Publication Type
Editorial
Version
publishedVersion
Publication Date
12-2010
Abstract
Patient safety is an emerging, major health care discipline with significance accentuated in the influential Institute of Medicine (IOM) reports in the United States “To Err is Human” and “Crossing the Quality Chasm”. These reports highlighted the danger and prevalence of medical errors and preventable adverse events, explained the three main sources of system-related, human factors-related and cognitive-related errors, and recommended the use of information and decision support technologies to help alleviate the problem. A number of studies and reports from all over the world with similar findings have since followed, culminating in the 55th World Health Assembly Resolution on Patient Safety and the 58th World Health Assembly Resolution on eHealth. These efforts initiated a global mandate to improve patient safety in health care; one of the critical strategies identified is to adopt and apply effective and efficient information technology (IT) solutions and clinical decision support technologies.
Keywords
Concept formation, Decision support system, Editorial, Health care quality, Human, Medical error, Safety
Discipline
Medicine and Health Sciences | Numerical Analysis and Scientific Computing
Research Areas
Intelligent Systems and Optimization
Publication
Methods of Information in Medicine
Volume
49
Issue
6
First Page
547
Last Page
549
ISSN
0026-1270
Identifier
10.1055/s-0038-1625365
Publisher
Schattauer
Citation
Tze-Yun LEONG.
Toward effective concept representation in decision support to improve patient safety. (2010). Methods of Information in Medicine. 49, (6), 547-549.
Available at: https://ink.library.smu.edu.sg/sis_research/3047
Copyright Owner and License
Publisher
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1055/s-0038-1625365
Included in
Medicine and Health Sciences Commons, Numerical Analysis and Scientific Computing Commons