HL7 Transforms – Square Pegs in Round Holes

The HL7 Tower of Babel that currently exists within the health information community can at times seem like an insurmountable obstacle.  The ever increasing number of codified elements has done little to address this problem in ways that can practically be applied, at least on a global scale (e.g. a “one size fits all” mechanism for unifying HL7).

Fortunately, for all but the largest organization, these types of problems are not a large as they first appear to be.  In fact, for most organizations data items within an HL7 message can be expressed in tens, hundreds, or (at worst case) thousands of expected values that need to be routinely shared and understood between health entities.  This is particularly true for health laboratories where the number and nature of tests performed is typically limited.

One of the real advantages of HL7 as a data exchange framework is that it allows us to divide and conquer problems with vocabulary, semantics, and syntax.  We can compartmentalize data exchange issues, creating opportunities to isolate and solve problems on an individual bases.

In this presentation a set of real life HL7 issues and problems will be explored.  These problems will be categorized, and associated general and specific approaches to their solutions offered.  Hands on practical tools will be demonstrated and contrasted.  In particular the Open Health Framework’s HL7 Java based toolkit will be presented as one approach for applying transforms.