Literature DB >> 21346947

Aligning Structured and Unstructured Medical Problems Using UMLS.

Lorena Carlo1, Herbert S Chase, Chunhua Weng.   

Abstract

This paper reports a pilot study to align medical problems in structured and unstructured EHR data using UMLS. A total of 120 medical problems in discharge summaries were extracted using NLP software (MedLEE) and aligned with 87 ICD-9 diagnoses for 19 non-overlapping hospital visits of 4 patients. The alignment accuracy was evaluated by a medical doctor. The average overlap of medical problems between the two data sources obtained by our automatic alignment method was 23.8%, which was about half of the manual review result, 43.56%. We discuss the implications for related research in integrating structured and unstructured EHR data.

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Year:  2010        PMID： 21346947      PMCID： PMC3041294     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN： 1559-4076


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