As more health applications are developed to be consumer-oriented, health vocabularies that support such application are increasingly in demand. Research indicates both that there is a significant difference between consumer (layperson) health terminology and the terminology used by health care providers (professional jargon), and that half of all Americans have low health literacy levels. As a result, vocabularies and tools developed for health providers are inadequate to meet the needs of consumer health informatics. Consider the following examples from the Unified Medical Language System (UMLS), the most comprehensive source of medical vocabularies. In each case the specific examples point to a more general failing in the broad spectrum of medical vocabularies: (a) common lay person terms such as 'belly button' and 'kneecap' are missing; (b) the term 'leg' is defined as the body part between the knee and the foot in UMLS, although it refers to the entire lower limb in lay language; (c) the terms 'Pes' and 'Kidney Calculi' are much less intelligible to lay persons than their synonyms 'foot' and 'Kidney stone', yet few vocabularies distinguish such arcane terms from their familiar synonyms; (d) terms such as 'flat head' or 'pes' are less effective query terms for consumer health content than their synonyms 'plagiocephaly' and 'foot,' because one is too 'lay' and the other too 'jargon,' - yet the UMLS offers the user no assistance in making such a judgment. We propose tackling these problems through further developing consumer health vocabulary (CHV) support. Based on our prior work, we identified one particular area within CHV research that has demonstrated great potential benefit and that differs from existing medical vocabulary research projects: the study of the effect that different forms (or 'terms' or 'names') of a concept have on the efficacy of consumer health applications. We propose to build on our previously funded CHV efforts, which centered on the automated mapping and linking of consumer terms to medical concepts for health information retrieval. The initial work of the proposed project will concentrate on improving consumer-term to health-concept mapping, and later work will give attention to the problem of selecting the best form of a concept for consumer health information comprehension and retrieval.
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