雖然目前醫院或診所的門診預約掛號系統大都已採用預約掛號的方式來減少病人等待時間。然而傳統上醫院門診預約掛號系統的設計是從管理為主的角度來進行設計，強調資源充分利用，採取超額預約方式，使病人仍必須花費大量時間等待。所以如何從病人及醫院的立立場來平衡病人的等待時間及醫生的使用率，已經成為未來醫院管理不可避免的議題。
為了能讓病人減少等待且醫生使用率不致低落。本研究首先分利實際收集所得資料，將具有相近看診時間的病人予以歸類。接著則對於包含了不同病人種類的多變環境發展各別適用的排程法則。最後利用倒傳遞類神經網路辨識外在環境的變化，使預約系統能夠根據新的環境去選擇適合的排程法則
研究結果顯示，利用病人基本特徵進行分類是可行的方法，且類神經網路能有效的發覺環境的改變。這可以讓預約在不同的環境下，切換至先前所定下的適用預約排程法則，使病人等候時間減少且醫生的使用率也能維持一定的水準。

Although appointment systems have been used by the most clinics and hospitals to reduce patients’ waiting time, traditionally, appointment systems are designed from management view; these systems overbook patients to increase resources utilization, which cause long patients waiting time. Therefore how to design an appointment system not only from the management’s view but also from patients’ view to balance waiting time and resources utilization has become an unavoidable issue that must be addressed.
In order to reduce patients’ waiting time and to maintain resources utilization, this study first analyzed the data collected from the hospital, and clustered patients with similar processing times. Next, for each individual environment, which consists of various clusters, the research developed a most feasible scheduling rule that yields the better performance. Finally the study used Backpropagation Neural Network to identify any significant changes in the environment, so that the appointment system could choose the appropriate scheduling rule according to the every of environment.
The results of the research indicate that the method of clustering patients based on their characteristics is feasible, and using Neural Network can effectively detect the environment variations. Also it is feasible to pre-programmed the better scheduling rules that can be switched in different environments for reducing patients’ waiting time and maintaining resources utilization at proper level.

誌謝 II
博碩士論文電子檔案上網授權書 III
博碩士論文電子檔案上網授權書 IV
各類博士暨教育類碩士論文授權書 V
摘要 VI
ABSTRACT VII
目錄 VIII
表目錄 X
圖目錄 XI
第一章 導論 1
1.1 研究緣起 1
1.2 研究目的 5
1.3 研究流程 6
1.3.1 實況調查 7
1.3.2 模擬 8
1.3.3 訂定預約作業原則 9
1.3.4 建立需求樣模進行類神經網路學習 10
1.3.5 驗証系統功效 10
第二章 文獻探討 11
2.1 醫院的管理 12
2.2 服務品質與等候 13
2.3 預約系統的影響 16
2.4 運用預約以改善等候 18
2.5 門診排班原則 20
2.6 績效指標 22
2.7 類神經網路 23
2.8 模擬工具的使用 28
第三章 研究方法 30
3.1 彈性門診預約系統概述 31
3.1.1 病人掛號流程 32
3.1.2 醫院排程作業 35
3.2 樣模與排程法則 36
3.2.1 資料收集與分析 37
3.2.1.1 收集病人特徵資料 38
3.2.1.2 病人分類 39
3.2.2 基本假設 43
3.2.3 模擬環境設定 44
3.2.3.1 外在環境樣模 45
3.2.3.2 模擬病人到達模式 47
3.2.3.3 模擬環境設定 48
3.2.3.4 績效指標定義 49
3.2.4 發展排程法則 51
3.2.4.1 名詞解說 52
3.2.4.2 排程法則 56
3.2.4.3 決定外在環境樣模適用排程法則 60
3.3 類神經網路 61
第四章 結果與討論 63
4.1 分類組數的影響 64
4.2 樣模一結果討論 66
4.3 容忍度分析 70
4.4 樣模二至五的適用排程法則 72
4.5 樣模二、樣模三、樣模四的結果討論 74
4.6 樣模五的結果討論 75
4.7 類神經網路學習狀況 77
4.8 模型辨認錯誤影響 78
第五章 結論與建議 80
5.1 研究結論 80
5.2 未來研究建議 82
參考文獻 83
中文部份 83
英文部份 84
附錄一 模型結果 87
附錄二 類神經網路訓練資料 105
附錄三 類神經網路測試資料及結果 107

中文部份
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[3] 黃俊智著，應用模擬技術探討專科診所之門診預約掛號制度，台灣大學公共衛生學院醫療機構管理研究所碩士論文，民國86年7月.
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英文部份
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