The Irish longitudinal Study on Ageing began in 2009 with wave 1 and has now completed 4 waves. There are over 1 million data points for over 8,500 participants. This is a random sample of the Irish population and therefore is very representative of community dwelling individuals in Ireland. As a result, findings of TILDA are directly translatable to the Irish population and has considerable potential for informing and transforming public health and health care policy in Ireland.
Data collection in TILDA has now reached a stage where data mining and big data techniques may unearth valuable insights, particularly for the integration of different forms of data such as demographic and economic data with biomarker, biometric and genetic data. The first objective of this project is to explore the relationship between kidney function and cardiac function using data obtained by the Finometer. We will then go on to use machine learning techniques to model and incorporate TILDA data in order to gain insights into such outcomes as kidney disease, syncope, injurious falls, death, hospitalisation, nursing home and care facility admission and medication usage over time. Synergistic with these aims Dr Sexton is also involved in clinical research involving the use of smart phone/device applications to both study and improve outcomes for patients with end stage kidney disease treated by both Haemodialysis and Peritoneal dialysis. The second part of this grant will be to explore the use of big data being collected by these smart phone applications to gain insights into the care of patients with chronic diseases such as kidney failure treated with a kidney transplant or dialysis. The training objective of this grant will be to help Dr Sexton become an independent investigator and an expert in big data applications.
