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Currently, extraction of data for epidemiological surveillance is severely limited by the lack of standardised structuring of medical records. The objective of this study is to describe a semi-automatic method for standardized coding of textual medical records for epidemiological use. In the context of the ALADIN-DTH research project, we are planning to develop a tool for detecting nosocomial infections. With that goal in mind we will ask physicians to manually code 2,000 hospital medical records using different appropriate medical terminologies (ICD10, SNOMED 3.5, ATC, CCAM, MeSH). A French automatic Multi-Terminology Health Concept Extractor (French acronym: ECMT) can offer a choice of labels and codes of different terminologies. This tool can be called on a distant server via an Internet connection thanks to an XML service. Among 3,450 medical expressions queried by users, the ECMT has proposed relevant codes for 70,5% of them (original formulation) and 87,7% of them after correction of the formulation by the annotator, this result ranging from 51,3% (bacteriological examinations) to 96,4% (symptoms/diagnoses). A multi-terminology health concept extractor is an interesting tool for standardized coding of textual data for epidemiological use. |
