A Model for Computing Temporal Eligibility Criteria on Large and Diverse Data Repositories

There have been numerous attempts to build query generators that compute eligibility criteria (EC) for a clinical trial automatically on repositories of patient data. However, one of the challenging key features of EC is the ability to express and compute complex temporal aspects. Existing EC generators has limited temporal capability and those do rely on underlying database technology to perform temporal reasoning. We propose a model that incorporates temporal features of existing generators. However, it separates the computation of the criteria, and in particular the temporal semantics, from the extraction of clinical data from the database to increase the efficiency of execution. We explain the implementation of this model and in particular its temporal algorithm, which runs in O(n log(n)) time where n is the number of clinical facts stored making it more efficient than existing reported generators, where performance, at best, has been reported to be O(n
²
). We perform an empirical validation to demonstrate the results.