From episodes of care to diagnosis codes: automatic text categorization for medico-economic encoding.

TitleFrom episodes of care to diagnosis codes: automatic text categorization for medico-economic encoding.
Publication TypeJournal Article
Year of Publication2008
AuthorsRuch, P, Gobeilla, J, Tbahritia, I, Geissb├╝hlera, A
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
Pagination636-40
Date Published2008
ISSN1942-597X
KeywordsAlgorithms, Artificial Intelligence, Decision Support Systems, Clinical, Diagnosis, Computer-Assisted, Information Storage and Retrieval, International Classification of Diseases, Medical History Taking, Medical Records Systems, Computerized, Natural Language Processing, Pattern Recognition, Automated, Subject Headings, Switzerland
Abstract

We report on the design and evaluation of an original system to help assignment ICD (International Classification of Disease) codes to clinical narratives. The task is defined as a multi-class multi-document classification task. We combine a set of machine learning and data-poor methods to generate a single automatic text categorizer, which returns a ranked list of ICD codes. The combined ranking system currently obtains a precision of 75% at high ranks and a recall of about 63% for the top twenty returned codes for a theoretical upper bound of about 79% (inter-coder agreement). The performance of the data-poor classifier is weak, whereas the use of tempo-rally-typed contents such as anamnesis and prescription free text sections results in a statistically significant improvement.

Alternate JournalAMIA Annu Symp Proc
PubMed ID18999206