Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Chen, Ping-Shuna | Lai, Chin-Huib; * | Chen, Ying-Tzua | Lung, Ting-Yua
Affiliations: [a] Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taoyuan, Taiwan | [b] Department of Information Management, Chung Yuan Christian University, Taoyuan, Taiwan
Correspondence: [*] Corresponding author: Chin-Hui Lai, Department of Information Management, Chung Yuan Christian University, No. 200 Zhongbei Rd., Zhongli Dist., Taoyuan 320, Taiwan. E-mail: [email protected].
Abstract: BACKGROUND: Scheduling patient appointments in hospitals is complicated due to various types of patient examinations, different departments and physicians accessed, and different body parts affected. OBJECTIVE: This study focuses on the radiology scheduling problem, which involves multiple radiological technologists in multiple examination rooms, and then proposes a prototype system of computer-aided appointment scheduling based on information such as the examining radiological technologists, examination departments, the patient’s body parts being examined, the patient’s gender, and the patient’s age. METHODS: The system incorporated a stepwise multiple regression analysis (SMRA) model to predict the number of examination images and then used the K-Means clustering with a decision tree classification model to classify the patient’s examination time within an appropriate time interval. RESULTS: The constructed prototype creates a feasible patient appointment schedule by classifying patient examination times into different categories for different patients according to the four types of body parts, eight hospital departments, and 10 radiological technologists. CONCLUSION: The proposed patient appointment scheduling system can schedule appointment times for different types of patients according to the type of visit, thereby addressing the challenges associated with diversity and uncertainty in radiological examination services. It can also improve the quality of medical treatment.
Keywords: Data mining, decision tree, patient appointments, appointment scheduling system, stepwise multiple regression analysis
DOI: 10.3233/THC-230374
Journal: Technology and Health Care, vol. 32, no. 2, pp. 997-1013, 2024
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]