Current research in Thames Valley and Surrey

Projects

ERAS

Enhanced Recovery After Surgery (ERAS) Insights Solution

The purpose of the project is to extract the insights from the EPR (Electronic Patient Record) data; this will help OUH to achieve proactive and timely patient care and understand the gaps in their process adherence to ERAS pathways.

Currently OUH staff create multiple text notes while on ward rounds and save them in EPR. OUH is unable to use this text effectively as it is unstructured. There is a wealth of insights in this data that can help OUH deliver ERAS care proactively.

Clinical staff often respond reactively to situations and have no capability to predict various scenarios. The proposed solution which uses Google Health Care API and GCP Services can help achieve this.

Organisation

Acuvate

Unique project identifier

SDE_TVS_OUH_Proj_1

Website

Healthcare Solutions | Modernize Healthcare with Data & AI from Acuvate

MORSE

MultiOmics pRoject to Study gEnomics (MORSE); Integrating human functional genomics, epigenomics and transcriptomics to accelerate drug discovery for precision medicine in asthma

The purpose is to analyse anonymised patient data to support the investigation of the impact of comorbidities, treatments and interventions for a cohort of patients with severe eosinophilic asthma and other characteristics of systemic immunological dysfunction over a period of time.

Organisation

Arcturis Data (UK) Ltd

Unique project identifier

SDE_TVS_OUH_Proj_2

Website

Arcturis | Advancing Insights Using Real-World Data

Haematological Malignancies

Haematological Malignancies

Developing synthetic control arms and identifying features associated with progression and prognosis within and across subtypes of haematological malignancies.

Organisation

Arcturis Data (UK) Ltd

Unique project identifier

SDE_TVS_OUH_Proj_3

Website

Arcturis | Advancing Insights Using Real-World Data

NASH

A real-world evidence study of the patient journey for patients with Nonalcoholic Fatty Liver Disease (NAFLD)/Nonalcoholic Steatohepatitis (NASH) in the UK secondary care setting

The purpose is to analyse anonymised patient data to support the investigation of the complete patient journey from metabolic syndrome diseases to NAFLD/NASH, as well as the demographic and disease characteristics, treatment pathways and outcomes for a cohort of patients with NAFLD/NASH over a period of time.

Organisation

Arcturis Data (UK) Ltd

Unique project identifier

SDE_TVS_OUH_Proj_4

Website

Arcturis | Advancing Insights Using Real-World Data

Oncology Research Database

Oncology Research Database

Curation of a commercially viable, deep, longitudinal anonymised oncology research dataset that will allow Arcturis to efficiently deliver unique insights to pharma in relation to the development of treatments that will deliver significant benefit to patients with cancer.

Organisation

Arcturis Data (UK) Ltd

Unique project identifier

SDE_TVS_OUH_Proj_5

Website

Arcturis | Advancing Insights Using Real-World Data

RSV

Respiratory Syncytial Virus (RSV)

The purpose is to analyse anonymised patient data to support the investigation of the current state of testing coverage, healthcare resource utilisation (HCRU) and economic cost of hospitalisations for Respiratory Syncytial Virus (RSV).

Organisation

Arcturis Data (UK) Ltd

Unique project identifier

SDE_TVS_OUH_Proj_6

Website

Arcturis | Advancing Insights Using Real-World Data

Liver Disease and Viral Hepatitis

NIHR Health Informatics Collaborative (HIC) Liver Disease and Viral Hepatitis - GlaxoSmithKline (GSK) phase 3a

Feasibility assessment

Assessment of availability and completeness of electronic health data on adult patients with chronic HBV infection within the UK National Institute for Health Research (NIHR) Health Informatics Collaborative (HIC) Network.

Organisation

GSK Plc

Unique project identifier

SDE_TVS_OUH_Proj_8

Website

Viral Hepatitis and Liver Disease - Health Informatics Collaborative

Cardiovascular

NIHR Health Informatics Collaborative (HIC) Cardiovascular

This theme has collated anonymised clinical information on patients presenting with this condition from five of the UK's major cardiac centres, including Imperial, University College London, St Thomas', Oxford and King's College Hospital. Data include information on the state of the arteries and the heart muscle and a measure of the degree of damage to the heart. This information is being used by NHS researchers to help our understanding of the factors that are important in the outcome of patients with acute coronary syndromes.

Organisation

Imperial College Healthcare NHS Trust

Unique project identifier

SDE_TVS_OUH_Proj_9

Website

Cardiovascular - Health Informatics Collaborative

DiAlS

Digital Alerting for Sepsis (DiAlS) - NIHR Health Informatics Collaborative (HIC)

The DiAlS study will investigate the impact of digital sepsis alerts on patient outcomes and staff activity in NHS hospital trusts across England and Wales. As UK hospitals move from paper based to electronic health records, the integration of digital alerts to identify patients at risk of deterioration has also become common.

