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Research Theme

Digital Health from Hospital to Home

You are here: Home > News > News for Digital Health from Hospital to Home

News for Digital Health from Hospital to Home

New Maternity Early Warning Score to be implemented across the NHS

16 May 2024 · Listed under Digital Health from Hospital to Home

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Researchers in Oxford have developed a new maternity early warning score that is derived from patient data. The new system, which is being rolled out across the English NHS, will help healthcare providers identify and respond to signs of deterioration in pregnant women. Maternity Early Warning ... READ MORE

Researchers develop easy-to-deploy federated learning system that safeguards patient data

24 January 2024 · Listed under COVID-19, Digital Health from Hospital to Home, Translational Data Science

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Researchers in Oxford have developed a new, easy-to-use technique for hospitals to contribute to the development of artificial intelligence (AI) models, without patient data leaving the hospital’s premises. The technique, which builds on recent advances in decentralised machine learning, uses ... READ MORE

Research profile: Clinical nurses helping to shape our medical knowledge

10 July 2023 · Listed under Digital Health from Hospital to Home

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Yuhan Zhang is an Advanced Nurse Practitioner in Oxford University Hospitals’ Ambulatory Outreach Team. She is also in the second year of a nursing doctorate at Oxford Brookes University, for which she is getting support from the NIHR Oxford Biomedical Research Centre (BRC). Yuhan works in an ... READ MORE

No benefit found in switching to citrate anticoagulation for ICU kidney injury treatment

16 December 2022 · Listed under Digital Health from Hospital to Home, Translational Data Science

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New research has found no added benefit of using citrate-based drugs in the treatment of acute kidney disease in intensive care, when compared to the anticoagulation drug heparin, despite their extra cost. People with acute kidney injury (when the kidneys stop working correctly) may need a ... READ MORE

One in eight people have undiagnosed nighttime hypertension

22 September 2022 · Listed under Cardiovascular Medicine, Digital Health from Hospital to Home, Preventive Neurology

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Around 15 percent of people aged between 40 and 75 may have a form of undiagnosed high blood pressure (hypertension) that occurs only at nighttime. Because they do not know about this, and are therefore not being treated for it, they are at a higher risk of cardiovascular disease such as ... READ MORE

OUH nurse researcher gets award to further study

6 September 2022 · Listed under Digital Health from Hospital to Home

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A Clinical Academic Nurse Researcher at Oxford University Hospitals (OUH) has been given an award by the British Federation of Women Graduates (BFWG) to continue her research exploring how to improve the escalation of care for patients whose condition deteriorates in the hospital setting. Jody ... READ MORE

Doctors making AI-assisted decisions more accurate and confident in decision-making

17 December 2021 · Listed under Cardiovascular Medicine, Digital Health from Hospital to Home, Imaging

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New research has shown that doctors who use an artificial intelligence (AI) algorithm to assess echocardiograms are more accurate and more confident in their decision making. The study, published in the journal JACC Cardiovascular Imaging, is the first to show that an algorithm can ... READ MORE

QCOVID study identifies vaccinated groups at highest risk hospitalisation and death

25 October 2021 · Listed under COVID-19, Digital Health from Hospital to Home

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Researchers from the University of Oxford have identified which vaccinated people are at greatest risk from severe Covid-19 leading to hospitalisation or death, from 14 days after the second dose of vaccination, when substantial immunity should be expected. The research used the QCovid tool, ... READ MORE

Researchers develop algorithm to diagnose deep vein thrombosis

15 September 2021 · Listed under Digital Health from Hospital to Home, Gene and Cell Therapy, Oxford Blood Group

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Researchers are developing an artificial intelligence (AI) algorithm to diagnose deep vein thrombosis (DVT) more quickly and as effectively as traditional radiologist-interpreted diagnostic scans, potentially cutting down long patient waiting lists and avoiding patients unnecessarily receiving drugs ... READ MORE

BRC-supported study receives Best Research Paper Award

9 August 2021 · Listed under Cardiovascular Medicine, COVID-19, Digital Health from Hospital to Home, Multimorbidity and Long-Term Conditions, Translational Data Science

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A leading cardiology journal has named an academic paper written by Oxford BRC-supported researchers as its best research paper of 2020. The paper – which found that two common heart medication do not increase the risk of COVID-19 hospitalisation – was named by the BMJ Heart journal as the ... READ MORE

Oxford wins government funding to evaluate prostate cancer detection system

16 June 2021 · Listed under Cancer, Digital Health from Hospital to Home, Molecular Diagnostics

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A prostate cancer detection software system to help pathologists quickly identify suspicious areas of tissue, developed by the digital diagnostic company Paige, will be investigated in a multicentre clinical study led by the University of Oxford as part of a successful NHSX Artificial Intelligence ... READ MORE

