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  2. College of Health Care and Management/健康管理學院
  3. School of Health Policy and Management/醫療產業科技管理學系
  4. A Robust ORMS Framework for Taiwanese Healthcare: Taguchi’s Dynamic Method in Action
 
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A Robust ORMS Framework for Taiwanese Healthcare: Taguchi’s Dynamic Method in Action

Journal
Healthcare
Journal Volume
13
Journal Issue
9
Start Page
1024
ISSN
2227-9032
Date Issued
2025-04-29
Author(s)
Hung-Chang Liao  
Ya-Huei Wang  
DOI
10.3390/healthcare13091024
URI
https://scholars.csmu.edu.tw/handle/123456789/5233
Abstract
<jats:p>The study focused on the design of an ORMS in a medical center in central Taiwan, which also functions as a teaching hospital. Background/Objectives: The research objectives were to design an ORMS simulation system based on the status quo of the operating room planning and scheduling in the medical center, obtain the optimal parameter setting in the ORMS, and find improvement strategies according to the sensitivity analysis based on the optimal parameter setting for total performance. Methods: Taguchi’s dynamic method was adopted to design the ORMS under human and material resource constraints. The scope of the study was internal medicine patients of the ORMS. A neural network was used to construct a relationship between parameters and performances. A genetic algorithm was used to obtain the optimal parameter setting for optimal performance. Results: This study successfully established a robust operating room management system (ORMS) to help hospital manager to plan and schedule operating rooms and take the ORMS into account to meet patient needs. Decision-makers can use the insights from the sensitivity analysis to refine their strategies effectively. The sensitivity analysis showed that the impact power (the percentage change in d) of the “number of circulating nurses (−0.15 to −1.25; −0.25 to −1.85)” factor was less than (<) that of the “number of holding nurses (−0.85 to −2.04; −0.91 to −2.07)” factor < that of the “number of preoperative beds (−2.57 to −4.53; −2.23 to −4.10)” factor < that of the “number of anesthetists (−3.13 to −7.50)” factor. Conclusions: In the optimal parameter setting obtained, the number of holding nurses was 18, the number of circulating nurses was 20, the number of anesthetists was 15, and the number of preoperative beds was 12. The optimal performance was 0.91.</jats:p>
SDGs

[SDGs]SDG3

Publisher
MDPI AG
Type
journal-article
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