Our theme is focused on delivering cost-effective patient benefits through technological innovation. The combination of machine-learning algorithms with emerging digital technologies such as wearable or non-contact sensors, smartphones and computer tablets, gives us an unprecedented opportunity to provide individualised patient care. Devices and algorithms will be taken all the way from initial feasibility studies to clinical deployment and commercialisation.
We will build on the achievements of our highly productive partnership between engineers, biomedical scientists and clinicians. Our partnership was the first in the world to demonstrate non-contact monitoring of oxygen saturation in clinical environments using webcams. Our electronic evidence-based early-warning system (SEND) is now deployed in every adult ward throughout the four acute hospitals in Oxfordshire. Our gestational diabetes self-management smartphone app (GDm-health) is used in four NHS Trusts in the region to manage diabetes during pregnancy.
From the patient’s home all the way to Intensive Care, we are developing monitoring and alerting systems appropriate to the environment and the patient. Two main workstreams will underpin our programme: the design of novel sensor systems to enable reliable, unobtrusive clinical-grade monitoring; and the development of machine-learning algorithms to integrate information from multiple data sources.
In the hospital, reliable ambulatory monitoring data will be fused in real-time with intermittent observation data, to identify those patients who need early intervention to prevent serious deterioration.
In the community, chronic diseases continue to place a major burden on the healthcare system and wider society. These diseases are responsible for unplanned hospital admissions, avoidable morbidity, excess mortality and poor quality of life. Our research targets unplanned admissions (and re-admissions) to hospital, which account for an estimated £11bn a year in the UK. It focuses on avoidable morbidity, using the under-treatment of chronic obstructive pulmonary disease (COPD) exacerbations as an example. We will decrease severe episodes and emergency hospital admissions in people living with COPD.
We will empower people living with chronic diseases to manage their own health, using their self-monitoring and hospital data, to improve their wellbeing and reduce their healthcare resource usage.
Professor Andrew Farmer is a General Practitioner and Researcher based at the Nuffield Department of Primary Care Health Sciences at the University of Oxford. His talk is on care for people with long-term health conditions and on the prospects for using new technologies for improving their health. Why is it taking so long for mobile devices to become part of routine health care? What are the implications for privacy around use of electronic data to support health care? Can wearable monitoring devices replace regular visits to the nurse or doctor?