SNOMED-CT as standard language for organization and representation of the information in patient records

• Autor(a) principal: Pinto, Virgínia Bentes
• Data de Publicação: 2014
• Outros Autores: Rabelo, Camila Regina de Oliveira, Girão, Igor Peixoto Torres
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da Universidade Federal do Ceará (UFC)
• Texto Completo: http://www.repositorio.ufc.br/handle/riufc/19136
• topic: SNOMED-CT; Patient records; Terminology; Information

The Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT), such as the Medical Subject Headings (MeSH) and the Health Sciences Descriptors (MeSH) is a standard for handling, organizing, representing and retrieval of information in the health context. It is structured, among other things, in 19 categories: clinical diagnosis/disease, procedures, observable entities, body structure, body, substance, biological and pharmaceutical products, sample, physical object, physical force, event, geographical or environmental location, social context, stages and scales, special concepts and qualifiers. We present research results carried out with patients’ medical records in the Walter Cantidio University Hospital, at Federal University of Ceará. The line guiding this study seeks to answer the following question: what is the contribution of these categories to build a representation of the patient’s medical records at the Department of Medical Records and Statistics (SAME), at the Walter Cantidio University Hospital (HUWC)? The objective of the research is to study the contribution of SNOMED-CT for the representation of information within those records. It is therefore an exploratory study supported by neofunctionalist method and content analysis, the physical structure of digitized records was analyzed at the SAME of the HUWC. Then we analyzed a corpus of two patient records with nine volumes, about 4000 pages corresponding to 777 Mb. The results and conclusions show that the hierarchical categories of SNOMED-CT may bring contributions to the representation of the charts, as it is a robust terminology based on ontology, contemplating the essence of the information recorded in these documents. Regarding the physical structure of the chart shows some similarities, and hence can contribute to information retrieval with higher added value, since it allows the use of pre and post-coordination as well as natural language, synonyms and acronyms.