Driving innovative Health and Social Care
One of the best-known health informatics centres in the UK
The organisations that form the National Health Service (NHS) – and those that provide social care – form a multi-billion pound business sector that impacts on the lives of every single person in the UK.
Thousands of people lose their lives in hospital each year because deterioration in their condition is not spotted early enough for treatment to be effective. An ageing population also means there's an ever-expanding demand for healthcare.
At the Centre for Healthcare Modelling and Informatics, we're working to develop technology that can make the work of these organisations more efficient. We conduct research that aims to make the NHS and social care services better for society.
We're using our information systems and computer science expertise to make the day-to-day jobs involved in healthcare delivery and administration easier. We're using our established links with healthcare and social care professionals to research new solutions to relevant problems – and providing knowledge and expertise to organisations and individuals that want to adopt information, communication and sensing technologies.
And because there's a growing need for better technology that can provide solutions that enable healthcare to be delivered at scale, we're looking for ways to deliver the technology required – and to equip healthcare professionals with the knowledge and skills to use it.
Our researchers covers the following areas of expertise:
Applied Health Informatics
We're researching the effective design and use of IT in health and social care to improve how practitioners communicate with patients and to promote patient wellbeing
Clinical Outcome Modelling
We're developing and evaluating mathematical and computer models, and collaborating with the NHS, to help make accurate healthcare predictions using health data science. Explore our clinical outcome modelling research.
We're investigating how information technology – including communications and sensors – can be help people live long and healthy lives.
Funders and collaborations
We collaborate with clinical colleagues at Portsmouth Hospitals NHS Trust. This underpins our clinical outcome modelling work, and the projects in that area. We use anonymised data from the hospital to conduct our research.
We collaborate with academic institutions nationally, including the University of Southampton, and the University of Oxford. Our academic collaborations give us access to specialist skills in areas complementary to our own.
Our work has been funded by various organisations and institutions, including the National Institute for Health Research, Innovate UK, the Engineering and Physical Sciences Research Council, and the Health Innovation Challenge Fund.
We're involved in several major projects:
- The background data analysis work that led to the development of the National Early Warning Score (NEWS) by the Royal College of Physicians. NEWS is the method adopted by all British hospitals to convert a patient's vital signs measurements into a measurement of their risk.
- We're looking at how NEWS can be expanded to include other clinical information, such as blood test results, to provide a better means of identifying which patients need to be considered for intensive care.
- We looked at the extent to which a reduced level of nurse staffing affects a patient's outcome.
- We have begun a study to answer questions about how frequently nurses need to take vital sign measurements.
- We are interested in the ways in which people can be monitored at home, or in a residential care home, to better identify those at risk of deterioration. This includes technology to monitor the person's health and how that information can be used by healthcare providers such as the NHS.
- We are investigating how better health and well-being can be achieved through support from technology, such as smartphone apps.
- We are researching how hospitals and other NHS organisations share data, to provide the most effective and efficient service to patients.
- We are interested in how computer vision can help understand, reconstruct and process facial and human actions and visual scenes.