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Healthc Inform Res > Volume 15(1); 2009 > Article
Journal of Korean Society of Medical Informatics 2009;15(1):141-151.
DOI: https://doi.org/10.4258/jksmi.2009.15.1.141    Published online March 31, 2009.
Toward the Automatic Generation of the Entry Level CDA Documents
Sungwon Jung1, Seunghee Kim2, Sooyoung Yoo2, Jinwook Choi2
1Interdisciplinary Program, College of Engineering, Seoul National University, Korea.
2Department of Biomedical Engineering, College of Medicine, Seoul National University, Korea.
Correspondence:  Jinwook Choi,
Received: 3 July 2008
Abstract

Objective: CDA (Clinical Document Architecture) is a markup standard for clinical document exchange. In order to increase the semantic interoperability of documents exchange, the clinical statements in the narrative blocks should be encoded with code values. Natural language processing (NLP) is required in order to transform the narrative blocks into the coded elements in the level 3 CDA documents. In this paper, we evaluate the accuracy of text mapping methods which are based on NLP.

Methods: We analyzed about one thousand discharge summaries to know their characteristics and focused the syntactic patterns of the diagnostic sections in the discharge summaries. According to the patterns, different rules were applied for matching code values of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT).

Results: The accuracy of matching was evaluated using five-hundred discharge summaries. The precision was as follows: 86.5% for diagnosis, 61.8% for chief complaint, 62.7%, for problem list, and 64.8% for discharge medication.

Conclusion: The text processing method based on the pattern analysis of a clinical statement can be effectively used for generating CDA entries.

Key Words: Clinical Document Architecture, Natural Language Processing, SNOMED CT
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