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Predictive models for chronic condition diagnosis

From international studies individuals with intellectual disabilities as they age appear to have a greater variety of health care needs compared to those of the same age and gender in the general population.
It has also been reported that: People with ID are more likely (compared to the general population) to lead unhealthy lifestyles and to not access health promotion and health screening services, contributing to physical ailments in later life.
Health problems of persons with ID are not being recognized.
Lack of specialist knowledge and training is contributing to poor case finding.
Different patterns of diseases and different influences on their likelihood of participation in health promotion practices influence disease diagnosis, health services offered and health care utilization
Ireland has a unique dataset on the ageing and health of adults with intellectual disability, the Intellectual Disability Supplement to the Irish Longitudinal Study on Aging and two waves of data collection have already been completed. There is now an opportunity to look in new ways at the things that might predict diagnosis of disease. This is an area where in datasets the general population there has been use of mathematical models such as the Markov model. There will be a great opportunity for me to learn more about the use of mathematics in this way by working with the IDS-TILDA investigators, Professors McCarron and McCallion and the IDS-TILDA statistician, Dr. Carroll to develop some preliminary Markov models and related algorithms.