醫事放射師是在醫療院所中從事輻射相關診療作業的醫事人員，工作時需長時間反覆進行操作儀器、搬移病人或是單手取放X光片匣等作業，常伴隨彎腰、高舉手臂、久站和蹲跪等重複性動作，造成肌肉骨骼不適，但外界對放射師的危害多聚焦於輻射暴露風險，易忽視肌肉骨骼不適之風險分析與改善。因此，本研究以新竹市某區域醫院放射線科為例，旨在建構排班最佳化的模型，在遵從法規限制、醫院內部輪班規定、特殊班別人員技術需求等條件下，降低醫事放射師之整體肌肉骨骼不適風險。
本研究分為五個階段：（1）問卷調查：透過職場疲勞調查問卷調查放射師連續工作多天之累積疲勞程度，藉以將主觀累積疲勞納入風險衡量，進行班表規劃，同時也詢問放射師造成疲勞感受的主觀原因；此外，亦透過北歐肌肉骨骼不適問卷調查放射師目前之肌肉骨骼不適情形，以了解各部位不適感受出現的盛行率；（2）個案醫院現行班次分析：藉由2018年放射線科業務統計資料區分出旺月、淡月及一般時節，以依據業務量排出不同的班表；（3）現場作業風險評估觀察：分別針對一般X光攝影、磁振造影等現場作業進行觀察，並運用工作相關肌肉骨骼傷害之風險因子檢核表，分析作業流程中肌肉骨骼不適危險因子與風險，將風險量化；（4）建立排班模式：綜合問卷調查得出之主觀累積疲勞程度、現場作業觀察得出之各班別客觀肌肉骨骼不適風險，以最小化醫事放射師整體肌肉骨骼不適風險為目標式，並以法令規範、科內輪班規定等為限制式，建立旺月、淡月、一般時節之排班最佳化模型，並使用Gurobi Optimizer 8.1.1版本搭配Python 3.7環境求解、產生班表；（5）專家意見討論：在完成排班求解後，除了分析節省的時間成本、降低之風險，亦向專家諮詢，探討排班最佳化之整體效益與可行性。
研究結果分為三部分：第一部分為問卷調查結果，在造成疲勞感受的主觀原因部分，前三名依序為：「工作量較大」、「輪班工作」、「睡眠不足」與「反覆操作動作」，透過排班最佳化應可改善輪班工作與反覆操作動作造成的疲勞感受，另外肌肉骨骼不適現況盛行率最高的身體部位前三名依序為：下背或腰（66.67%）、手或手腕（46.67%）及肩膀（46.67%）；第二部分為現場作業觀察結果，結果顯示電腦斷層攝影、血管攝影等相關班次以及一般X光攝影中，當病患為躺床狀態、攝影部位為身體中段時，因為牽涉到移床作業，肌肉骨骼不適風險最高；第三部分為最佳化排班模式結果，基於主觀累積疲勞程度與各班別肌肉骨骼不適風險分數，求出三種時節的最佳化班表。由於2019新型冠狀病毒疫情的影響，未能將班表即時實行、追蹤醫事放射師的回饋，故透過專家意見討論，探討實施的可行性以及降低醫事放射師之肌肉骨骼不適盛行率的可能效果，結果發現：相較於既有班表，最佳化班表中，放射師在單一週期內輪值較多種班次，應可降低單週內重複輪值同樣班次的肌肉骨骼不適情形。
另外，分析每位放射師之肌肉骨骼不適風險平均分數，在各種時節下，採取最佳化班表時皆比既有班表低，進一步觀察最佳化班表之班次分配與放射師個人主觀疲勞程度的關聯，發現平均每日主觀累積疲勞程度最高的四位放射師被分配到一般X光攝影、乳房攝影等風險較低的班次，而每日主觀累積疲勞程度最低的四位放射師則被分配到電腦斷層攝影、磁振造影等風險較高的班次，代表最佳化班表確實有助於使主觀累積疲勞程度較高的放射師盡可能從事肌肉骨骼不適風險較低的工作。此外，主觀累積疲勞程度與肌肉骨骼不適風險總和之間在既有班表中呈現低度正相關，在最佳化班表中則皆呈現中度負相關，表示主觀累積疲勞程度愈高的放射師愈可能會被分配到肌肉骨骼不適風險較低的班別，應有助於降低其工作肌肉骨骼不適情形。
整體而言，本研究將醫事放射師的主觀累積疲勞、各班別的肌肉骨骼不適風險納入考量，建立最小化整體肌肉骨骼不適風險的排班模型，提供個案醫院在未來實行，將有助於縮短排班所需時間以及降低醫事放射師工作之肌肉骨骼不適風險。

Medical radiation technologists are medical staff engaged in radiation-related operations in hospitals. They need to repeatedly operate instruments, move patients, or hold X-ray cassettes with one hand. Repetitive actions such as bending the torso, raising the arms, twisting the neck, standing for a long time, and squatting are involved and would cause musculoskeletal discomforts. However, the public focuses mainly on the risk of radiation exposure among medical radiation technologists. Risk analysis and improvement of musculoskeletal discomforts are somehow neglected. Therefore, this study takes the radiology department of a regional hospital in Hsinchu City as an example and aims to construct a mathematical model for schedule optimization to reduce the overall risk of musculoskeletal discomforts among medical radiation technologists.
