Understanding requirements of clinical data standards for developing interoperable knowledge-based DSS: A case study

González-Ferrer, Arturo; Peleg, Mor

doi:10.1016/j.csi.2015.06.002

Cited by 21 publications

(9 citation statements)

References 35 publications

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“…An alternative approach consists in adding a data integration layer to the architecture and to represent all the needed information using a common information model that serves as a single data provider for the DSS. Several approaches to the design and implementation of such common data models have been proposed in the medical informatics literature, some of which have been specifically developed to support clinical DSS [10,11,12,13]. Among these, some approaches only provide the specifications for a logical data model that defines entities and their relationships at a high level of abstraction (e.g.…”

Section: Methodsmentioning

confidence: 99%

Decision Support through Data Integration: Strategies to Meet the Big Data Challenge

Parimbelli¹,

Sacchi²,

Bellazzi³

2016

ejbi

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Objectives: Presentation of an overview of the reasons why data integration initiatives should be seen as enablers for effective decision support in data-intensive healthcare settings. Methods: Typical challenges rising from the information requirements of clinical decision support systems are highlighted. We then propose a methodological solution where several heterogeneous data sources are integrated by the means of a common data model on top of which the DSS is built. Results: We report on two successful case studies based on the DSSs developed in the context of the MobiGuide and Mosaic projects, funded by the European Union in the Seventh Framework Program. The MobiGuide patient guidance system has been successfully validated during a recent pilot study involving 30 patients (10 with atrial fibrillation and 20 with gestational diabetes), while Mosaic is currently undergoing a validation phase involving 1000 type 2 Diabetes patients. Conclusions: In the era of big data, effective data integration strategies are an essential need for medical informatics solutions and even more for those intended to support decision processes. Building generic DSSs based on a stable (but easily extensible) data model, specifically designed to meet the information requirements of DSSs and analytics, has proven to be a successful solution in the two presented use cases.

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Section: Methodsmentioning

confidence: 99%

Decision Support through Data Integration: Strategies to Meet the Big Data Challenge

Parimbelli¹,

Sacchi²,

Bellazzi³

2016

ejbi

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“…System actions characterize the inference engine and can be organized as an algorithm. We wanted a typology of system actions that even by reducing the complexity of representation in tools like GLIF, HL7 and ISO 13606 [60] always remains compatible with these standards for interoperability issues [61].…”

Section: System Actionsmentioning

confidence: 99%

Data mining for decision support with uncertainty on the airplane

Sene

Kamsu-Foguem

Rumeau

2018

Data & Knowledge Engineering

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“…A padronização garante uma melhor estruturação assim como a interoperabilidade com aplicações terceiras e até mesmo com instituições médicas. O modelo SAC irá utilizar as definições propostas pelo openEHR [GONZÁLEZ-FERRER, 2015].…”

Section: Introductionunclassified

Um modelo de monitoramento de pacientes utilizando a ciência de situação

Closs¹,

Costa²,

Righi³

2016

Anais Do VIII Simpósio Brasileiro De Computação Ubíqua E Pervasiva (SBCUP 2016)

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Os constantes avanços na computação móvel e ubíqua possibilitam novos desenvolvimentos e recursos em diversas áreas, sendo a saúde uma destas. A partir disto, surge então o conceito de cuidados ubíquos, onde são aplicadas novas formas cuidados médicos, como o monitoramento de pacientes. Tendo em vista este recurso, o modelo SAC - Situation-Aware Care propõe o uso do monitoramento de pacientes em conjunto da ciência de situação para perceber, compreender e projetar desvios e degradações na saúde, disponibilizando aos médicos melhores informações para atendimento. Para avaliar a viabilidade do modelo SAC foi aplicado um estudo de caso, baseado em cenário, sendo este apoiado pelo desenvolvimento de um protótipo do modelo.

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Understanding requirements of clinical data standards for developing interoperable knowledge-based DSS: A case study

Cited by 21 publications

References 35 publications

Decision Support through Data Integration: Strategies to Meet the Big Data Challenge

Decision Support through Data Integration: Strategies to Meet the Big Data Challenge

Data mining for decision support with uncertainty on the airplane

Um modelo de monitoramento de pacientes utilizando a ciência de situação

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