Health Deterioration and Fall Prediction Tool

Predicting Health Deterioration in NHS Home Care

Publicly sourced

The challenge

Preventable hospital admissions, particularly among older adults, place significant strain on the NHS. Falls alone account for over 4 million hospital bed days and cost the NHS an estimated £2 billion per year. However, early signs of deterioration often go unnoticed in home care settings due to limited real-time clinical oversight and a reliance on manual reporting.

The solution

The tool predicts early signs of health deterioration, including fall risk, by analysing vital signs such as temperature, heart rate, and blood pressure. This information is collected by carers, family members, or healthcare professionals using a mobile app. It then generates real-time alerts to enable timely intervention. The system also supports care planning, detects illnesses like flu and COVID-19, and automates routine tasks such as scheduling and documentation.

The results

Predicts a patient's risk of falling with up to 97% accuracy, potentially avoiding up to 2,000 hospital admissions per day.
As of March 2025, the tool is used in over two-thirds of NHS Integrated Care Systems, identifying up to 5,000 high-risk cases daily to enable care at home and reduce hospitalisations by up to 70%.
It is estimated to save the NHS over £1 million per day by reducing A&E attendances and freeing up hospital beds.
Currently used daily by nearly 10,000 home healthcare professionals, boosting staff efficiency and improving patient outcomes.

Details

Organisation name: Department of Health and Social Care (DHSC) / NHS England (NHSE)
Government body: UK Government
User group: Wider public sector
Use case type: Specific
Type of technology: Machine Learning
Phase: Live
Impact: Better Customer experience / Time savings / Cost savings

Links

Content created: 10 July 2025

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