SNOMED CT module-driven clinical archetype management

Abstract

Exploiting medical domain knowledge from ontologies such as SNOMED CT may overcome some limitations of the keyword-based systems and thus improve the search experience of repository users. An automated approach based on ontology segmentation is an efficient and feasible way for supporting modeling, management and user navigation in clinical archetype repositories.

Clustering clinical models from local electronic health records based on semantic similarity

“…what is the common content of two or more CMs is one of the themes of the studies by Allones et al [46] and Gøeg et al [47]. It would be an interesting follow-up on this study to deduce the common content of user-defined clusters drawn from the dendrograms.…”

“…One application of the semantic search is that overlap between archetype content can be detected. The structure of SNOMED CT is used as a resource to enrich the search [46]. In the third study by Gøeg et al, SNOMED CT is used to determine similarities and differences in physical examination templates using both full matches and terminology matches deduced from the structure of SNOMED CT [47].…”

“…In the evaluation, we chose to include 15 templates, which is comparable to the related studies where the sample size is 4 [47], 7 [45], and 25 [46] respectively. We chose the relatively limited number of templates to make the analysis transparent, which in our opinion is important in this methodological oriented study.…”

Modelo de Objetos do openEHR: uma Revisão Sistemática da Literatura e sua relação com métricas de software

“…Para a questão de pesquisa Q1, os projetos estão distribuídos geograficamente por 38 países. projeto POSEACLE para facilitar a gestão semântica de informação e conhecimento em RES 42-44" ; projeto gestão de terminologias para arquétipos 45,46 .…”

Relevant Tools for Tackling Interoperability Problems on Heterogeneous Electronic Health Record Systems: An Exploratory Research

“…The above mentioned problems have been partially resolved through the use of Information Communication Technologies (ICT). These allow a decrease of medical records based on paper [6] , avoided paper limitations [7] and empower the electronic health known as e-health [8] to make way to digital medical records [9] , called Electronic Health Record (EHR), which allows healthcare professionals to retrieve and store digital medical information [7] . Although, problems for sharing data persist, and the consequences of having disperse electronic medical records impact inaccurate clinical diagnosis, which could generate serious consequences for the patient's health; another consequence is that, it would be necessary to do diagnostic studies again, due to the disperse information.…”