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First published May 19, 2005 as JAMIA PrePrint; doi:10.1197/jamia.M1771
Journal of the American Medical Informatics Association 2005;12(5):517-529
© 2005 American Medical Informatics Association

A more recent version of this article appeared on September 1, 2005
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Submitted on December 13, 2004
Accepted on May 8, 2005

MediClass: A system for detecting and classifying encounter-based clinical events in any EMR

Brian Hazlehurst PhD1*, H. Robert Frost MS2, Dean F. Sittig PhD3, and Victor J. Stevens PhD1

Affiliation of the authors: 1 Kaiser Permanente Center for Health Research, Portland, OR; 2 HRF Engineering, New London, NH; 3 Department of Medical Informatics, Kaiser Permanente, Northwest, Portland, OR

* To whom correspondence should be addressed.

Mediclass is a knowledge-based system that processes both free-text and coded data to automatically detect clinical events in electronic medical records (EMR). This technology aims to optimize both clinical practice and process control by automatically coding EMR contents regardless of data input method (e.g., dictation, structured templates, or typed narrative). We report on the design goals, implemented functionality, generalizability, and current status of the system. Mediclass could aid both clinical operations and health services research through enhancing care quality assessment, disease surveillance, and adverse event detection.




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