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Knowledge Representation in Patient Safety Reporting: An Ontological Approach Cover

Knowledge Representation in Patient Safety Reporting: An Ontological Approach

By: Chen Liang and  Yang Gong  
Open Access
|Sep 2017

Abstract

Purpose

The current development of patient safety reporting systems is criticized for loss of information and low data quality due to the lack of a uniformed domain knowledge base and text processing functionality. To improve patient safety reporting, the present paper suggests an ontological representation of patient safety knowledge.

Design/methodology/approach

We propose a framework for constructing an ontological knowledge base of patient safety. The present paper describes our design, implementation, and evaluation of the ontology at its initial stage.

Findings

We describe the design and initial outcomes of the ontology implementation. The evaluation results demonstrate the clinical validity of the ontology by a self-developed survey measurement.

Research limitations

The proposed ontology was developed and evaluated using a small number of information sources. Presently, US data are used, but they are not essential for the ultimate structure of the ontology.

Practical implications

The goal of improving patient safety can be aided through investigating patient safety reports and providing actionable knowledge to clinical practitioners. As such, constructing a domain specific ontology for patient safety reports serves as a cornerstone in information collection and text mining methods.

Originality/value

The use of ontologies provides abstracted representation of semantic information and enables a wealth of applications in a reporting system. Therefore, constructing such a knowledge base is recognized as a high priority in health care.

DOI: https://doi.org/10.20309/jdis.201615 | Journal eISSN: 2543-683X | Journal ISSN: 2096-157X
Language: English
Page range: 75 - 91
Submitted on: Nov 10, 2015
Accepted on: May 6, 2016
Published on: Sep 1, 2017
Published by: Chinese Academy of Sciences, National Science Library
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2017 Chen Liang, Yang Gong, published by Chinese Academy of Sciences, National Science Library
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.