Challenges in Interpreting Electronic Health Records and a Case Study in Calibrating eGFR

Electronic health records contain a wealth of information that has not been fully exploited. In the UK, clinical practices have been computerised since the 1990's whereas hospital episode data have been available since about 2005. The clinical informatics has gone significant advancement. It is possible to retrieve millions of patient records over time and across vendors and clinical practices.

In the first part of the talk, I will first present some challenges when processing and modelling health records. In the second part, I will present a case study based on the Quality Improvement Chronic Kidney Disease data set which contains nearly a million patient records. This case study shows how machine learning or pattern recognition techniques can be used to solve a data calibration problem, which otherwise, would have prevented the data from being used for epidemiology studies and worst, could lead to unnecessary referral of patients to specialists.

I will conclude the talk with a personal but possibly biased view of where research should be focused. There is plenty of room for contributions and opportunities for collaboration.