政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/103455

English | 正體中文 | 简体中文 | Post-Print筆數 : 27 | Items with full text/Total items : 113318/144297 (79%)
Visitors : 51079430 Online Users : 920

RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.

Scope

please add "double quotation mark" for query phrases to get precise results

please goto advance search for comprehansive author search

Adv. Search

Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer

Goto mobile version

政大機構典藏 > 商學院 > 資訊管理學系 > 期刊論文 > Item 140.119/103455

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/103455

Title:	A Smart Medication Recommendation Model for The Electronic Prescription
Authors:	黃鼎鈞
Contributors:	資管博三
Keywords:	NHI database;Medications;Inappropriate prescription;Diagnosis-Medication association;Smart medication recommendation model
Date:	2014-11
Issue Date:	2016-11-07 15:18:10 (UTC+8)
Abstract:	Background The report from the Institute of Medicine, To Err Is Human: Building a Safer Health System in 1999 drew a special attention towards preventable medical errors and patient safety. The American Reinvestment and Recovery Act of 2009 and federal criteria of ‘Meaningful use’ stage 1 mandated e-prescribing to be used by eligible providers in order to access Medicaid and Medicare incentive payments. Inappropriate prescribing has been identified as a preventable cause of at least 20% of drug-related adverse events. A few studies reported system-related errors and have offered targeted recommendations on improving and enhancing e-prescribing system. Objective This study aims to enhance efficiency of the e-prescribing system by shortening the medication list, reducing the risk of inappropriate selection of medication, as well as in reducing the prescribing time of physicians. Method 103.48 million prescriptions from Taiwan`s national health insurance claim data were used to compute Diagnosis-Medication association. Furthermore, 100,000 prescriptions were randomly selected to develop a smart medication recommendation model by using association rules of data mining. Results and conclusion The important contribution of this model is to introduce a new concept called Mean Prescription Rank (MPR) of prescriptions and Coverage Rate (CR) of prescriptions. A proactive medication list (PML) was computed using MPR and CR. With this model the medication drop-down menu is significantly shortened, thereby reducing medication selection errors and prescription times. The physicians will still select relevant medications even in the case of inappropriate (unintentional) selection.
Relation:	Computer Methods and Programs in Biomedicine · November 2014, Vol.117, No.2, pp.218-224
Data Type:	article
DOI 連結:	http://dx.doi.org/10.1016/j.cmpb.2014.06.019
DOI:	10.1016/j.cmpb.2014.06.019
Appears in Collections:	[資訊管理學系] 期刊論文

Files in This Item:

File	Description	Size	Format
1-s2.0-S0169260714002533-main.pdf		1546Kb	Adobe PDF2	715	View/Open

All items in 政大典藏 are protected by copyright, with all rights reserved.

社群 sharing

著作權政策宣告 Copyright Announcement

1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.

DSpace Software Copyright © 2002-2004 MIT & Hewlett-Packard / Enhanced by NTU Library IR team Copyright © - Feedback