Quantifying the longitudinal value of healthcare record collections for pharmacoepidemiology.

We introduce an information score for longitudinal healthcare record data, specifically in the monitoring of chronic conditions. The score is designed to capture the value of different observation patterns in terms of shaping and testing clinical epidemiological hypotheses. The score is first developed for the simple case where equally spaced observations are most informative, then extended to a more context-specific version where the optimal density of observations can be elicited. It can be interpreted as a measure of the average quantity of information provided by each observation in an individual's time course, where information is lost whenever the observation density deviates from a defined optimal density. We illustrate the score on routine healthcare records from the population of Salford, UK - focusing on repeat testing of liver function in people with common long-term conditions. We demonstrate validity of the score in terms of concordance between score levels and clinically meaningful patterns of repeat testing.