急診室是一間醫院的縮影，提供24小時的醫療服務，由於健保制度的實施，讓醫療資源的使用門檻下降，導致民眾不論大小症狀都往急診室跑，時常引發急診室壅塞，壅塞的急診室會讓病患醫療品質下降，甚至引發急診室暴力。因此如何讓病患儘速離開急診室，減少急診室壅塞成為十分重要的議題。我們分析了病患在急診室內的醫療流程及人力資源的分配，其中醫師與護理師在病患急診流程中都扮演相當重要的角色，病患在急診流程中會受到多位護理師服務治療，但除了會診外通常只會受到一位醫師診治，醫師工作包含對病患初次問診與診療後的評估處置，急診室內醫師人數相較護理師來的少，我們不希望醫師成為流程瓶頸，因此我們透過安排醫師在這兩項流程中所有病患的執行順序，減少病患的等候醫師的時間。
我們利用即時系統的概念將病患的醫療流程模擬為工作(Job)，醫師等人力資源模擬為處理器(Processor)，並混合Earliest Deadline First(EDF)與Shortest Job First(SJF)的概念，提出一套混合式(Hybrid)的即時排程方法，透過排序病患工作並分配給醫師執行，協助醫師選擇工作流程，更讓病患盡可能在各檢傷等級的安全等候時間內接受治療，並降低病患等候的時間。在模擬實驗中本研究方法與其它方法做比較，結果顯示我們的方法與EDF方法的錯失結束底線機率(deadline missed rate)僅相差1%，在全體病患對於醫師的平均等待時間減少達22%。

The emergency department is the epitome of a hospital, it provides 24-hour urgent care to patients. The emergency department(ED) is often overcrowded, because the patients overuse of National Health Insurance (NHI) and medical resource. ED crowding will affect medical quality and even lead to the violent event. Therefore, how to improve ED crowding has become an important issue. We analyzed patient flow and resource allocation in the ED. Physicians and nurses play vital role in the patient flow, but there are fewer physicians than nurses. The work of the physician includes diagnosis and evaluation. We want to reduce patient waiting time and improving ED crowding by sorting the patients in a certain order. We recommend the patient order sets to optimize physician workflow.
We simulate the patient's medical process as a job and the physician as a processor by using the concept of real-time system. We proposed a hybrid scheduling method to ensure that patients with various level of triage can be treated within the perceived waiting time. This method combine the earliest deadline first (EDF) and shortest job first (SJF).In addition to helping physicians choose patients, it also can reduce the patient's length of stay (LOS) in the ED. In the simulation experiment, this method was compared with other methods. Our method and the EDF method's deadline missed rate are only 1% different, but can reduce the average waiting time of patients about 22%.

[1] Drew B Richardson. Increase in patient mortality at 10 days associated with emergency department overcrowding. The Medical Journal of Australia. 2006;184:213-216.
[2] Mancini, Marguerite R, and Alice T Gale. Emergency Care and the Law. Rockville, Md: Aspen Systems Corp, 1981.
[3] Rinderer ZM. A study of factors influencing ED patients’ length of stay at one community hospital. Journal of Emergency Nursing. 1996;22,105-110.
[4] Sprivulis PC, Da Silva JA, Jacobs IG, Frazer AR, Jelinek GA. The association between hospital overcrowding and mortality among patients admitted via Western Australian emergency departments. Med J Aust. 2006;184:208–212.
[5] Forero R, Hillman K. Access Block and Overcrowding; A Literature Review. Melbourne: Australasian College for Emergency Medicine, 2008;1-26.
[6] Hoot NR, Aronsky D. Systematic review of emergency department crowding: Causes, effects, and solutions. Annals of Emergency Medicine. 2008;52:126-36.
[7] Asplin BR, Magid DJ, Rhodes KV, Solberg LI, Lurie N, Camargo CA, Jr. A conceptual model of emergency department crowding. Annals of Emergency Medicine.2003;42:173–80.
[8] Yarmohammadian MH, Rezaei F, Haghshenas A, et al. Overcrowding in emergency departments: A review of strategies to decrease future challenges. Journal of Research in Medical Sciences. 2017;22:23.
[9] Jane W S Liu. Real-Time Systems. University of Illinois at Urbana-Champaign. ISBN 0130996513,9780130996510, 2000.
[10] J. Xiao, LJ Osterweil, and Q Wang. Dynamic Scheduling of Emergency Department Resources. Proceedings of the 1st ACM International Health Informatics Symposium.2010;590-599.
[11] National Hospital Ambulatory Medical Care Survey: 2015 Emergency Department Summary Tables. U.S. Department of Health and Human Services Centers for Disease Control and Prevention National Center for Health Statistics.2015. https://www.cdc.gov/nchs/data/nhamcs/web_tables/2015_ed_web_tables.pdf.
[12] Martin, M., et al., Mapping patient flow in a regional Australian emergency department: A model driven approach. International Emergency Nursing.2010. 19(2):75-85.
[13] 胡勝川，急診醫師與緊急醫療救護(第三版)，ISBN：9578804504，2002。
[14] 賴政皓，“應用資料探勘技術提升急診醫學檢傷分類之一致性”，國立勤益科技大學工業工程與管理研究所，碩士論文，2007。
[15] 陳怡婷，“影響教學醫院主治醫師生產力之因素研究-以台灣北部某教學醫學中心為例”，長庚大學管理學研究所，碩士論文，2000。
[16] 劉敏玲，“急診病患對就醫之感受等候時間、實際等候時間與滿意度之相關研究-以某醫學中心為例”，國立臺灣大學醫療機構管理研究所，碩士論文，2001。
[17] 韓季霖，“台灣地區醫師人力供需之研究－灰色預測模式之應用”，銘傳大學管理科學研究所，碩士論文，2000。
[18] 蔡柏祥，“醫療資源績效評比與改善之研究”，東海大學工業工程與經營資訊學系，碩士論文，2011。
[19] 翁紹仁，“大型分散式醫療網即時模擬系統之研究研究成果報告(精簡版)”，行政院國家科學委員會專題研究計畫成果報告，2011。
[20] 趙若婷，“運用精實系統改善急診室價值流程之研究 -以中部某醫學中心為例”，碩士論文，中國科技大學企業管理研究所，2013。
[21] 葉進儀、陳民枝、吳軍劼，“使用 UML 與模擬技術於醫院急診室流程改善之研究-以中部某區域教學醫院為例”，大葉學報第十一卷第一期，91-102，2002。
[22] 衛生福利部統計處:醫療資源現況及服務量，( https://dep.mohw.gov.tw/DOS/lp-3555-113.html)，2016。
[23] 林靜宜，“醫院輸送人力配置與作業流程改善－以某區域教學醫院為例”，國立雲林科技大學工業工程與管理研究所碩士班，碩士論文，2009。
[24] 唐于絢、蔡米山，先到院者先看病嗎《急診檢傷分類 》，( http://www.kmuh.org.tw/www/kmcj/data/8909/4558.htm)，2000。
[25] 黃柏諭，“運用系統模擬最佳化探討動態急診部資源規劃之研究”，東海大學工業工程與經營資訊學系，碩士論文，2013。
[26] 衛生福利部規範「急診五級檢傷分類基準」，( https://dep.mohw.gov.tw/DOMA/cp-2710-38118-106.html)，2017