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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/100255


    Title: 互動多模式決策支援之研究─醫院藥品存貨管理決策
    Other Titles: An Interactive Decision Support Using Multiple Models: The Hospital Drugs Management for Inventory Level
    Authors: 李俊民;張義範
    Lee, Jiunn-Min;Chang, Yi-Fan
    Keywords: 預測模式;醫師與藥品關係矩陣知識庫;決策支援系統;資料倉儲
    Forecasting Model;Doctor and Drug relation Matrix;Data Warehouse
    Date: 2003-06
    Issue Date: 2016-08-16 15:17:06 (UTC+8)
    Abstract: 一般全民健保的藥品及醫療材料的資材約佔醫療院所營運成本的30～40%，其中藥品又約佔資材成本的80%以上；然而醫療院所在經營上，對於藥品存貨管控卻經常忽略。另外，文獻探討顯示解決方案都是運用複雜且單一統計預測模式，無法支持不同藥品間的使用特性，及缺乏適當的分析工具。因此管理者尚延用過去的經驗法則，使得訂購及儲存成本無法有效地改善與降低。本研究考慮各種藥品在實務上的不同需求特性，當在需求預測時，為降低潛在存貨成本，則指數平滑法較優於貝氏自迴歸（GL Shoesmith et al.,2001）。所以，運用時間序列的預測模式－包括指數平滑、移動平均、互動加權、季節變動、算術平均法、及定性法等等；將具有專業主觀的醫師處方（order）行為，轉置為具體量化的醫師與藥品關係矩陣知識庫（knowledge base）。然後，建立多維度的資料倉儲（data warehouse）以包含藥品耗用的歷史資料，及執行醫師與藥品間具關聯性的線上分析處理（online analysis process, OLAP），並採用（s, S）的存貨策略來控制存貨水準，適時提出訂購需求。本研究以VB（Visual Basic）及SQL2000為基礎，透過微軟Excel的友善圖形介面，建立互動多模式的訂購量決策支援系統。經實驗結果確有顯著性的提高預測精確度，及有效改善決策品質、降低訂購及儲存成本。
    Generally speaking, the cost percentage for purchasing the medication and the medical material related to the total cost for operating a hospital is 30~40%. For the purchasing cost, the medication`s cost occupies 80% more. Unfortunately, medical institutes usually neglect the drug inventory management and literature review shows that all institutes only use a class of complicated forecasting models. For example, GL Shoesmith & JP Pinder (2001) compared demand forecasts computed using several forecasting models and showed that the techniques using exponential smoothing and seasonal decomposition was effective in improving forecast accuracy and reducing inventory costs. But these techniques do not consider the important factor for individual medication`s characteristics and also lack an appropriate analytic tool to reduce the ordering and holding cost.In this study, characteristics of medications` demands are included, several forecasting models can transform the judgments of physician prescribing behaviors into the knowledge base of the quantifiable doctor and drug relation matrix, and then all the required data are extracted to a multidimensional data warehouse. OLAP for analyzing doctor and order relations can be implemented on the data warehouse in a prototype system. The experimental results shows that the interactive decision support system can give effective and efficient decisions for reducing the ordering and holding cost.
    Relation: 資管評論, 12, 139-158
    MIS review
    Data Type: article
    Appears in Collections:[MIS review(資管評論)] 期刊論文

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