@inproceedings{874eeeba6b944c50a40b36db3cc18fe1,
title = "Sharable appropriateness criteria in GLIF3 using standards and the knowledge-data ontology mapper",
abstract = "Creating computer-interpretable guidelines (CIGs) requires much effort. This effort would be leveraged by sharing CIGs with more than one implementing institution. Sharing necessitates mapping the CIG's data items to institutional EMRs. Sharing can be enhanced by using standard formats and a Global-as-view approach to data integration, where a common data model is used to generate standard views of proprietary EMRs. In this paper we demonstrate how generic guideline expressions could be encoded in the GELLO standard using HL7-RIM-based views. We also explain how the Knowledge-Data Ontology Mapper (KDOM) can be used to simplify GELLO expressions. We are aiming to use this approach for computerizing radiology appropriateness criteria and linking them with EMR data from Stanford Hospital. We discuss our initial study to assess whether such computerization would be possible and beneficial.",
keywords = "Appropriateness criteria, Clinical guidelines, EMR, GEL, GELLO, GLIF, KDOM, Knowledge sharing, Ontology",
author = "Mor Peleg",
year = "2010",
doi = "10.1007/978-3-642-11808-1_6",
language = "English",
isbn = "3642118070",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "64--75",
booktitle = "Knowledge Representation for Health-Care",
note = "Workshop on Knowledge Representation for Health-Care: Data, Processes and Guidelines, KR4HC 2009. Held in Conjunction with the 12th Conference on Artificial Intelligence in Medicine, AIME 2009 ; Conference date: 19-07-2009 Through 19-07-2009",
}