Dynamic risk prediction models for patients in primary care – pilot study


Principal investigator(s)Co-InvestigatorPhD student or Research Fellow(s)Project title
Professor William Henley Dr Venura Perera, Professor Chris Hyde Dr Margaritis Voliotis Dynamic risk prediction models for patients in primary care – pilot study


Lay summary:

When patients visit their GP or attend a hospital appointment, clinical staff routinely record health information about the patient. This includes symptoms, diagnoses and test results, enabling NHS clinicians to monitor the condition of the patient. Doctors and nursing staff use their clinical experience to interpret these data. However, it can be difficult to anticipate when patients are at risk of deterioration in their condition. We will analyse the electronic health data for each patient to see if we can uncover patterns.

We hope to be able to develop a computer or tablet based tool that will detect changes in the patient’s underlying health and wellbeing at an early stage. This would assist the clinical team in intervening early to ensure the patient receives the most appropriate care and could save lives. We plan to begin by developing a system for older patients and to test it out in a GP surgery setting. This has the potential to reduce unplanned hospital admissions and to help patients manage their condition in the community. If successful, this project could lead to the development of similar tools for patients of all ages.