Falls cost the NHS £2.3bn per year and devastate the personal independence of thousands of older adults. Proactive falls prevention can help prevent future injury and NHS costs. Identifying those at risk of falls is the first step to targeted falls prevention. However, existing prediction models have significant limitations and as a result, are not currently recommended in NICE guidance. eFalls is a comprehensive and externally validated prediction model aimed at supporting proactive falls prevention services. It uses existing information from the primary care record to generate the percentage risk a person has of having a fall that requires A&E attendance or hospital admission in the next 12 months. Having a systematic, digital solution to identify those at risk of falls means that clinical time and services can be directed away from case finding and towards proactive prevention for those most in need. If through the application of the tool, services were able to prevent just 25% of serious falls a year in England, this would save the NHS more than £140m annually.
Current progress and next steps:
•tool developed, externally validated and paper published
•working with NHSE and NICE to explore inclusion in national policy guidance
•piloted tool in primary care electronic patient records in Greater Manchester
•tool adopted in Norfolk and Waveney ICB (following ‘localisation’ i.e. recalibration using locally available data to ensure well suited to local population)
•planned roll out of tool in large Primary Care Network in Bradford
•will submit as impact case story for 2025/26 annual report
Head of Academic Unit for Ageing and Stroke Research and Theme Lead for Health and Care in our Ageing Society theme