Representation by standard terminologies of health status concepts contained in two health status assessment instruments used in rheumatic disease management.
Health and functional status data have been shown to have clinical utility in predicting outcome. Various metadata registries in the form of patient self-administered health assessment questionnaires have been incorporated into routine clinical care and clinical research of patients with rheumatic disease. Examples of such health assessment instruments are the Clinical Health Assessment Questionnaire (CLINHAQ) and the Modified Health Assessment Questionnaire (MHAQ). These instruments contain concepts that are an integral part of the health and functional status domain. Using an automated indexing tool we examined the clinical content coverage by SNOMED RT and the Unified Medical Language System (UMLS) Metathesaurus for health and functional status concepts identified in the MHAQ and CLINHAQ. Significant differences existed between the overall representational ability of SNOMED and UMLS for concepts identified in the MHAQ (49%, vs. 77% respectively, p < .005) and for concepts identified in the CLINHAQ (30% vs. 64% respectively p < .005). Representational capability by SNOMED-RT and UMLS for concepts in a given health assessment instrument was carried across four semantic classes of "attitudes", "symptoms", "activities", and "social attributes". The conceptual content coverage of health status assessment concepts contained in the MHAQ and CLINHAQ by SNOMED-RT and UMLS was incomplete but better for UMLS with its panoply of vocabulary sources. This observed overall improved representation by UMLS appeared to be due to better representation of concepts in "activities" and "social attributes" semantic classes. Representation of health or functional status concepts in a computerized medical record should be founded on a universally agreed concept model of that domain. Established functional and health status metadata registries can serve as important sources for concepts and candidate classes within that domain.
Ruggieri
A P
AP
Division of Health Computer Sciences, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA.
Elkin
P
P
Chute
C G
CG
D006304:Health Status; D006801:Humans; D012216:Rheumatic Diseases / Q000628:therapy; D011795:Surveys and Questionnaires; D017432:Unified Medical Language System; D018875:Vocabulary, Controlled