There are five stages in this study: (1) Questionnaire survey: Workplace fatigue questionnaire was used to investigate medical radiation technologists’ cumulative fatigue level in multiple working days. By doing so, subjective cumulative fatigue can be included in risk assessment for schedule optimization. Meanwhile, medical radiation technologists were also asked about the possible causes of fatigue. In addition, the current musculoskeletal discomfort situation among medical radiation technologists was investigated through the Nordic Musculoskeletal Discomfort Questionnaire to understand the prevalence of discomfort in various body parts. (2) The analysis of current shift of the hospital: The represensative months of peak, slack, and general seasons are differentiated according to the nember of patients in the radiology department collected monthly in 2018. (3) On-site observation and risk assessment: Operations of general X-ray photography and magnetic resonance imaging were first observed. After that, the Risk Factor Checklist for Work-related Musculoskeletal Disorders was used to identify and quantify the risk factors. (4) Constructing the scheduling model: By combining the subjective cumulative fatigue level from the questionnaire survey and the risk of musculoskeletal discomfort from on-site observation, the scheduling model was constructed to minimize the overall risk of musculoskeletal discomforts among medical radiation technologists. The constraints include regulatory restrictions and internal shift regulations. The model is solved by Gurobi Optimizer ver. 8.1.1 with Python ver. 3.7 to generate the schedules for peak, slack, and general seasons. (5) Expert review: After solving the scheduling model, the reduction of risk, time and cost saved were analyzed. In addition, experts were consulted to help validate the overall benefits and feasibility of the scheduling model.
The research results are divided into three parts. The first part is the questionnaire survey results. The top three possible causes of fatigue are "heavy workload", "shift work", "lack of sleep" and "repetitive operations." With schedule optimization, the fatigue caused by shift work and repetitive operations might be improved. In addition, the body parts with the highest prevalence of musculoskeletal discomforts are lower back or waist (66.67%), hands or wrists (46.67%), and shoulders (46.67%). The second part is the results of on-site observation and risk assessment. The results showed that in computer tomography, angiography and general X-ray photography, when it is necessary to transfer the immobile patients between the bed and operation table for taking pictures of their middle body, the risk of musculoskeletal discomforts is the highest. The third part is the result of the scheduling model. Based on the subjective cumulative fatigue level and the musculoskeletal discomfort risk scores of each operation, the optimized schedule for the three types of seasons were obtained. Due to the impact of the COVID-19, it is difficult to implement the schedule immediately and get the feedback from the hospital. Therefore, the feasibility of implementation and the possible effect on reducing the prevalence of musculoskeletal discomforts among the technologists were discussed with experts of the hospital. The results showed that the optimized schedules help assign the technologists to multiple operations in a week, which might reduce the musculoskeletal discomforts caused by repeating the work of the same operation in a week.
Moreover, after analyzing the average musculoskeletal discomfort risk scores of each technologist, the results showed that the scores of adopting the optimized schedules are lower than the score of adopting the original schedule. Furthermore, the four technologists with the highest average cumulative fatigue level are re-assigned to the operations with lower risks such as general X-ray photography and mammography, while the four technologists with the lowest average cumulative fatigue level are re-assigned to higher-risk operations such as computer tomography and magnetic resonance imaging. This indicates that the optimizad schedules do help technologists with a higher level of subjective cumulative fatigue reduce the risk by assigning them to the operations with lower risk of musculoskeletal discomforts. Besides, the subjective cumulative fatigue level and the risk of musculoskeletal discomforts were lowly positively correlated in the original schedule but are moderately negatively correlated in the optimized schedules. It indicates that the higher the subjective cumulative fatigue, the more likely that the technologist would be assigned to operations with the lower risk of musculoskeletal discomforts.
