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題名:應用馬氏距離與SERVQUAL量表於醫療服務品質缺口之分析研究
作者:李政宗 引用關係
作者(外文):Cheng-Chung Lee
校院名稱:中華大學
系所名稱:科技管理學系(所)
指導教授:賀力行
學位類別:博士
出版日期:2009
主題關鍵詞:多變量服務品質缺口分析馬氏距離Gap analysisMahalanobis distanceMultiple variablesSERVQUALService quality
原始連結:連回原系統網址new window
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隨著時代的變遷、社會的脈動、生活水平的提昇,國人不僅對醫療服務的需求增加,對服務品質的要求亦不斷提高。由於病患的自我意識提高,對醫療上的需求已如一般消費者挑選商品一般,不僅僅要求醫療效果,也要求在醫療過程中作業效率要快速、收費要合理,服務品質要良好,因此各醫療院所無不投入財力、人力、物力從不同的角度來研究改善,以提昇醫療服務品質,滿足病患的需求,並藉此以增加行政效率及提昇競爭力。
本研究應用「馬氏距離」法與「SERVQUAL」量表發展出一套「醫療服務品質缺口衡量模式」,藉由此模式衡量醫療服務品質的缺口五,進而瞭解門診病患對醫院服務品質的感受程度與期望程度之差距。本研究首先整合相關文獻於歸納出五個服務品質構面與二十二項服務品質指標並形成問卷後,即針對一個案醫院之門診病患進行隨機抽樣調查。研究結果顯示,門診病患對醫院服務品質的感受程度與期望程度有顯著差異存在,且利用「馬氏距離」法將每個服務品質構面視為馬氏空間,並將各個構面下的每個服務品質指標視為一多變量,經衡量每個構面所得之缺口值較傳統之服務品質缺口分析法更準確。就管理意義而言,馬氏距離不僅適合用於衡量醫療服務品質的缺口,亦可以改進過去一些簡單的陳述性假設,更可以提供更準確的結果作為醫療院所改善醫療服務品質之決策依據。
本研究之學術貢獻,除有助於台灣新興「醫務管理實務」及「醫院品質管理」等相關教學單位或研究領域外,更為無形、主觀之醫療服務認知行為提供一個具體的衡量方法,不僅適用於醫療範疇上之相關單位,其他各行各業之服務業者亦可個別為自己的從業單位量身訂做一套問卷後,如法炮製進而找出己身之缺點,並歸納出己身之服務品質衡量指標。
With the changes, pulsation, promotion of the living standard of the society of the times, compatriot's not merely demand for medical care increases, is also improving to the demand for serving quality constantly. Because the patient's self- consciousness improves, already if general consumers have selected the goods generally to the demand on medical treatment, not merely require the medical result, require too it is wanted rationally that the efficiency of the homework want fast, charge in the medical course, serving quality want it well, so every medical institute invests financial resources, manpower, material resources to study and improve from different angles invariably, in order to promote medical care quality, meet patient's demands, and by increasing administrative efficiency and promoting the competitiveness by this.
SERVQUAL has been widely applied in service industries since proposed, but there are also several arguments raised. This study focus on calculation of gap score, proposes a conceptual model to apply Mahalanobis distance to the measurement of the gap score of each dimension, the method is to regard each dimension as a Mahalanobis space, and to regard each element as its multiple variables. The result showed several differences between conventional gap analysis and Mahalanobis distance analysis. The advantage of this method is the variances and relativity can be included in measurement, which may provide more accurate result for correct decision making.
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