Adding HL7 version 3 data types to PostgreSQL

Y Havinga, W Dijkstra, A de Keijzer - arXiv preprint arXiv:1003.3370, 2010 - arxiv.org
Y Havinga, W Dijkstra, A de Keijzer
arXiv preprint arXiv:1003.3370, 2010arxiv.org
The HL7 standard is widely used to exchange medical information electronically. As a part of
the standard, HL7 defines scalar communication data types like physical quantity, point in
time and concept descriptor but also complex types such as interval types, collection types
and probabilistic types. Typical HL7 applications will store their communications in a
database, resulting in a translation from HL7 concepts and types into database types. Since
the data types were not designed to be implemented in a relational database server, this …
The HL7 standard is widely used to exchange medical information electronically. As a part of the standard, HL7 defines scalar communication data types like physical quantity, point in time and concept descriptor but also complex types such as interval types, collection types and probabilistic types. Typical HL7 applications will store their communications in a database, resulting in a translation from HL7 concepts and types into database types. Since the data types were not designed to be implemented in a relational database server, this transition is cumbersome and fraught with programmer error. The purpose of this paper is two fold. First we analyze the HL7 version 3 data type definitions and define a number of conditions that must be met, for the data type to be suitable for implementation in a relational database. As a result of this analysis we describe a number of possible improvements in the HL7 specification. Second we describe an implementation in the PostgreSQL database server and show that the database server can effectively execute scientific calculations with units of measure, supports a large number of operations on time points and intervals, and can perform operations that are akin to a medical terminology server. Experiments on synthetic data show that the user defined types perform better than an implementation that uses only standard data types from the database server.
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