Identifying Key Psychosocial Predictors of Hospital Readmission Among Older Adults

Dr Adrian Yeow, senior lecturer of the Accountancy programme at the SUSS School of Business, together with researchers from Ng Teng Fong General Hospital, Geriatric Education and Research Institute, and Nanyang Technological University, recently signed a Research Collaboration Agreement to work on a healthcare AI project, which aims to develop a more holistic set of predictors of hospital readmission among geriatric patients. 

One in five older adults aged 65 years and older hospitalised in Singapore public hospitals are readmitted within 30 days of discharge. Hospital readmissions are distressing to patients, burdensome to their families, and costly for the healthcare system. While information on typical predictors may be extracted from structured data in electronic health records (EHR), psychosocial risk factors are largely embedded as unstructured data which are challenging to extract.

Additionally, the goal of the project is to also use machine learning and text mining techniques to build a psychosocial profile of patients to complement existing systems that rely mainly on clinical and administrative variables in order to improve hospital readmission prediction and interventions.