The Australian health system is currently transitioning to a fully electronic system.
The Australian health system is currently grappling with the transition to a fully electronic system which will enable health data to be accessed as and when required. Achieving this will rely on the semantic integration of data from multiple sources. Australia has adopted SNOMED CT as the standard clinical terminology for the exchange of clinical data.
The long-term goal of this project is to develop tools and techniques to support the capture, use and analysis of health data in electronic form by exploiting and extending the formal description logic foundation of SNOMED CT.
Research topics that will be addressed include:
- Concepts that are not representable using clinical terms from an existing ontology
- The large size of the existing ontology
- Errors and inconsistencies in the existing ontology
- Evolution of the ontology over time
- Management of concrete domains – how to incorporate numeric values into SNOMED CT
The tools described below are designed to make the use of the SNOMED CT and related terminologies as simple as possible, reducing the need for a deep technical knowledge of the standards and data formats to begin capturing or working with the codes and the hierarchies.
A terminology server designed to support the requirements of SNOMED CT tooling including the ability to manage multiple SNOMED CT extensions, subsumption queries, and SNOMED CT Reference Sets. Includes support for the Australian Medicines Terminology and reasoning with numbers as well as LOINC, and ad hoc taxonomies.
A fast modern browser for SNOMED CT and AMT – requires a modern web browser (IE8 and earlier not supported)
A classification engine that has been licensed to the IHTSDO and NEHTA for use in the SNOMED Workbench for the ongoing maintenance of SNOMED CT internationally. Snorocket is fast, able to classify SNOMED CT at least an order of magnitude faster than other known classifiers.
The Snapper Platform is an application that enables the description of existing clinical terminology terms using concepts or expressions from SNOMED CT.
The mapping of existing data to expressions using an ontology involves:
- Normalising the expressions, which may contain multiple codes from an ontology, for consistency purposes
- Calculating subsumption relationships, so that the relationship between expressions is understood
- Finding efficient ways to process the existing ontology extended with new terms and relationships
The Snapper Platform is not bound to SNOMED CT, and other ontologies can be used as an alternate target ontology.