Health Informatics and Data Science

People with severe mental illness (SMI) are more likely to conditions such as diabetes, heart attack, and stroke and to develop these at a younger age than people without SMI. Outcomes from these diseases, such as complications and further events, are also worse in people with SMI. The reasons for the links between SMI and these types of physical diseases are not fully understood, but metabolic dysfunction (which occurs when there are abnormal chemical reactions in your body) may play a central role. We can measure metabolic function using markers such as obesity, blood pressure, cholesterol, whether the body responds to a hormone called insulin, and levels of sugar in the blood. 

This workstream aims to use existing electronic health records to compare how these markers change over time from when someone is diagnosed with SMI, compared to people without SMI. By doing this we can identify sub-groups of people at higher risk of conditions such as diabetes and at higher risk of these conditions developing at a younger age. We will investigate how these patterns of markers over time differ in men and women and by ethnicity and how they are affected by poverty level, lifestyle and medication use (including for mental illness). This work will allow us to identify and characterise different sub-groups of people with SMI, ultimately leading to improved and better tailored treatment for both mental illness and physical health conditions.