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Implementation of Hospital Examination Reservation System Using Data Mining Technique

Authors :
Il Won Shin
Seung Hyun Chung
Yang Hyo Choe
Ki Chung Ryu
Jae Dong Lee
Keun Ho Ryu
Hyo Soung Cha
Tae Sik Yoon
Kyoung Yong Lee
Source :
Healthcare Informatics Research, Vol 21, Iss 2, Pp 95-101 (2015), Healthcare Informatics Research
Publication Year :
2015
Publisher :
The Korean Society of Medical Informatics, 2015.

Abstract

Objectives New methods for obtaining appropriate information for users have been attempted with the development of information technology and the Internet. Among such methods, the demand for systems and services that can improve patient satisfaction has increased in hospital care environments. Methods In this paper, we proposed the Hospital Exam Reservation System (HERS), which uses the data mining method. First, we focused on carrying clinical exam data and finding the optimal schedule for generating rules using the multi-examination pattern-mining algorithm. Then, HERS was applied by a rule master and recommending system with an exam log. Finally, HERS was designed as a user-friendly interface. Results HERS has been applied at the National Cancer Center in Korea since June 2014. As the number of scheduled exams increased, the time required to schedule more than a single condition decreased (from 398.67% to 168.67% and from 448.49% to 188.49%; p < 0.0001). As the number of tests increased, the difference between HERS and non-HERS increased (from 0.18 days to 0.81 days). Conclusions It was possible to expand the efficiency of HERS studies using mining technology in not only exam reservations, but also the medical environment. The proposed system based on doctor prescription removes exams that were not executed in order to improve recommendation accuracy. In addition, we expect HERS to become an effective system in various medical environments.

Details

Language :
English
ISSN :
20933681
Volume :
21
Issue :
2
Database :
OpenAIRE
Journal :
Healthcare Informatics Research
Accession number :
edsair.doi.dedup.....81c6f405482f41bb3012bacc6ac3164b