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First published June 28, 2007 as JAMIA PrePrint; doi:10.1197/jamia.M2399
Journal of the American Medical Informatics Association 2007;14(5):589-598
© 2007 American Medical Informatics Association


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Submitted on February 4, 2007
Accepted on May 22, 2007

The SAGE Guideline Model: Achievements and Overview

Samson W. Tu MS1*, James R. Campbell MD2, Julie Glasgow MD3, Mark A. Nyman MD4, Robert McClure MD5, James McClay MD2, Craig Parker MD, MS6, Karen M. Hrabak MSN, RNC2, David Berg, Tony Weida PhD5, James G. Mansfield PhD7, Mark A. Musen MD, PhD1, and Robert M. Abarbanel MD, PhD8

Affiliation of the authors: 1 Department of Medicine, Stanford University School of Medicine, Palo Alto, CA ; 2 University of Nebraska Medical Center, Omaha, NE; 3 GE Healthcare Integrated IT Solutions, Seattle, WA; 4 Mayo Clinic, Rochester, MN; 5 Apelon, Inc., Ridgefield, CT; 6 RemedyMD, Inc., Sandy, UT; 7 Kea Analytics, Bothell, WA; 8 Hospira, Inc., Lake Forest, IL

* To whom correspondence should be addressed.

The SAGE (Standards-Based Active Guideline Environment) project was formed to create a methodology and infrastructure required to demonstrate integration of decision-support technology for guideline-based care in commercial clinical information systems. This paper describes the development and innovative features of the SAGE Guideline Model and reports our experience encoding four guidelines. Innovations include methods for integrating guideline-based decision support with clinical workflow and employment of enterprise order sets. Using SAGE, a clinician informatician can encode computable guideline content as recommendation sets using only standard terminologies and standards-based patient information models. The SAGE Model supports encoding large portions of guideline knowledge as re-usable declarative evidence statements and supports querying external knowledge sources.







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