Title

加護病房非計劃性重返與疾病嚴重度間之相關性探討

Translated Titles

The Relationship between the Unplanned Readmission and Severity of illness in the Intensive Care Units

Authors

葉淑玲

Key Words

加護病房 ; 非計劃性重返 ; 疾病嚴重度 ; Intensive care units(ICU) ; unplanned readmission ; severity of illness

PublicationName

臺北醫學大學護理學系碩士暨碩士在職專班學位論文

Volume or Term/Year and Month of Publication

2007年

Academic Degree Category

碩士

Advisor

張文英

Content Language

繁體中文

Chinese Abstract

因疾病嚴重度和非計劃性重返均是加護病房重要檢視病人病情變化與品質指標,但有關的研究卻甚少,故本研究目的旨在(一)了解加護病房非計劃性重返與未重返病患之基本屬性及其疾病嚴重程度(APACHE II)的分佈狀況。(二)探討加護病房非計劃性重返病患之基本屬性、疾病嚴重度(APACHE II)與非計劃性重返之差異性與相關性。(三)以APACHE II偵測非計劃性重返之敏感度(Sensitivity)與特異性(Specificity)閥值。 本研究採回溯性設計,以北部某醫學中心內科加護病房之病患為研究對象,共收取重返組43人及未重返組129人,並依自擬之「加護病房非計劃性48小時內重返病患資料收集表」為收集工具,進行病患病歷資料登錄。以描述性統計、卡方檢定、獨立樣本t檢定、邏吉斯迴歸、及ROC曲線方法進行資料分析。 結果顯示兩組在基本屬性中,僅重返經驗及重返時間具有統計上顯著差異。而在疾病嚴重度(APACHE II)之評估項目中,動脈含氧量(p=0.000)、白血球(p=0.008)、昏迷指數(p=0.0047)、急性生理分數(p=0.000)、疾病嚴重度分數(p=0.000)也呈現統計上之顯著差異(p<0.05),但只有白血球數及疾病嚴重度分數可有效預測48小時內重返事件。並以ROC曲線圖表偵測重返組的疾病嚴重度分數,曲線下面積為0.689,95%信賴區間為(0.598, 0.780),顯示以疾病嚴重度分數(APACH II)來診斷48小時內非計劃性重返加護病房是具有中度準確之診斷價值,並選擇APACHE II 18.5分(敏感度39.5%,特異性86%)為相對最高敏感性及特異性閥值,超出此閥值則病患轉出後易發生48小時內非計劃性重返事件。 本研究結果可提供臨床加護團隊審慎評估病患轉出加護病房前之決策依據,並藉由疾病嚴重度分數之評估依據,事先讓家屬了解病患可能有非計劃性重返之危險機率。

English Abstract

Owing to severity of illness and the unplanned readmission are the important criteria to inspect patents’ condition when in Intensive Care Unit (ICU), but relevant researches are very few. Therefore, the objective of this search would try to: (1) understand the distribute of characteristics and severity of illness between unplanned and non readmission patients; (2) explore the difference and relevance between characteristics, severity of illness and readmission patients; (3) detect unplanned readmission patents’ valve value of Sensitivity and Specificity, which was examined by APACHE II score. Backtracking design was adapted by this research. It contains unplanned readmission (43 people) and non-readmission (129 people) as the sampling groups, who are patients of MICU in one medical center in Northern Taiwan. Moreover, the questionnaire that made by the author is the tool of data collection, that helps to provide patients information for coding as well. Finally, all these data would be conducted by SPSS version 13.0 English edition to process some data analyses, including Descriptive Statistics, Chi-Square test, Independent t-test, Logistic Regression, and ROC curve. The findings showed the two sets in the comparative of patients’ characteristics, which has showed that only the experience of returning and the time of returning have significant difference. In addition, under the estimation in the level of severity of illness(APACHE II), arterial oxygen(p=0.000)、white blood cells(p=0.008)Glasgow coma scale (GCS)(p=0.0047)、acute physiology score (APS)(p=0.000)、yet the levels of severity of illness(p=0.000)have dramatically divergences(< 0.05). On the other hand, the ones have significant differences, only the numbers of white blood cell count and the levels of severity of illness are able to predict the issue of readmission in 48 hours. Then based on the readmission group of the levels of its illness lined ROC curve, the area under ROC curve is 0.689, which was under the confidence interval of 95%(0.598, 0.780). That is to say, diagnosing by the levels of severity of illness(APACH II)is more accurate and estimated that its valve value was 18.5(the Sensibility was 39.5% while Specificity was 86%). Once if exceeding this value, the percentage of unplanned readmission in 48 hours will easily occur. The results of this study might provide clinical ICU team with some decision-making evidence to carefully evaluate whether patients were able to transfer from ICU or not. Furthermore, the assessment evidence of disease severity score could let patient’s family members understand beforehand, that what dangerous probabilities of unplanned readmission might happen.

Topic Category 醫藥衛生 > 社會醫學
護理學院 > 護理學系碩士暨碩士在職專班
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Times Cited
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