There is a clear benefit to patients from this research as the results will contribute to improved screening for sepsis in NHS hospital trusts and make recommendations for how alerts designed to improve patient outcomes are best introduced and evaluated.

DiAlS utilises the NIHR Health Informatics Collaborative (HIC) Data Sharing Framework.

Organisation

Imperial College Healthcare NHS Trust

Unique project identifier

SDE_TVS_OUH_Proj_10

Website

Health Informatics - The Institute of Cancer Research, London

FIT

Faecal Immunochemical Test (FIT) Clinical Audit

The faecal immunochemical test (FIT) is already an effective test for colorectal cancer.

However, it seems likely that the consideration of FIT test results in the context of other results obtained for the same patients would allow us to improve the sensitivity and specificity of FIT testing, and thus help us to stratify and prioritise patients for further investigation or treatment.

Organisation

Oxford University Hospitals NHS Foundation Trust

Unique project identifier

SDE_TVS_OUH_Proj_11

Website

Home tests for colorectal cancer could prioritise patients for referral - OxCODE

Sonobiometry

RAIQC GEHC Sonobiometry Tool

Premarket evaluation of GE Healthcare's AI tool using retrospective patient data sourced from Oxford University Hospitals SDE and the RAIQC pre-market evaluation platform.

Organisation

RAIQC Ltd

Unique project identifier

SDE_TVS_OUH_Proj_12

Website

Developing tools for pre-market evaluation and post-market surveillance of Medical Imaging AI - gtr.ukri.org

JivaRDX

JivaRDX

Premarket evaluation of JIVA's AI tool using retrospective patient data sourced from Oxford University Hospitals SDE and the RAIQC pre-market evaluation platform.

Organisation

RAIQC Ltd

Unique project identifier

SDE_TVS_OUH_Proj_13

Website

Developing tools for pre-market evaluation and post-market surveillance of Medical Imaging AI - gtr.ukri.org

OxPOS

Oxford Precision Oncology for Sarcoma (OxPOS)

The project is a prospective, observational study of patients with sarcoma. It will involve the collection of additional blood and tissue samples for genetic analysis. It will involve also the re-use of clinical and laboratory data - in particular, medical imaging - collected in the course of routine care.

The purpose of the study is to provide information that will improve the diagnosis and treatment of sarcoma: a disease with relatively low survival rates (currently 55 percent at five years).

Organisation

Roche

Unique project identifier

SDE_TVS_OUH_Proj_14

Website

OxPOS: Oxford Precision Oncology for Sarcoma - Health Research Authority

Radiology Reports

Automated generation of radiology reports from PET-CT scans using machine learning

The primary aim of this project is to assess the feasibility of creating pre-reports to assist radiologists in radiology report writing for PET-CT scans. The quality of the generated pre-reports will be assessed with a variety of metrics designed to capture clinical accuracy and readability of reports and similarity to the 'real' reports which will be an outcome measure of this study.

The clinical accuracy refers to firstly diseases being correctly identified, and secondly changes from previous scans correctly captured. The readability and similarity of the reports will be assessed by more common NLP metrics with scores such as: BLEU, METEOR, ROUGE.

By stratifying the data based on the ID of radiologists that compiled the original report, we will also assess whether the AI generates reports that agree equally well with the reports generated from different radiologists or there is model bias to specific writing style.

The proposed research will generate novel techniques for jointly modelling visual and textual information from medical databases, an area where current generation of algorithms is still inadequate. Such models will be able to extract wealth of information from routinely produced radiology reports to learn how to better detect pathologies in medical scans.

When these models make a prediction for the existence of a pathology in a new scan, these models will also be able to generate explanations for their prediction in natural language that can be easily interpreted by the human user. These mechanisms will enhance predictive performance and explainability of the models, factors that are necessary for reliable adoption of such tools in clinical workflows.

Organisation

University of Oxford

Unique project identifier

SDE_TVS_OUH_Proj_15

Website

MCGOWAN GROUP - Department of Oncology

BTRU

NIHR Health Informatics Collaborative (HIC) Patient Blood Management and Perioperative Care. Blood and Transplant Research Unit (BTRU)

The overall aim for the NIHR HIC Patient Blood Management and Perioperative Care research database is to improve patient blood management for patients with or at risk of anaemia, who may require blood transfusion, by building and curating a database of highly granular, longitudinal electronic healthcare record data.

