Title: Challenges in predicting rehabilitation requirements for older patients
Speaker: Konstantin Georgiev
An ageing population is a major success of modern healthcare, but this challenges the NHS to better support increasingly frail hospitalisations. One third of older people acquire a new disability by discharge, leaving hospital with less independence than before getting ill. Rehabilitation attempts to maximise recovery, but this is not well targeted to people at the highest risk of disability, as the true contributing factors are poorly understood. However, electronic health records now routinely hold information about rehabilitation progress. This brings forward a new opportunity to utilise this data and build structured care pathways using Machine Learning, Process Mining and Explainable AI tools.
In this talk, I will give an introduction to the current challenges in rehab, particularly the complexity in deciding the duration, intensity and type of treatment for frail and multimorbid patients. We will also briefly look at one case study involving rehab patterns for patients recovering from COVID-19.