We have developed a systematic methodology using corpus-based text analysis followed by human review to assign "consumer-friendly display (CFD) names" to medical concepts from the National Library of Medicine (NLM) Unified Medical Language System (UMLS) Metathesaurus. Using NLM MedlinePlus queries as a corpus of consumer expressions and a collaborative Web-based tool to facilitate review, we analyzed 425 frequently occurring concepts. As a preliminary test of our method, we evaluated 34 ana-lyzed concepts and their CFD names, using a questionnaire modeled on standard reading assessments. The initial results that consumers (n=10) are more likely to understand and recognize CFD names than alternate labels suggest that the approach is useful in the development of consumer health vocabularies for displaying understandable health information.
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