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First published August 21, 2007 as JAMIA PrePrint; doi:10.1197/jamia.M2389
Journal of the American Medical Informatics Association 2007;14(6):781-787
© 2007 American Medical Informatics Association


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Submitted on January 30, 2007
Accepted on July 26, 2007

A Pattern-based Analysis of Clinical Computer-Interpretable Guideline Modeling Languages

Nataliya Mulyar MSc1*, Wil M.P. van der Aalst PhD1, and Mor Peleg PhD2

Affiliation of the authors: 1 Eindhoven University of Technology, Eindhoven, The Netherlands; 2 Department of Management Information Systems, University of Haifa, Israel

* To whom correspondence should be addressed.

Objective Languages used to specify computer interpretable guidelines (CIGs) differ in their approaches to addressing particular modeling challenges. The main goals of this paper are: 1) to examine the expressive power of CIG modeling languages; and 2) to define the differences, from the control-flow perspective, between process languages in workflow management systems and modeling languages used to design clinical guidelines.

Design The pattern-based analysis was applied to guideline modeling languages Asbru, EON, GLIF, and PROforma. We focused on control-flow and left other perspectives out of consideration.

Measurements We evaluated the selected CIG modeling languages and identified their degree of support of 43 control-flow patterns. We used a set of explicitly defined evaluation criteria to determine whether each pattern is supported directly, indirectly or not at all.

Results PROforma offers direct support for 22 of 43 patterns, Asbru 20, GLIF 17, and EON 11. All four directly support. Basic Control-flow patterns, Cancellation patterns, and some Advance Branching and Synchronization patterns. None support Multiple Instances patterns. They offer varying levels of support for Synchronizing Merge patterns and State-based patterns. Some support a few scenarios not covered by the 43 control-flow patterns.

Conclusion CIG modeling languages are remarkably close to traditional workflow languages from the control-flow perspective, but cover many fewer workflow patterns. CIG languages offer some flexibility that supports modeling of complex decisions and provide ways for modeling some decisions not covered by workflow management systems. Workflow management systems may be suitable for clinical guideline applications.







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