What safety indicators can be derived from the Oxehealth Service and how can they best support care delivery?
Professor John Geddes, Alvaro Barrera et al, writing in BMJ Evidence Based Mental Health:
"Have shown that use of Oxehealth Vital Signs maintains the safety on the ward but enables patients to get a better night’s sleep."
Consequently, our work on safety currently focus on two main sub themes:
We also work closely with groups improving seclusion safety and experience.
We are keen to work with groups working on subjects such as zero suicide, reducing restrictive practice and improving observation regimes in mental health and general medicine.
What cardio-respiratory measurements can be derived from video and how can they best support care delivery?
Clinicians make wide-ranging use of patient’s cardio-respiratory measurements, provided by Oxevision so we collaborate on a wide range of studies in this theme.
Particular areas of clinical engineering focus for us are:
We are open to collaborating with groups rethinking care delivery across inpatient and residential care settings.
What sleep measurements can be derived from video and how can they best support care delivery?
Sleep is crucial to well being and recovery in the patient groups our customers service. Oxevision provides ground-breaking contact free insight into sleep opportunity. We see tremendous opportunity to provide far greater insight into sleep quality and abnormal breathing phenomena using the Oxevision platform.
We have a powerful, longstanding research project into sleep monitoring and sleep apnea detection working with Professor Mike Polkey and his sleep lab team at Royal Brompton and Harefield NHS Foundation Trust.
We would in particular welcome collaborations with practicing physicians working to track and improve sleep on active wards.
What frailty measurements can be derived from video and how can they best support care delivery?
The Oxehealth Service has helped clinicians to reduce falls in a dementia-care ward by 48%. Oxehealth’s vital signs and activity alerts and team of computer vision and machine learning research engineers offer an exciting opportunity to create tools that reliably identify frailty risk factors and earlier warning signs for falls and other frailty-related incidents.
Working with Dr Jordan Bowen and the gerontology team at the John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, our live studies in this area focus on:
We would particularly welcome collaborations to research gait, the quantification of frailty measures and work to create a proxy Barthel scale using computer vision.
How are vision-based monitoring and management tools best integrated into care delivery?
Professor Lionel Tarassenko and the Oxehealth team, working with practising Nursing Directors Tracey Wrench of RDASH and Ade Odunlade of CNWL have seeded the field of vision-based patient monitoring and management* and welcome collaboration from interested academics and practitioners.
In advancing the theory and practice of data-enabled care, we aim to answer two fundamental questions:
Areas of live study include assessing patient and staff experience and documenting success factors for the successful introduction of vision-based patient monitoring and management tools.