Overall, this study took the subjective cumulative fatigue of medical radiation technologists and the risk of musculoskeletal discomforts of each operation into account, and constructed a scheduling model that minimizes the overall risk of musculoskeletal discomforts for the implementation in the hospital. With the scheduling model, the time required for scheduling can be shorter, and the overall risk of musculoskeletal discomforts among medical radiation technologists can be reduced.

摘要
第一章 緒論 1
1.1. 研究背景與動機 1
1.2. 研究目的與範圍 4
1.3. 研究架構與流程 4
第二章 文獻探討 9
2.1. 肌肉骨骼不適評估方法 9
2.1.1. 客觀之肌肉骨骼不適檢核表 9
2.1.2. 主觀知覺負荷及肌肉骨骼不適自覺量表 14
2.2. 放射線科之排班考量 15
2.2.1. 法規限制 15
2.2.2. 輪班規定 16
2.2.3. 主觀累積疲勞 16
2.2.4. 季節性差異 19
2.2.5. 特殊班別技能需求 20
2.3. 排班型態 20
2.3.1. 依排班內容分類 20
2.3.2. 依產業類別分類 21
2.4. 人員排班問題之求解方法 23
2.5. 小結 25
第三章 資料蒐集 26
3.1. 個案醫院放射線科排班現況 26
3.1.1. 排班規則 26
3.1.2. 排班需求 29
3.2. 主觀累積疲勞調查與肌肉骨骼不適盛行率調查 31
3.2.1. 主觀累積疲勞 32
3.2.2. 肌肉骨骼不適盛行率 37
3.3. 作業之肌肉骨骼不適風險評估 39
3.3.1. 一般X光攝影班次檢查項目統計資料 39
3.3.2. 現場作業觀察 41
3.4. 小結 49
第四章 排班模式建立 50
4.1. 參數定義 50
4.2. 變數定義 50
4.3. 常數定義 51
4.4. 數學函式 53
4.5. 取得最佳化的班表 65
第五章 研究結果 68
5.1. 問卷調查結果 68
5.1.1. 職場疲勞調查問卷 68
5.1.2. 肌肉骨骼不適問卷 70
5.2. 現場作業觀察結果 72
5.2.1. 一般X光攝影 72
5.2.2. 移動式X光（病房、加護病房、手術室）攝影 76
5.2.3. 血管攝影、磁振造影與電腦斷層攝影 76
5.2.4. 乳房攝影 76
5.2.5. 小結 77
5.3. 排班結果 79
5.3.1. 不同時節最佳化排班結果與排班模式改善比較 79
5.3.2. 專家意見 85
5.3.3. 小結 85
第六章 討論 87
6.1. 排班最佳化結果與放射師的主觀疲勞程度比較 87
6.1.1. 每位放射師肌肉骨骼不適風險總和與其被分配到的班別 87
6.1.2. 最佳化班表之分配與放射師個人主觀疲勞程度的關聯 96
6.1.3. 小結 100
6.2. 主觀疲勞程度 101
6.2.1. 以最不疲勞之日為基準做正規化 101
6.2.2. 以第一天的疲勞程度為基準做正規化 102
6.3. 現場作業肌肉骨骼不適分析 108
6.3.1. 使用工作相關肌肉骨骼傷害之風險因子檢核表分析醫療工作的限制 108
6.3.2. 肌肉骨骼不適風險檢核表的限制 109
6.3.3. 小結 110
6.4. 肌肉骨骼不適原因探討 110
6.4.1. 主觀因素 111
6.4.2. 排班影響 111
6.4.3. 小結 112
6.5. 其他影響 112
第七章 結論 113
7.1. 主要發現 113
7.2. 研究貢獻與應用 113
7.3. 研究限制與未來方向 114
參考文獻 116
附錄（一）馬偕紀念醫院人體研究倫理審查委員會審查證明 126
附錄（二）職場疲勞調查問卷 127
附錄（三）肌肉骨骼不適問卷 132
附錄（四）工作相關肌肉骨骼傷害之風險因子檢核表 142
附錄（五）一般X光攝影檢查作業流程、危險因子與時間 148
附錄（六）移動式X光（病房、加護病房、手術室）攝影檢查作業流程、危險因子與時間 173
附錄（七）血管攝影、磁振造影、電腦斷層攝影檢查作業流程、危險因子與時間 176
附錄（八）乳房攝影檢查作業流程、危險因子與時間 179
附錄（十）程式碼（以旺季為例） 181

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