Diagnosis of health conditions from administrative data

Dr Lucas Calais Ferreira
lucas.cf@unimelb.edu.au

Project Details

An increasing number of observational studies rely on administrative data for ascertaining diagnoses of acute and chronic health and medical conditions in diverse populations. Such studies greatly benefit from the ability to follow study participants by accessing linked health and medical administrative records. However, the accuracy of administrative data for exposure, covariate and outcome ascertainment has not been adequately quantified. The potential marginal gain from including more than one administrative data source to improve outcome ascertainment is also largely unknown.

In this project, we will quantify the accuracy of ascertaining diagnostic information on a range of priority acute and chronic health and medical conditions through administrative data in the relevant literature, and evaluate the extent to which the inclusion of additional administrative data sources impacts accuracy. This systematic review will generate a fundamental piece of evidence that will inform the many cohort studies worldwide that use administrative data to ascertain health and medical outcomes.