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  • 學位論文

醫療服務之動態預約管理與產能配置

Dynamic Booking Management and Capacity Allocation for Healthcare Industry

指導教授 : 吳政鴻

摘要


近年來,我國民眾對醫療保健需求增加。然而,醫療資源有限,已無法滿足快速成長的市場需求,醫療產業如何適切地導入資源配置、預約管理模型,將助於發展有效率的醫療服務經營管理模式。不同於一般視營收為首要目標的產業,醫療服務產業必須兼顧利潤及醫療品質。此外,各類型顧客之行為具有異質性,反映於需求、取消以及預約未到診等行為上,為避免上述不確定性造成關鍵資源閒置或過度使用,進行預約機制設計時將一併列入考量。因此,本研究以動態規劃為基礎,提出一考量顧客需求、取消、未到診、檢查時間不確定性下的啟發式動態預約管理與產能配置模型,此模型具有高度彈性,適用於求解簡單或是複雜的顧客預約與產能配置問題,以有效利用有限產能,減少資源閒置,兼顧機構營收,同時避免因超時工作所增加的營運成本及其衍生的醫療品質損失。 為驗證本啟發式動態預約管理與產能配置法之效度,藉由程式語言撰寫一預約模擬系統,除了將本方法與動態規劃最佳預約管理與產能配置法作比較之外,也進行啟發式動態預約管理與產能配置法、固定產能配置之動態預約法、固定人數上限法的比較。模擬結果說明,本啟發式動態預約管理與產能配置法和動態規劃最佳預約管理與產能配置法在預約決策圖形、模擬效用值、產能利用率皆近似。而且不論在範例模型,抑或在台北某醫院健檢中心的實例模型中,啟發式動態預約管理與產能配置法之效用優於固定產能配置之動態預約法、固定人數上限法,證實其可行性與優越性。除此之外,在多種參數、增加資源,以及求解假設的顧客需求趨勢和實際不同等變動環境下,啟發式動態預約管理與產能配置法之效用仍維持優越表現,證實本模型具有穩健性。

並列摘要


This research uses dynamic programming to propose a flexible heuristic dynamic booking management and capacity allocation model. Recently, demands for healthcare are rising. However, finite resources can't fulfill infinite demands. It would be necessary to develop an efficient capacity allocation and booking management model to healthcare industry. The proposed model is able to approach simple and complex patients booking and capacity allocation problem such that resource utilization is high, and resource idleness and overtime is reduced. It also considers patient demand, cancellation, no-show, and service time uncertainties. Different from the other industries, optimization in healthcare service has to take profit, medical quality into account. Hence, we construct a utility function to evaluate performance, which comprise of revenue, overtime cost and the potential loss on service quality. And the objective is to maximize the expected utility. To manifest the robustness of our model, we use C# to establish a registration simulation system, and compare our heuristic model with other booking methods. In simple model, our heuristic model has nearly the same booking policy, utility and resource utilization as optimal booking policy of dynamic programming. Moreover, not only in simple model, but also in the real case from Healthcare Management Center (HMC) of a certain hospital in Taipei, our heuristic model is more robust and superior to fixed capacity allocation and booking method, and constant upper-limit booking method under various parameters.

參考文獻


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