Unified Medical Language System Terms Research Articles

Perils of providing visual health information overviews for consumers with low health literacy or high stress

This pilot study explores the impact of a health topics overview (HTO) on reading comprehension. The HTO is generated automatically based on the presence of Unified Medical Language System terms. In a controlled setting, we presented health texts and posed 15 questions for each. We compared performance with and without the HTO. The answers were available in the text, but not always in the HTO. Our study (n=48) showed that consumers with low health literacy or high stress performed poorly when the HTO was available without linking directly to the answer. They performed better with direct links in the HTO or when the HTO was not available at all. Consumers with high health literacy or low stress performed better regardless of the availability of the HTO. Our data suggests that vulnerable consumers relied solely on the HTO when it was available and were misled when it did not provide the answer.

A tool for sharing annotated research data: the "Category 0" UMLS (Unified Medical Language System) vocabularies.

BackgroundLarge biomedical data sets have become increasingly important resources for medical researchers. Modern biomedical data sets are annotated with standard terms to describe the data and to support data linking between databases. The largest curated listing of biomedical terms is the the National Library of Medicine's Unified Medical Language System (UMLS). The UMLS contains more than 2 million biomedical terms collected from nearly 100 medical vocabularies. Many of the vocabularies contained in the UMLS carry restrictions on their use, making it impossible to share or distribute UMLS-annotated research data. However, a subset of the UMLS vocabularies, designated Category 0 by UMLS, can be used to annotate and share data sets without violating the UMLS License Agreement.MethodsThe UMLS Category 0 vocabularies can be extracted from the parent UMLS metathesaurus using a Perl script supplied with this article. There are 43 Category 0 vocabularies that can be used freely for research purposes without violating the UMLS License Agreement. Among the Category 0 vocabularies are: MESH (Medical Subject Headings), NCBI (National Center for Bioinformatics) Taxonomy and ICD-9-CM (International Classification of Diseases-9-Clinical Modifiers).ResultsThe extraction file containing all Category 0 terms and concepts is 72,581,138 bytes in length and contains 1,029,161 terms. The UMLS Metathesaurus MRCON file (January, 2003) is 151,048,493 bytes in length and contains 2,146,899 terms. Therefore the Category 0 vocabularies, in aggregate, are about half the size of the UMLS metathesaurus.A large publicly available listing of 567,921 different medical phrases were automatically coded using the full UMLS metatathesaurus and the Category 0 vocabularies. There were 545,321 phrases with one or more matches against UMLS terms while 468,785 phrases had one or more matches against the Category 0 terms. This indicates that when the two vocabularies are evaluated by their fitness to find at least one term for a medical phrase, the Category 0 vocabularies performed 86% as well as the complete UMLS metathesaurus.ConclusionThe Category 0 vocabularies of UMLS constitute a large nomenclature that can be used by biomedical researchers to annotate biomedical data. These annotated data sets can be distributed for research purposes without violating the UMLS License Agreement. These vocabularies may be of particular importance for sharing heterogeneous data from diverse biomedical data sets. The software tools to extract the Category 0 vocabularies are freely available Perl scripts entered into the public domain and distributed with this article.