Patient Blood Management (PBM) is the systematic and patient-centred approach taken to conserve blood and minimise transfusion rates to improve patient outcomes and reduce costs. Approximately half of hospital inpatients have anaemia. This area of research has been prioritised in light of recent national blood shortages.

Organisation

University of Oxford

Unique project identifier

SDE_TVS_OUH_Proj_16

Website

NIHR BTRU in Data Driven Transfusion Practice - Radcliffe Department of Medicine

CSOR

Children's Surgery Outcome Reporting system

CSOR is a collaboration between the National Perinatal Epidemiology Unit (NPEU), based at the University of Oxford, and ten hospitals across England and Scotland. The team includes paediatric surgeons, other healthcare professionals, researchers, IT specialists and parents of children with surgical conditions, led by Professor Marian Knight and Professor Simon Kenny. Mr Benjamin Allin is responsible for the day-to-day management of the programme.

CSOR utilises the NIHR Health Informatics Collaborative (HIC) Data Sharing Framework.

Organisation

University of Oxford

Unique project identifier

SDE_TVS_OUH_Proj_17

Website

Children's Surgery Outcome Reporting (CSOR) Research Database

DART

The Integration and Analysis of Data Using Artificial Intelligence to Improve Patient Outcomes with Thoracic Diseases (DART)

The DART project will collect and transfer clinical data, CT scans, digitised images of stained tissue sections (digital pathology) and blood-derived data from the consented participants of the lung cancer screening programme to Oxford.

Organisation

University of Oxford

Unique project identifier

SDE_TVS_OUH_Proj_18

Website

Want to know more about the DART project aims and objectives? | DART

FAME

The Fractured Ankle Management Evaluation (FAME) Study

This project is designed to investigate the feasibility of extracting data for an economic evaluation of participants within the FAME trial (ISRCTN67007305) from the routine health record.

Once the feasibility has been determined, the process will be used in future clinical trials and the code generated shared with other NHS sites involved in the study.

Organisation

University of Oxford

Unique project identifier

SDE_TVS_OUH_Proj_19

Website

FAME Overview - The FAME Study

GAinS

Genomic Advances in Sepsis (GAinS)

The overall aim of this study is to understand how and why some patients have an extreme response to infection in order to improve patient care.

To achieve this objective, we propose to establish a sample collection from patients with sepsis and a comparator control group of patients admitted into hospital for non-septic causes to enable application of cutting edge immunological and -omic technologies that will enable us to investigate the dysregulated innate immune response seen in patients with sepsis.

Organisation

University of Oxford

Unique project identifier

SDE_TVS_OUH_Proj_20

Website

Sepsis patients could get the right treatment faster based on their genes - Immunology

IORD

Infections in Oxfordshire Research Database (IORD)

The Infections in Oxfordshire Research Database (IORD) is an important part of the Modernising Medical Microbiology and Big Infection Diagnostics research theme. It includes routinely collected electronic data from hospital and GP records, covering about one percent of England.

The overall goal of IORD is to improve the management of infections and potentially infection-related episodes in UK hospitals.

Organisation

University of Oxford

Unique project identifier

SDE_TVS_OUH_Proj_21

Website

IORD | NIHR Oxford Biomedical Research Centre

Colorectal Cancer

NIHR Health Informatics Collaborative (HIC) Colorectal Cancer

The aim of the project is to collect detailed information from a number of the UK's major colorectal cancer centres. This information will provide a significant data resource outside of a clinical trial setting, to help our understanding of the factors that are important in the outcome of patients presented with colorectal cancer, which helps the development of new and improved treatments and medicines.

Organisation

Oxford University Hospitals NHS Foundation Trust

Unique project identifier

SDE_TVS_OUH_Proj_22

Website

Cancer: Colorectal - Health Informatics Collaborative

Liver Disease and Viral Hepatitis Research Database

NIHR Health Informatics Collaborative (HIC) Liver Disease and Viral Hepatitis research database

The NIHR Health Informatics Collaborative (HIC) viral hepatitis and liver disease theme is collecting electronic health care records from people infected with viruses that predominantly affect the liver, to use in research for patient benefit. Our main focus is currently advancing hepatitis B research.

Chronic hepatitis B infection affects 254 million people globally and caused around 1.1 million deaths in 2022, primarily from cirrhosis and liver cancer (hepatocellular carcinoma [HCC]). We are leading a nationwide initiative, building on clinical expertise to collect and analyse mass real-world data from electronic patient records using multidisciplinary techniques (informatics, engineering, and analytics).

