Theme 2: Health informatics
This theme uses electronic health records and other large clinical databases to advance our understanding of the epidemiology and aetiology of cardiometabolic diseases, and their management by health services. The theme uses mega cohorts to evaluate outcomes and determinants of variation (regional or by patient features), and tests policy-relevant hypotheses on healthcare organisation and delivery, in order to improve quality of care.
Large volume datasets (colloquially termed big data) provide valuable insight to the occurrence and progression of conditions, especially chronic diseases with low rates in the population, and diseases that develop over a long period of time.
Using large routinely collected clinical and administrative databases (CPRD, HES, ONS), data from National audits (NICOR) and large cohort studies (UK Biobank), we look to reliably report on the relationship between risk factors or markers and cardiometabolic diseases. For this, we use advanced statistical methods complemented by machine learning techniques. We have an interdisciplinary team of data scientists, epidemiologists, statisticians and clinicians that work closely in translating high impact findings to improving patient outcomes and informing public health policy.