sites where EQ5D is available before and after rehabilitation. This allows exploration of changes over time in the EQ5D, investigating which patient characteristics may be influencing these changes.

The aim of this study is to support stakeholders to understand and use the data they are collecting, to inform the delivery of their services and drive quality improvement.
June 2023 PreHOspital Triage for potential stroke patients: lessONs from systems Implemented in response to COVID19 (PHOTONIC) Rachael Hunter University College London The statistical and health economic analysis of the PHOTONIC study will focus on how prehospital triage in the context of stroke impacts on appropriate patient transfer, care delivery, patient outcomes, and cost effectiveness.We will compare ambulance services with and without prehospital triage to test the following hypotheses:
  1. Prehospital triage will result in a reduction in proportion of patients classified as suspected stroke who are transferred to hospitals with specialist stroke units.
  2. Pre-hospital triage will increase communication between ambulance crews and the receiving stroke unit. As a result, the receiving stroke unit will be better prepared to receive the incoming patient. This will reduce the time from arrival at hospital to receiving clinical interventions and increase the likelihood that patients with a stroke diagnosis will receive timely and effective care.
  3. If care is improved, patient outcomes resulting from improved care will be impacted, such as length of stay in hospital and 30-day and 90-day all-cause mortality.
Finally, a health economic model will evaluate the cost-effectiveness of the intervention.
September 2023 Specialist PrE-hospital rEDirection for ischaemic stroke thrombectomy (SPEEDY): a cluster randomised controlled trial with included health economic and process evaluations Professor Christopher Price Newcastle University In an earlier project, a ‘specialist prehospital redirection pathway’ was developed which involves communication between ambulance practitioners and specialist hospital thrombectomy staff to decide whether the emergency operation is likely to be required, followed by direct admission to the specialist hospital if this is the case. A large research study will now test the impact of this new pathway for patients and the NHS. In order to describe what happens when the new pathway is used, the study will examine data about thrombectomy treatments and other aspects of emergency medical care which are routinely recorded in ambulance and hospital records, and entered by clinical services into the NHS Sentinel Stroke National Audit Programme.
March 2024 Exploring the Longer Term Clinical Care and Outcomes of Non-White Stroke Patients Dr Eugene Tang Newcastle University All patients should have equal access to care post-stroke according to need, but internationally there is evidence that this can vary according to ethnicity. The overall aim of this study is to help clinicians and services identify any disparities in NHS post-stroke care amongst Black and Asian patients. The aim would be to develop recommendations for practice and research if possible inequalities are identified.
May 2024 The impact of different configurations of inpatient stroke care, an analysis of data from the UK Sentinel Stroke National Audit Programme (SSNAP) Dr Shirley Thomas University of Nottingham This study aims to understand the impact that the configuration of the hospitals stroke unit (combined versus separate) has upon a stroke survivor’s disability on discharge and how long they stay in hospital. Also, it will investigate whether transferring to a rehabilitation hospital or having rehabilitation in the admitting hospital impacts discharge disability, hospital length of stay or the amount of therapy received. This aims to help inform service leads and commissioners when undergoing service reorganisation.
  The Oxford Risk Factors And Non Invasive Imaging Study (ORFAN) Professor Charalambos Antoniades The University of Oxford The ORFAN Study is a research project set up to find new and more accurate ways to predict a person’s chances of suffering from diseases such as heart-attack or stroke. The ORFAN Study has different research arms that work together to enable the success of the project. 

The research team uses the gathered information to discover new ways to assess patient’s risk for harm due to diseases such as heart attacks and strokes.

Patients will be able to use these accurate risk calculator tools with their doctor to understand the likelihood that they will suffer from a certain condition. This information can then be used to empower patients to influence their disease risk through lifestyle changes, increased monitoring and, if necessary, medication

Find us

Sentinel Stroke National Audit Programme
Kings College London
Addison House
Guy's Campus
London
SE1 1UL

Support

0116 464 9901
ssnap@kcl.ac.uk

 

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