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|Title:||An integrated electronic medical record system (iEMRS) with decision support capability in medical prescription|
Decision support systems
Electronic medical records
|Publisher:||Emerald Group Publishing Limited|
|Source:||Journal of systems and information technology, 2012, v. 14, no. 3, p. 236-245 How to cite?|
|Journal:||Journal of systems and information technology|
|Abstract:||Purpose – The purpose of this paper is to show how a clinical decision support system can help in prescription and knowledge acquisition processes.|
Design/methodology/approach – An integrated electronic medical records system (iEMRS) is designed to enhance the decision support quality in prescription.
Findings – By evaluating the system performance through 135 prescription records collected from a Hong Kong medical organization, iEMRS shows a satisfactory result in suggesting medicines that is properly the same as the decisions made by the physicians.
Originality/value – Compared with the static clinical guidelines built (manually) in the traditional clinical decision support system, knowledge in iEMRS is generated by the knowledge discovery result from professional experiences of various physicians and patient histories, which are more dynamic in nature. A treatment algorithm, designed in data mining technique, is introduced to improve information management in medical organizations by integration of decision support capability and EMRS, and supplement the deficiencies of traditional clinical decision support system.
|Rights:||© Emerald Group Publishing Limited|
This paper is a postprint of a paper submitted to and accepted for publication in Journal of systems and information technology. Journal of systems and information technology is available online at http://www.emeraldinsight.com/, the open URL of the article: http://dx.doi.org/10.1108/13287261211255347
|Appears in Collections:||Journal/Magazine Article|
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|Manuscript_iEMRS_revised.pdf||Pre-published version||368.53 kB||Adobe PDF||View/Open|
Citations as of Jan 28, 2016
Checked on Jan 31, 2016
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