臺灣博碩士論文加值系統

因為健保制度政策抑制醫療費用的成長，因此醫療機構必須精確控制成本，而醫藥與耗材乃醫院成本的第二大科目，是成本控制的一個重要環節，而控制醫藥與耗材存貨的最有效方法不是供應鏈上下游業者各自為政，反而是需要一起努力配合。在醫療供應鏈裡，醫療機構是下游顧客，而物流商是銜接醫療機構和上游供應商的橋梁。目前的醫療供應鏈中，醫療機構的訂購次數頻繁，導致物流商出貨次數頻繁。從物流商的角度出發，出貨次數頻繁表示配送成本、處理成本、理貨成本都會增加；從醫院的角度來看，頻繁的訂購是否就是最好的方式呢？上下游可否透過下游訂購與上游出貨之間的有效整合，找出對醫療供應鏈上下游業者都有助益的供應鏈創新解決方案？
本研究選擇供應鏈下游的C醫院和上游的Z物流公司為對象，蒐集醫院向物流商訂購的營運數據，以及物流商對醫院出貨的營運數據，進行深入分析，以探討醫院訂購模式改變後，將會對雙方產生哪些成本或效益上的影響。透過這些資料的模擬分析，研究發現選擇訂購次數前排名前20%的品項，將其平均分成兩類並透過隔週訂購一類的模式，可以得到最佳的量化效果。本研究進一步分析雙方協作的機會，探討導入模擬分析最適訂構模式下，雙方應該採取何種協作模式及協作成功的關鍵因素。
本研究主要研究結果彙整說明如下：
一、 個案醫院
個案醫院的原始訂購模式的變異性很大，造成重複的人力作業成本，以及存貨過多的現象。本研究模擬醫院採用新訂購模式的成效，結果發現新訂購政策能夠節省C醫院的驗貨成本、人力成本與存貨持有成本，合計共186,174元；另外，採購及進貨作業時間合計可減少1,113分鐘。
二、 個案物流公司
個案物流公司因為個案醫院的訂購變異性很大，導致貨車沒有達到最大的裝載效率，使得營運作業成本增加。模擬個案醫院根據醫院的新訂購政策採用新出貨模式，結果發現個案物流公司的理貨成本、處理成本將會增加，但是存貨水準下降了141,367，配送成本下降了45,700，而總物流成本則下降了150,216元。
三、 綜合分析結果
本研究發現除了醫院與物流公司間的存貨政策問題之外，個案物流公司與個案醫院的庫存資料在比對上產生落差，經進一步探討，發現醫院端會有驗收退貨、物流公司端會有分次出貨等狀況，而且雙方資訊系統為兩個獨立系統，無法即時調和存貨資訊上的變化，造成雙方存貨資訊上的落差。本研究建議雙方除在訂購模式協作之外，未來也需要整合彼此的資訊系統。若要使供應鏈效益極大化，本研究發現如導入越庫作業，可將存貨降低至僅保留緊急用量的最低水準。
四、 供應鏈協作分析結果
研究進一步探討如欲改變個案醫院與物流公司的訂購與出貨模式，雙方組織應具備哪些協作條件？本研究結合文獻與研究期間的實際觀察，發現協作如欲成功，必須具備六個要件：雙方高層如不支持，協作成功的機率將非常的小；雙方成立專案聯合管理團隊推動各項協作方案，彼此交流學習並定期評估協作績效，隨時改善不適之處；雙方資訊系統連線可使雙方即時確認貨品狀況，以即早發現原廠控貨，或是貨品留滯海關無法出關等因素，讓醫院可以掌握貨品第一手資訊，對緊急情形可預作應變措施；雙方建立流程關係人互動環境，透過跨組織教育訓練，確保流程關係人可以適應新的工作模式；個案醫院記錄使用單位使用量，以掌握醫院的需求量，作出更精確的訂購政策；雙方應朝越庫作業與拉式供應鏈目標發展，使供應鏈上的庫存、人力、空間等資源可以更節省。

