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Archetype based patient data modeling to support treatment of pituitary adenomas.
Chalopin, Claire; Lindner, Dirk; Kropf, Stefan; Denecke, Kerstin.
Afiliação
  • Chalopin C; Innovation Center Computer Assisted Surgery, Universität Leipzig, Germany.
  • Lindner D; University Hospital, Department of Neurosurgery, Universität Leipzig, Germany.
  • Kropf S; Innovation Center Computer Assisted Surgery, Universität Leipzig, Germany.
  • Denecke K; Innovation Center Computer Assisted Surgery, Universität Leipzig, Germany.
Stud Health Technol Inform ; 216: 178-82, 2015.
Article em En | MEDLINE | ID: mdl-26262034
The treatment of patients with pituitary adenoma requires the assessment of various patient data by the clinician. Because of their heterogeneity, they are stored in different sub-information systems, limiting a fast and easy access. The objective of this paper is to apply and test the tools provided by the openEHR Foundation to model the patient data relevant for diagnosis and treatment of the disease with the future intention to implement a centralised standard-based information platform. This platform should support the clinician in the treatment of the disease and improve the information exchange with other healthcare institutions. Some results of the domain modeling, so far obtained, are presented, and the advantages of openEHR emphasized. The free tools and the large database of existing structured and standard archetypes facilitated the modeling task. The separation of the domain modeling from the application development will support the next step of development of the information platform.
Assuntos
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Base de dados: MEDLINE Assunto principal: Neoplasias Hipofisárias / Adenoma / Registro Médico Coordenado / Modelos Organizacionais / Sistemas de Apoio a Decisões Clínicas / Registros Eletrônicos de Saúde / Fluxo de Trabalho Idioma: En Ano de publicação: 2015 Tipo de documento: Article
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Base de dados: MEDLINE Assunto principal: Neoplasias Hipofisárias / Adenoma / Registro Médico Coordenado / Modelos Organizacionais / Sistemas de Apoio a Decisões Clínicas / Registros Eletrônicos de Saúde / Fluxo de Trabalho Idioma: En Ano de publicação: 2015 Tipo de documento: Article