Translating arden MLMs into GLIF guidelines-a case study of hyperkalemia patient screening

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

To re-examine the validity of the medical knowledge that are embedded in the legacy system, we translated a Medical Logic Module (MLM) for hyperkalemia patient screening into the GuideLine Interchange Format (GLIF). We used a set of guiding principles to direct the translation. In addition, we used the GLIF3 Guideline Execution Engine (GLEE) as a testing tool to validate the encoded GLIF guideline by applying it to 5 simulated patient cases. The result has shown that it is possible to translate Arden MLMs into GLIF guidelines. However, significant efforts are necessary to handle the problems arose during the translation process. Automatic translation could be a more generalizable approach for future work.

Original languageEnglish (US)
Title of host publicationComputer-Based Support for Clinical Guidelines and Protocols - Proceedings of the Symposium on Computerized Guidelines and Protocols, CGP 2004
PublisherIOS Press
Pages177-181
Number of pages5
ISBN (Print)158603412X, 9781586034122
DOIs
StatePublished - Jan 1 2004
Externally publishedYes
EventSymposium on Computerized Guidelines and Protocols, CGP 2004 - Prague, Czech Republic
Duration: Apr 12 2004Apr 14 2004

Publication series

NameStudies in Health Technology and Informatics
Volume101
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Other

OtherSymposium on Computerized Guidelines and Protocols, CGP 2004
CountryCzech Republic
CityPrague
Period4/12/044/14/04

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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  • Cite this

    Wang, D. (2004). Translating arden MLMs into GLIF guidelines-a case study of hyperkalemia patient screening. In Computer-Based Support for Clinical Guidelines and Protocols - Proceedings of the Symposium on Computerized Guidelines and Protocols, CGP 2004 (pp. 177-181). (Studies in Health Technology and Informatics; Vol. 101). IOS Press. https://doi.org/10.3233/978-1-60750-944-8-177