Title: What do data tell us about frailty?
Speaker: Lara Johnson
My research integrates data science and geriatric medicine to explore what different data sources and methods can tell us about frailty, a state of increased vulnerability to adverse health outcomes for individuals of the same chronological age. I am looking at how the number and combination of health issues people have – a proxy measure for frailty – relate to their functioning ability (such as their ability to make a cup of tea, get dressed or walk up a flight of stairs) and adverse health outcomes (death, falls, fractures, care needs). This will inform the development of a data-driven definition of frailty (currently lacking), which is useful both for identifying patients in later life at highest risk as well as forecasting demand on health and social care services. My research aims to answer questions such as whether there are different types of frailty, whether frailty manifests differently in men vs. women (who are more frail but live longer) and whether distinguishing between types of frailty improves the performance of prediction models.