This programme aims to understand the clinical trajectories and outcomes of HBV infection, including responses to antiviral therapy, development of advanced liver disease stage and liver cancer (HCC), and HBsAg loss. We are also evaluating the impact of recently expanded treatment guidelines, the effectiveness of combination antiviral therapies, and examining how other health conditions (comorbidities) and metabolic factors affect disease outcomes.

Additionally, we are investigating factors associated with care discontinuation. Hepatitis D virus (HDV) coinfection, which may worsen outcomes in people with hepatitis B, will also be characterised in terms of its prevalence in the UK and its impact on progression to severe liver disease. By informing intervention and care strategies, this programme is working towards better patient care and health outcomes for people living with hepatitis B in the UK and globally.

Organisation

Oxford University Hospitals NHS Foundation Trust

Unique project identifier

SDE_TVS_OUH_Proj_23

Website

Viral Hepatitis and Liver Disease - Health Informatics Collaborative

Lung Cancer Radiomics

Lung Cancer Radiomics

This project aims to develop a novel deep learning segmentation method that can reliably segment a single tumour into different subregions according to its heterogeneity using complementary information provided in PET/CT images for lung cancer patients.

These novel subregional segmentations will allow the automated extraction of clinically interesting features (e.g. radiomics) that can support personalised decision-making process.

Ultimately, the project will also seek to link genetic mutation of the patients to the radiomics features observed in the PET/CT images. Merging genetic and imaging information can further enhance treatment planning and patient outcome predictions.

This project will bring valuable biological insights, such as understanding what phenotypic features make tumours more aggressive.

Organisation

University of Oxford

Unique project identifier

SDE_TVS_OUH_Proj_24

Website

MCGOWAN GROUP - Department of Oncology

ORCHARD

Oxford Cognitive Comorbidity and Ageing Research (ORCHARD) - Clinical Record Interactive Search (CRIS) Dementia Linkage Project

Primary objective

To develop a semi-automated CT-brain analysis tool to extract standardised data on stroke lesions, white matter disease and brain atrophy.

Secondary objectives

1. To extract data on markers of brain ageing (stroke lesions, white matter disease and brain atrophy) from standard NHS-acquired CT-brain and MR-brain imaging for linkage to EPR clinical data and clinical research data. The linked data will be used to determine the factors associated with delirium and cognitive decline in acutely hospitalised patients including those with stroke.
2. Use the resulting CT-brain and MRI-brain analysis tools as the basis of an application for external funding towards a clinically approved tool for use in routine clinical practice.

Organisation

University of Oxford

Unique project identifier

SDE_TVS_OUH_Proj_25

Website

Old Age Neuroscience and the ORCHARD portfolio - Nuffield Department of Clinical Neurosciences

OxPOS Health Economics

Oxford Precision Oncology for Sarcoma (OxPOS) Health Economics Project

Health economics is important for medical research. By comparing the health benefits and costs of medical treatments, diagnostic tools, and ways of organising care, economists provide evidence to guide better ways of spending the NHS budget.

Sarcoma patients could benefit from innovations like more accurate and comprehensive diagnostic tests and digital tools that help doctors access and interpret patient records. These innovations, currently being tested as part of the Oxford Precision Oncology for Sarcoma study, have the potential to improve the quality of care patients receive and reduce healthcare costs.

The health economics project within this study aims to provide the NHS with data to decide if these innovations are worth adopting.

Organisation

University of Oxford

Unique project identifier

SDE_TVS_OUH_Proj_26

PARADISE

Predicting AF after Cardiac Surgery - the PARADISE Score

A Clinical Prediction Rule for Post-operative Atrial Fibrillation in Patients Undergoing Cardiac Surgery.

Organisation

University of Oxford

Unique project identifier

SDE_TVS_OUH_Proj_27

Website

Welcome to PARADISE | PARADISE

STARLIGHT

Towards a STandardised diagnostic pAthway for hypeRtension using routine hospitaL data: An InvestiGation of the Health and economic ouTcomes (STARLIGHT)

The aim of the STARLIGHT study is to assess the value of implementing a diagnostic prediction model for hypertension within a standardised care pathway that integrates patient information between secondary and primary care.

Organisation

University of Oxford

Unique project identifier

SDE_TVS_OUH_Proj_29

Website

STARLIGHT - Health Research Authority

True Colours

True Colours (Inflammatory Bowel Disease Quality of Life Study)

Post Operative Quality of Life assessment in Stricturing Crohn's Disease: A Digital Exploration with the True Colours App.

Organisation

University of Oxford

Unique project identifier

SDE_TVS_OUH_Proj_30

Website

True Colours