臺灣博碩士論文加值系統

研究背景：於2015年，由醫策會的「醫療品質指標管理中心」規畫並辦理「醫院品質績效量測指標系統與落實品質改善計畫」推動第二階段，新增中風病人層級的指標。而「非計畫性再住院」被認為是醫療機構重要的結果評值成效指標之一，如何降低非計畫性再住院的發生一直是醫療機構所重視的議題。

研究目的：瞭解缺血性中風病人非計畫性再住院的病人特性，以及探討中風病人層級過程面指標的組合分數與30/90天非計畫性再住院之間的關係。

研究方法：本研究資料來源取自於臺大醫療體系醫療整合資料庫、P4P中風指標登錄表，及臺大總院腦中風個案管理檔進行本研究的資料分析。以2015年10月~2016年9月出院之缺血性腦中風病人為研究母體，利用複羅吉斯迴歸模型，探討缺血性腦中風病人層級過程面指標的兩種組合分數(原始分數加總、70%標準法)與30/90天內是否有非計畫性再住院的關係及可能影響之相關因素。

研究結果：病人分布情形為男性占59%，平均年齡68.78歲。病人層級過程面指標的兩種組合分數分別與30天內非計畫性再住院達統計上顯著相關(p = 0.0195 ; p = 0.0298)。病人危險因子部分，抽菸/心臟相關疾病分別與30天內/ 90天內非計畫性再住院達統計上顯著相關(p = 0.0497 ; p = 0.0299)。

結論與建議：缺血性腦中風病人30天內非計畫性再住院的預測因子有照護過程組合分數與抽菸，90天內非計畫性再住院的預測因子為心臟相關疾病。建議未來可探討不同層級別/嚴重度/年齡層的分組對於缺血性腦中風病人30天內/90天內非計畫性再住院之影響是否有不同程度上的差異，若能進一步與全國的健康資料串聯更佳，便能獲得較完整的病人流向追蹤。

Background: In 2015, the "Hospital Quality Performance Measurement Index System and Implementation Quality Improvement Program" was developed and implemented by the "Center for Quality Management of Healthcare Indicators", which is part of the Joint Commission of Taiwan. Findings from the second stage of this program were used to increase the effectiveness of patient level indicators of stroke. Furthermore, "unplanned readmission" was found to be an important indicator of medical institution quality. Therefore, determining how unplanned readmission rates can be reduced has become an important area of health management research.

Objectives: In this study, we sought to elucidate the characteristics of patients who experienced unplanned readmission for ischemic stroke. We also explored associations between composite process scores (which are used to determine the effectiveness of patient-level indicators) and unplanned 30- and 90-day hospital readmissions in ischemic stroke patients.

Methods: This study investigated a retrospective cohort of ischemic stroke patients who were discharged from the hospital between 2015 and 2016. For this analysis, we used data from the Medicine Integrated Database maintained by the National Taiwan University Hospital Healthcare System, pay-for-performance documents, and case management files of stroke patients. Specifically, we applied multiple logistic regression modeling to investigate how various hospital- and patient-level factors affect unplanned readmission rates for ischemic stroke.

Results: In this study, 59% of the patients were male, and the mean age of all patients was 68.78 years. We identified significant correlations between the two composite scores (Row Sum Score & 70% Standard) describing patient-level process indicators and unplanned readmissions within 30 days (p = 0.0195 ; p = 0.0298). Considering
patient risk factors, smoking and heart-related disease were significantly correlated with unplanned readmission within 30 days and 90 days (p = 0.0497 ; p = 0.0299), respectively.

Conclusions: For ischemic stroke patients, composite scores and smoking were found to be predictors of unplanned readmission within 30 days; heart-related disease was found to be a predictor of unplanned readmission within 90 days. We suggest that future research on ischemic stroke patients investigate different hospital levels, degrees of stroke severity, and patient age groups in order to further elucidate the adverse effects of unplanned readmission within 30 and 90 days. We also suggest that future researchers include data from the National Health Insurance database in their analysis order to obtain results that are as robust and generalizable as possible.

目錄
致謝 i
中文摘要 iii
Abstract iv
目錄 vi
表目錄 viii
圖目錄 x
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 4
第二章 文獻探討 5
第一節 缺血性腦中風之介紹 5
第二節 醫療品質測量指標的應用與論質計酬之簡介 11
第三節 非計畫性再住院定義 22
第四節 相關實證研究 25
第五節 文獻小結 41
第三章 研究方法 42
第一節 研究設計與架構 42
第二節 研究假說 44
第三節 資料來源與研究對象 44
第四節 研究變項操作型定義 46
第五節 資料處理流程 49
第六節 統計分析方法 50
第四章 研究結果 51
第一節 描述性統計 51
第二節 雙變項分析 55
第三節 多變項分析 61
第五章 討論 67
第一節 研究方法討論 67
第二節 研究結果討論 70
第三節 研究限制 76
第六章 結論與建議 77
第一節 結論 77
第二節 建議 78
參考文獻 80

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