As the national healthcare insurance policy restricts the growth of medical expenses, healthcare institutions must control their costs very cautiously. Parma products and medical devices are the second largest cost category for most healthcare institutions. It is not effective for upstream and downstream members in the healthcare supply chain to work independently, rather through the coordinated efforts of supply chain members, better performance may be achieved. Within the context of healthcare supply chain, healthcare institutions are downstream customers while logistics firms act as the bridges between healthcare institutions and the upstream suppliers. Currently, the healthcare institutions place orders very frequently, which have caused very high shipping frequencies for logistics firms. This in turn results the increase of delivery costs, order processing costs and warehousing costs for logistics firms. Therefore, it is questionable whether it is beneficiary for hospitals to order frequently. Hence, it is worthy to investigate innovative supply chain solutions which can provide effective integration of the ordering and shipping operations between healthcare institutions and logistics firms.
A regional level Hospital, C and the largest pharmaceutical logistics company Z are selected as the cases for this study. We collected the ordering operational data from C regarding to Z and shipping operational data from Z regarding to C so as to conduct detail analysis of the cost/benefit effects when ordering patterns were changed. Based on the order policy change simulation of these baseline data, this research found when top 20% items sorted by yearly item order dates were selected and changed their ordering policy from irregular daily ordering to (10%+10%) alternate bi-weekly ordering, it would provide the best quantitative results on total logistics costs savings. This research further analyzed the collaborative opportunities between two parties, what collaborative models should be adopted, and the key success factors needed under the simulated optimal ordering policy.
The research results are summarized below:
1. Hospital C
Large variation in Hospital C's original ordering patterns has caused additional labor costs and excessive inventory. This research simulated various new ordering patterns. The optimal ordering pattern was able to save Hospital C's inspection cost, labor cost and inventory holding cost, with a total saving of $186,174 (Taiwan Dollars). Additionally, purchasing time and handling time for receiving were decreased by 1,113 minutes.
2. Company Z
With the large variations of the ordering patterns of Hospital C, Company Z could not utilize efficiently its shipping trucks and had led to the increase of the operating cost. Through simulation analysis of the optimal ordering policy, we found that the order picking and order processing costs will increase; however, inventory levels can be decreased to $141,367, distribution costs can also be decreased to $45,700 and the total logistics cost can be decreased to $150,216.
3. Results of comprehensive analysis
Apart from inventory policy and ordering problems, inventory data from both Hospital C and Company Z could not be matched. By further analysis, this research found that Hospital C had experienced the late delivery or multiple-day deliveries of an order. Sometimes, there was a shortage of the product supply but Z did not inform C earlier, and their information systems can not mediate changes of the inventory information. Thus, information gaps between two organizations were caused. Therefore, this research suggests Hospital C and Company Z not only collaborate in ordering and shipping policies, but also integrate their information flows. To achieve the maximum supply chain effectiveness, we found that developing a cross docking based supply chain operations can reduce the inventory level to the minimum level for emergency needs.
4. Results of supply chain collaboration analysis
This research also studied what requirements would be needed if Hospital C and Company Z decided to collaborate on implementing the optimal ordering and shipping policies. Combining findings from literatures and observations during the study period, this research has found that for Hospital C and Company Z to collaborate successfully, they should follow at least the following six requirements:
(1) if top management do not give full support, probability of success of collaboration is very low;
(2) Hospital C and Company Z should establish joint project team to plan and execute the collaboration program. In this way, project team can learn from each other, regularly assess project performance, and make corrections to any problem quickly;
(3) Both parties should provide good interface to connect their information systems to provide inventory status visibility to discover as soon as possible the product delay situations due to pharmaceutical suppliers or customs clearance. In this way, Hospital C can access real time and accurate inventory status information and prepare in advance any emergency situations;
(4) Hospital C and Company Z should establish an interactive environment for employees involved in the new collaborative program to provide good training to them to ensure they can smoothly adapt to the new working model;
(5) Hospital C should record the product usage of user units to gain better demand information and make accurate ordering policy;
(6) In the long run, Hospital C and Company Z should move toward a pull-based cross docking supply chain to reduce inventory, labors, and space resources.

第一章 緒論 1
第一節、 研究背景與動機 1
第二節、 研究目的 3
第二章 文獻探討 5
第一節、 存貨的定義、目的與功能 5
第二節、 存貨控制 8
第三節、 存貨管理方法 18
第四節、 供應鏈協作 23
第三章 研究方法 32
第一節、 研究架構 32
第二節、 研究方法 33
第三節、 研究對象 34
第四節、 資料收集 36
第五節、 研究限制 41
第四章 個案分析 43
第一節、 Z物流公司出貨現況及新出貨政策模擬分析 43
第二節、 C醫院訂購現況及新訂購政策模擬分析 57
第三節、 政策模擬分析結果彙整及綜合討論 72
第四節、 C醫院及Z公司供應鏈物流協作模式探討 75
第五章 研究結論與建議 81
第一節、 研究結論 81
第二節、 對研究個案之建議 82
第三節、 後續研究建議 83

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