Predicting Frailty Using Integrated Health and Social Data to Support Preventive, Community-Based Care

About the Project

This project explores how we can better support people to live healthier, more independent lives for longer by predicting frailty earlier using large, real-world datasets. Frailty often develops gradually in the community and is a major driver of hospital admission, loss of independence, and reduced quality of life. However, it is frequently recognised too late, when opportunities for prevention are limited.

The main aim of this project is to investigate how data-driven approaches can be used to identify individuals at risk of frailty earlier, enabling more personalised and preventive care—particularly through emerging models such as “hospital at home.”

Key objectives include:

• Understanding frailty in a community and home-based care context
• Integrating diverse data sources
• Developing personalised prediction approaches
• Supporting preventive and community-based care

Supervisors: Prof Hamde Nazar, Prof Noura Al-Moubayed

Tenure: 3 year PhD