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Abstract

Research in Medical & Engineering Sciences

Healthcare Critical Knowledge Monitor System Model: Healthcare Knowledge Capture Component Specification

Submission: October 14, 2019;Published: November 08, 2019

DOI: 10.31031/RMES.2019.08.000685

ISSN: 2576-8816
Volume8 Issue2

Abstract

The constant evolution of Information and Communication Technologies brings new opportunities with multiple forms of communication, therefore new ways of sharing knowledge. In healthcare practice, being updated it’s extremely important in order to provide a better service. The growth of multiple sources of knowledge, mostly supported by technology, gives more opportunity to achieve it. Another way to be updated is sharing knowledge with partners and communities, which is becoming part of the healthcare organizations culture (i.e. Electronic Health Record systems). Healthcare organizations manage with personal information concerning to patients such as clinical treatment, clinical history, drug administration, diseases casuistic, among others; and from many sources, such as patient’s feedback, knowledge from suppliers, knowledge from Internet sources, knowledge from decision support systems and inference knowledge (e.g. knowledge from data mining techniques) that are supported by computerbased systems and therefore, demands cautious when are ethical and legal aspects involved. The Critical Knowledge Monitor System Model, proposed, allows knowledge sharing in a controlled ambient and could be a part of the answer to this paradigm that healthcare organizations face. To implement the Critical Knowledge Monitor System model we’ll need, to capture knowledge in multiple forms in healthcare organizations, to accomplish it knowledge engineering techniques such as text mining techniques, Information retrieval, ontology construction, among others, should be applied. Since not all knowledge manage by healthcare organizations could be considered critical (or much critical), it’s necessary to use specific clinical constructs, such as sensitivity and, we believe, combining it with information security principles CIA and Privacy we could assess documents and classify them as critical to the healthcare organization.

Keywords: Healthcare critical knowledge; Knowledge capture; Topic models; Ontology; Knowledge engineering and knowledge security

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