The GuideLine Interchange Format (GLIF) is a computer-interpretable language for modeling and executing clinical practice guidelines, currently in the development stage by the InterMed team. GLIF will allow sharing of computer-interpretable clinical guidelines across different medical institutions and system platforms, facilitating the contextual adaptation of a guideline to the local setting and integrating them with the electronic medical record systems. GLIF has a formal representation. It defines an ontology for representing guidelines, as well as a medical ontology for representing medical data and concepts. The medical ontology is designed to facilitate the mappings from the GLIF representation to different electronic patient record systems. We are also developing tools for guideline authoring and execution and a guideline server, from which GLIF-encoded guidelines could be browsed through the internet, downloaded, and locally adapted.

GLIF3.3 ontology in Protege (includes encoded guideliens: depression, flu)
GLIF3.4 ontology in Protege (includes encoded guideliens: cough, hypertension, thyroid)
GLIF3.5 ontology in Protege
GLIF3 ontology, in Protege,  configured for Authoring by domain experts [Level A] (includes guidelines: Depression, headache)

The validation tool is included in the GLIF ontology (version 3.5). To view it, select from the Project menu the option Configure, and check the box PAlConstraintsTab. Next, press on the PalConstraints Tab. Use the '+' on the top to select constraints. Then, press on "Warn about..". Next press on "Evaluate...". If you get a red mark, then click on it to see instances that violate the constraint.
 

Disclaimer: the guidelines encoding was done as part of Intermed research to test the adequacy of the GLIF formalism. They encode only a part of the guidelines, and have not been validated by clinicians or tested with patient cases. They should only be seen as examples of GLIF encoding and not medically valid guidelines.

Project goals
More about GLIF
GLIF.org
Publications

Contact person: Mor Peleg, Stanford Medical Informatics, Stanford University