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Evaluation of the Mining Techniques in Constructing a Traditional Chinese-Language Nursing Recording System

LIAO, PEI-HUNG PhD; CHU, WILLIAM PhD; CHU, WOEI-CHYN PhD

CIN: Computers, Informatics, Nursing: May 2014 - Volume 32 - Issue 5 - p 223–231
doi: 10.1097/CIN.0000000000000051
Feature Article

In 2009, the Department of Health, part of Taiwan’s Executive Yuan, announced the advent of electronic medical records to reduce medical expenses and facilitatethe international exchange of medical recordinformation. An information technology platform for nursing records in medical institutions was then quickly established, which improved nursing information systems and electronic databases. The purpose of the present study was to explore the usability of the data mining techniques to enhance completeness and ensure consistency of nursing records in the database system.

First, the study used a Chinese word-segmenting system on common and special terms often used by the nursing staff. We also used text-mining techniques to collect keywords and create a keyword lexicon. We then used an association rule and artificial neural network to measure the correlation and forecasting capability for keywords. Finally, nursing staff members were provided with an on-screen pop-up menu to use when establishing nursing records. Our study found that by using miningtechniques we were able to create a powerful keyword lexicon and establish a forecasting model for nursing diagnoses, ensuring the consistency of nursing terminology and improving the nursing staff’s work efficiency and productivity.

Author Affiliations: Department of Nursing, Mackay Medicine Nursing and Management College (Dr Liao); and Institute of Biomedical Engineering (Dr W. Chu); and Department of Biomedical Engineering (Dr W.-C. Chu), National Yang Ming University, Taipei, Taiwan, Republic of China.

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

The authors have disclosed that they have no significant relationship with, or financial interest in, any commercial companies pertaining to this article.

Corresponding author: Woei-Chyn Chu, PhD, 155 Linong St, Sec. 2, Beitou, Taipei 11221, Taiwan, Republic of China (wchu@ym.edu.tw).

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