背景：不少醫院別醫療照護品質評比機構使用手術死亡率作為醫療照護品質指標，但是也引起許多方法學爭議。有學者提出「搶救不力」(failure to rescue)指標(分母是手術發生併發症個案數，分子是這些個案死亡數)比較能反映照護團隊的經驗與照護能力，也就是及早發現併發症(譬如手術後出血或感染或是栓塞)，及早啟動搶救措施避免死亡發生。
目標：本研究使用病患風險調整死亡率的醫院別排序當金字標準，首先與使用粗死亡率與年齡標準化死亡率醫院別排序比較是否有差異；二是與使用粗併發症發生率、年齡標準化併發症發生率與病患風險調整併發症發生率醫院別排序比較是否有差異；三是與使用粗搶救不力率、年齡標準化搶救不力率與病患風險調整搶救不力率醫院別排序比較是否有差異。最後嘗試同時使用三種指標及群組化三分位方式來排序醫院，檢視是否能提供較佳標竿學習訊息。
材料與方法：本研究使用2000-2010年全民健保申報住院醫療費用清單明細檔比較醫院別執行冠狀動脈繞道術(CABG)與經皮冠狀動脈擴張術(PTCA)兩處置之死亡率、併發症發生率與搶救不力率排序差異。這三個率也都分別比較病患病患風險調整率、年齡標準化率與粗率排序之差異。不同指標醫院別排序之相關使用斯皮爾曼等級係數檢定。
結果：在研究期間執行CABG一百例以上的醫院有41間，執行PTCA二百例以上的醫院有84間。以年齡標準化死亡率進行醫院別排序的結果與以病患病患風險調整死亡率醫院別排序結果(金字標準)的相關係數：CABG為.99，PTCA為.98。若以粗死亡率進行醫院別排序，與金字標準的相關係數下降為：CABG為.98，PTCA.93。病患病患風險調整併發症發生率與病患病患風險調整死亡率的的相關係數：CABG為.62，PTCA為.63。病患病患風險調整搶救不力率與病患病患風險調整死亡率的的相關係數：CABG為.80，PTCA為.87。如果同時以三個指標區分高中低三分位，執行CABG醫院可區分為十四組，PTCA可區分為十八組，可以提供較細膩的標竿學習討論。
結論：本研究顯示搶救不力率與病患病患風險調整率的相關係數沒有預期高，最主要理由是本研究的病患病患風險調整率只是用健保申報資料的共病症進行調整，缺乏病患嚴重度資料(譬如冠狀動脈阻塞程度與心臟功能相關數據)，所以不見得是很好的金字標準。未來還是應該透過病歷資料分析確認搶救不力的價值。不過，同時呈現三種指標的群組化分組來排序，應該可以提供比較多元資料提供標竿學習參考。

Background: Ranking hospital quality of care according to surgical mortality had many debates. Silber proposed “failure-to-rescue”, the mortality rate among surgical patients with complications, as an emerging quality indicator.
Objectives: The objective of this study was to assess the correlation among hospital quality assessment ranking based on crude/ age-adjusted/ risk-adjusted mortality, complication and failure-to-rescue rate. We then assessed the ranking hospitals by combining three indicators and using aggregated information to provide better benchmark learning.
Materials and methods: This study use inpatient claims data set to compare hospital outcome rankings for three different measure of quality of care: hospital death, complication and failure-to-rescue.
Results: For 41 hospitals of CABG and 84 hospitals of PTCA, the correlation between hospital rankings based on age-adjusted mortality rate and patient-risk-adjusted mortality rate were high correlations (CABG, r=.99; PTCA, r=.98). A similarly high correlation was present between the patient-risk-adjusted mortality and FTR rate (CABG, r=.80; PTCA, r=.87). There were moderate correlations between patient-risk-adjusted complication and mortality (CABG, r=.62; PTCA, r=.63).
Conclusions: The findings of this study indicate that the correlation between failure-to-rescue and patient-risk-adjusted mortality rate was not as high as expected. One of the possible explanations was that many severity of illness information were not available in claims data. Studies using medical record to verify the validity of failure-to-rescue concept are needed. However, the classification of hospitals according to combined information could provide useful information for benchmark learning.

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