Clinical Informatics Research Programme (CIRP)
The CIRP was established, thanks to investment from the Great Ormond Street Hospital Charity, to support clinical informatics research at Great Ormond Street Hospital (GOSH) in partnership with Higher Education Institutes across the UK.
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CIRP funds data scientists, clinical and non-clinical PhD fellowships, internships, and other activities that enable research. It focusses on developing the use of data and technology to transform delivery of care, for the benefit of patients at GOSH and the wider NHS.
CIRP research themes include data and informatics, human-computer interaction and clinical pathways and decision support.
You can find project examples below. For more information about CIRP, please contact Drive.Research@gosh.nhs.uk.
Project examples
Can virtual reality be used with young people with cancer?
As a biomedical engineer and PhD student in digital health, Mairi noticed that there is lots of research on virtual reality (VR) in healthcare, but very little VR is used in the NHS. By conducting, analysing and reporting on interviews with healthcare professionals and co-design workshops with young people being treated for cancer, she hopes to bridge this gap by improving our understanding of how VR could be implemented in the NHS.
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“Engineers regularly work with new technologies to solve niche problems, but they often have very little context for how the technology will be used in practice.... With services already up and running it can be difficult to fit in new technologies and ways of working, so it's important that my research will understand these obstacles so we can innovate around them.”
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Mairi Therese Deighan is conducting her PhD at the University of Bristol.
Applied Child Health Informatics
The collaboration between GOSH and UCL Great Ormond Street Institute of Child Health is the only National Institute for Health and Social Care-supported Biomedical Research Centre that solely focuses on paediatric research.
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The applied child health informatics theme builds on the potential of data science to revolutionise medicine. The infrastructure in GOSH Digital Research Environments (DRE) supporting this theme, is world-leading. Professor Neil Sebire and Dr Pia Hardelid co-lead the theme.
Industry Exchange Network (IXN)
DRIVE works in partnership with University College London IXN where Great Ormond Street Hospital staff and clinicians collaborate with academic groups on projects to provide insight into real-life problems in healthcare and develop early stage technological solutions. The programme addresses three major clinical areas - interoperability, efficiency and innovation.
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DRIVE has hosted over 60 IXN projects. A majority of these (57%) focused on development of websites or mobile apps, or virtual environments such as augmented and virtual reality. The end users that could benefit from these developments were mainly healthcare professionals (31%) and patients and families (31%).
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You can read about some project examples below.
HoloRepository: A Repository of Holographic Medical Images
Medical images, such as MRI or CT images, are stacks of 2D images used for analysis and diagnostics. These images are difficult to interpret for non-trained eyes, which could lead to a diminished understanding by patients of their condition and treatment options.
The Holorepository provides an interactive and engaging way to view medical images in 3D. It implements a pipeline to create holographic images from MRI and CT scans. These holograms can then be viewed using devices, such as Microsoft HoloLens, during patient-doctor consultations.
UCL Computer Science MSc Project 2019
My Nephrotic Notebook Mobile App
Parents of children with nephrotic syndrome,or the children themselves use a paper notebook to record daily the level of protein in their urine. These notes are meant to guide patients/parents on medication dosage and inform the clinical team of the patient’s progress, but they are difficult to interpret and often get lost, or damaged. The My Nephrotic Notebook mobile app allows users to easily record proteinuria dipstick readings, and based on these results, it informs users whether they have relapsed, are in maintenance, or have reached a period of remission. The data is stored locally and it can be shared with clinical teams via e-mail.
UCL Computer Science MSc Project 2019
