- Providing interoperability between different clinical systems, across care settings’ boundaries, and semantically integrating clinical and research systems (e.g., with digitally enhanced medical terminology services and ontology-based approaches) in order to achieve effective impact of research into practice.
- Bridging the translational gap between research and care provision, through the innovative development of e-trial systems, novel analytics methodologies and meta-analysis approaches.
- Implementing new integrated care platforms to measure, analyse and communicate health data to all levels of healthcare delivery.
- Promoting wellbeing through patient-empowerment solutions (e.g., m-health and wellbeing apps) and supporting patient behavioural change.
- Modelling and analysing quality and service improvements of care, through healthcare systems engineering approaches.
- Clinical IT Safety, including areas on digital architectures improving patient safety, safety analysis techniques (e.g. FMEA) for healthcare services, assurance of complex socio-technical healthcare services, interpretation of safety standards such as SCCI 0160, and ISO 13485, clinical safety cases, and failure analysis of integrated digital healthcare.
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- Making sense of health and wellbeing data, in order to improve public health and clinical knowledge in the characterisation and management of disease, through novel biomedical informatics technologies (e.g., connected healthcare information systems, electronic healthcare records, clinical decision support systems, etc.).
- Developing methodologies, based on advanced statistical learning, machine learning and AI approaches, for the analysis of complex biomedical datasets in the context of non-communicable and chronic diseases in order to achieve a personalized medicine perspective in the provision of care.
- Developing further the emerging field of Radiomics to achieve more accurate prediction of disease progression, responsivity to treatments, and patients’ survival in cancer. In particular, investigating the application of informatics and advanced computer algorithms to provide an intelligent decision support aid to clinicians for the characterisation of childhood brain tumours.
We offer expertise and capability in AM to industry, both in support of their New Product Introduction activities and also in providing a secure and supportive environment in which new manufacturing approaches can be evaluated in their business and new business models may be explored.
Health Informatics and Health Data Science
Our overall objective is to improve the quality, safety, accessibility and productivity of healthcare by supporting the implementation of digital solutions for the public, patients and professionals, underpinned by rigorous multi-disciplinary research, development and evaluation. Our model of research-led innovation in healthcare entails identifying relevant theories, selecting appropriate technologies and developing new solutions where necessary. Each solution then needs rigorous evaluation for safety, effectiveness and cost implications before promotion to healthcare systems. All this requires close working with industry, the NHS and across many disciplinary boundaries In order to achieve translational impact in society.
In the theme of Healthcare Informatics and Health Data Science our work concentrates in understanding healthcare data, through the concept of electronic healthcare records, and make it more readily available to provide a core facility in understanding the complexity of disease.
Such data can also provide better insights for the whole patient journey in the context of chronic conditions. Quality digital healthcare data, combined with our current evidence-based medical knowledge, allows professionals to make more precise, stratified/personalised and informed decisions on care provision and patient support. Moreover, the transparent use of this information can empower the individual patient in their awareness of health and wellbeing, by involving them in their own healthcare management; this is achieved through the provision of feeding back information to the individual themselves for improved understanding of their condition and lifestyle needs, through the use of digital means.
In addition to information, digital technology can provide independence in patients’ lives, by supporting them in enhanced and integrated activity within our societal structures. Finally, technology can promote the concept of a digital community, where patients, careers and citizens can exchange views and information on the best available choices for people’s care and support.
The integration of healthcare data and electronic healthcare records improves the understanding of the complexity of disease, and the whole patient journey in the context of chronic conditions. Our work is focused on enabling professionals to make more precise, stratified/personalised and informed decisions on care provision and patient support, and in the use of technology to support patients and improve lives.