@ShahidNShah
HL7 Version 3 and semantically interoperable healthcare information
Healthcare Informatics has a good article on HL7 3.0. Many people think that HL7 3.0 is about “XML enabling” HL7 but it’s actually much more than that, especially if you’re interested in semantic integration of healthcare data. From the article:
The limitations of HL7 V2.x … and thus the overarching motivations for the HL7 Version 3 framework, can be summarized as unpredictable message semantics and a consequent lack of scalability, particularly across inter-enterprise boundaries.
HL7 Version 3 addresses these problems with a four-pronged approach:
- The Version 3 RIM spans all healthcare domains and provides consistent and unambiguous definitions of the semantics of structures common to all types of data that is to be exchanged.
- The Version 3 Datatype Specification provides machines with unambiguous semantics for each data element transferred. Datatypes are formally related to allow machine-level constraints or restrictions of a given type for increasingly exact data-element semantics.
- Version 3 includes a formal methodology for binding the common structures to domain-specific concept codes (or other value lists or sets), overseen by the HL7 Vocabulary Technical Committee. This feature enables separation of common structures from domain-specific terminologies, such as vocabularies used in Systematized Nomenclature of Medicine (SNOMED), Digital Imaging and Communications in Medicine (DICOM), Medical Dictionary for Regulatory Activities (MeDRA), Minimum Information About a Microarray Experiment (MIAME)/MicroArray and Gene Expression (MAGE), and Logical Observation Identifiers, Names and Codes (LOINC).
- Version 3 provides several specification-building tools to assist in developing Version 3-conformant, RIM-compliant interchange structures for ANSI balloting in the standards development process.
Shahid N. Shah
Shahid Shah is an internationally recognized enterprise software guru that specializes in digital health with an emphasis on e-health, EHR/EMR, big data, iOT, data interoperability, med device connectivity, and bioinformatics.