A foundational model of time for heterogeneous clinical databases

Differences among the database representations of clinical data are a major barrier to the integration of databases and to the sharing of decision-support applications across databases. Prior research on resolving data heterogeneity has not addressed specifically the types of mismatches found in various timestamping approaches for clinical data. Such temporal mismatches, which include time-unit differences among timestamps, must be overcome before many applications can use these data to reason about diagnosis, therapy, or prognosis. In this paper, we present an analysis of the types of temporal mismatches that exist in databases. To formalize these various approaches to timestamping, we provide a foundational model of time. This model gives us the semantics necessary to encode the temporal dimensions of clinical data in legacy databases and to transform such heterogeneous data into a uniform temporal representation suitable for decision support. We have implemented this foundational model as an extension to our Chronus system, which provides clinical decision-support applications the ability to match temporal patterns in clinical databases. We discuss the uniqueness of our approach in comparison with other research on representing and querying clinical data with varying timestamp representations.