Study challenges idea of clinically significant mid-pregnancy drop in blood pressure

28 April 2021 · Listed under Digital Health from Hospital to Home

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An international study involving NIHR Oxford BRC researchers has shown where normal blood pressure in pregnancy should be across the world and when clinicians should react because it is abnormal. The study’s findings, published in PLOS Medicine, provide international, gestational age-specific ... READ MORE

Oxford academics named NIHR Senior Investigators

3 March 2021 · Listed under Digital Health from Hospital to Home, Inflammation across Tissues, Life-saving Vaccines, Musculoskeletal, Other News, Surgical Innovation, Technology and Evaluation

Four academics supported by the NIHR Oxford Biomedical Research Centre have been awarded a prestigious national award. The University of Oxford  professors have been named National Institute of Health Research (NIHR) Senior Investigators in recognition of being “among the most prominent and ... READ MORE

Machine learning system developed to identify deteriorating patients in hospital

5 February 2021 · Listed under Digital Health from Hospital to Home

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Researchers in Oxford have developed a machine learning algorithm that could significantly improve clinicians’ ability to identify hospitalised patients whose condition is deteriorating to the extent that they need intensive care. The HAVEN system was developed as part of a collaboration ... READ MORE

Using AI to improve the quality of endoscopy videos

25 November 2020 · Listed under Cancer, Digital Health from Hospital to Home, Inflammation across Tissues

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A multidisciplinary team of researchers has developed a deep-learning framework for improving endoscopy to aid the detection of cancer and other gastrointestinal diseases. Cancers detected at an earlier stage have a much higher chance of being treated successfully. The main method for ... READ MORE

Eight BRC projects get RCF funding

7 September 2020 · Listed under Cancer, Cardiovascular Medicine, Digital Health from Hospital to Home, Gene and Cell Therapy, Genomic Medicine, Imaging, Inflammation across Tissues, Metabolic Experimental Medicine, Molecular Diagnostics, Multimorbidity and Long-Term Conditions, Preventive Neurology, Surgical Innovation, Technology and Evaluation, Translational Data Science

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Eight Oxford BRC proposals, many covering a number of themes, have been awarded NIHR Research Capability Funding (RCF) funding to take forward key areas of research. The selected projects that will be supported include: Developing a research centre devoted to urgent and acute careThe ... READ MORE

Common heart medication does not increase risk of COVID-19 hospitalisation

10 August 2020 · Listed under Cardiovascular Medicine, COVID-19, Digital Health from Hospital to Home, Translational Data Science

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A study by Oxford researchers, supported by the NIHR Oxford Biomedical Research Centre (BRC), found that ACE inhibitors and ARBs – both common treatments for high blood pressure and heart failure – are not generally linked to an increased risk of severe COVID-19 disease or an increased likelihood of ... READ MORE

Oxford leads development of risk prediction model for smarter COVID-19 shielding advice

23 June 2020 · Listed under COVID-19, Digital Health from Hospital to Home, Multimorbidity and Long-Term Conditions

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People at highest risk of serious illness from SARS-CoV-2 infection may soon have access to better shielding advice based on a new data-driven risk prediction model being developed by an Oxford University-led team. The Principal Investigator, Professor Julia Hippisley-Cox of the ... READ MORE

BRC Technology Co-theme Lead appointed as NIHR Health Technology Assessment Programme Director

13 May 2020 · Listed under Digital Health from Hospital to Home

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Professor Andrew Farmer, the Oxford Biomedical Research Centre’s Co-theme Lead for Technology and Digital Health and an experienced general practitioner, begins a new role with the NIHR on 1 June 2020 as Health Technology Assessment (HTA) Programme Director. He will take over from Professor Hywel ... READ MORE

BRC funds new COVID-19 research projects

6 April 2020 · Listed under COVID-19, Digital Health from Hospital to Home, Imaging, Multimorbidity and Long-Term Conditions, Respiratory Medicine

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The NIHR Oxford Biomedical Research Centre (BRC) has allocated funding to three COVID-19 research projects in an attempt to improve treatment, understand how the virus interacts with chronic diseases, and the longer-term effects of infection on organs. The funding, originally earmarked for BRC ... READ MORE

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Digital Health from Hospital to Home

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  • Digital Health from Hospital to Home
  • Sub-theme 1: Enhancing patient care from the hospital to the home
  • Sub-theme 2: Identifying undiagnosed conditions
  • Sub-theme 3: Minimising hospitalisation with virtual wards
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