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研究生:方淑雲
研究生(外文):Shu-Yun Fang
論文名稱:醫院急診室壅塞與中風併發肺炎病患死亡率、入住加護病房及醫療花費之相關性
論文名稱(外文):The Association between Emergency Department Overcrowding and Mortality Rate, Intensive Care Unit Admission, Medical Expenses among Stroke Patients Complicated with Pneumonia in Taiwan
指導教授:楊振昌楊振昌引用關係
指導教授(外文):Chen-Chang Yang
學位類別:碩士
校院名稱:國立陽明大學
系所名稱:公共衛生研究所
學門:醫藥衛生學門
學類:公共衛生學類
論文種類:學術論文
論文出版年:2010
畢業學年度:98
語文別:中文
論文頁數:120
中文關鍵詞:急診壅塞加護病房醫療花費肺炎中風
外文關鍵詞:emergency department overcrowdingintensive care unitmedical expensepneumoniastroke
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研究背景:
急診壅塞自1980年代起即是被關注的議題。近年來,急診壅塞對醫療照護品質的影響更日益受到重視,但急診壅塞對於慢性病併發急性疾病之影響尚未有文章提出探討。本研究以2005至2007年健保台北分局轄區醫院照護之中風併發肺炎急診病患,瞭解急診壅塞對其醫療照護之影響。
研究方法:
以健保台北分局轄區17家醫院中風併肺炎急診就醫(就醫日期訂為index date)病患為分析對象,以病例對照研究方法,依病患年齡、性別進行1比2配對;index date之後30日內死亡的個案為病例組,index date之後存活一年以上為對照組,探討急診壅塞與index date之後30日內死亡風險之相關性。本研究之次要結果變項為個案組與對照組入住加護病房之比率及其相關因素、及急診後平均之個人醫療點數。
在index date之後30日內死亡及入住加護病房比率部份,除了以描述性資料及卡方檢定進行分析外,並以條件式邏輯斯迴歸統計(Conditional logistic regression),計算各變項的單變項及多變項勝算比(odds ratio)。急診後平均個人醫療點數部份,除了基本資料之描述外,並以變異數F檢定進行單變項分析,及以廣義線性模式(generalized linear regression)進行多變項分析。
結果:
本研究之主要發現如下:
一、 急診壅塞程度與中風併發肺炎急診病患之死亡風險雖無顯著之統計相關,但呈劑量效應關係(dose-response relationship)
經控制病患特質(如併發偏癱程度、重大傷病、低收入戶)、醫院特質(如層級別及住院佔床率)、時間因素(如季節及不同急診就醫年份)、入住加護病房、抗生素使用種類、降血脂用藥使用、前一年住院次數等因素後,在全部研究個案部份,壅塞程度第2級、第3級、第4級、及第5級者,分別較第1級高出4% (95% CI 0.77~1.40,p= 0.80)、11% (95% CI 0.83~1.47,p= 0.50)、16% (95% CI 0.87~1.56,p= 0.31)、32% (95% CI 0.99~1.76,p= 0.06),呈線性相關。
二、 病患特質為影響死亡率之主要因素
急診檢傷分類為第一級之患者,較分類為第三級之患者,有較高的死亡風險(全部研究個案為4.79倍;無併發偏癱者為4.19倍、併發輕度偏癱者為5.49倍、併發中度偏癱者為5.39倍、併發重度偏癱者為5.51倍;於醫學中心就醫之病患為4.83倍,區域醫院為5.32倍)。前一年住院3次以上者死亡的風險高於未曾住院者,且達顯著性差異(全部研究個案為2.03倍;無併發偏癱者為2.23倍、併發重度偏癱者為1.95倍;於醫學中心就醫之病患為2.00倍,區域醫院為2.11倍)。
三、 降血脂用藥可降低肺炎死亡率,但對入住加護病房無明顯的影響
急診病患曾經使用stains者,與降低病患死亡風險有關[全部研究個案之風險降低27% (95% CI 0.57~0.92,p= 0.01);併發重度偏癱者風險降低44% (95% CI 0.36~0.85,p= 0.01);醫學中心就醫者風險降低35% (95% CI 0.46~0.92,p= 0.02)]。
但入住加護病房者較未入住加護病房者,曾經使用stains藥物之比率並無明顯差異(OR 1.32,95% CI 0.90~1.96,p= 0.16)。
四、 病患危急及疾病嚴重度是影響病患入住加護病房之因素
經校正其他變項後,檢傷分類第1級者入住加護病房之風險為第3級者的10.31倍;重大傷病者較無重大傷病者為1.65倍;抗生素使用種類為第一線+第二線以上者為第一線者之2.41倍,顯示情況危急及疾病嚴重度是病患入住加護的主要因素。急診壅塞程度或住院佔床率則與入住加護病房比率呈負相關。
五、 醫療費用以疾病嚴重度較高或治療成本較高者為多
在對照組病患中,檢傷分類為第1級者較檢傷分類為第3級者之醫療點數使用多155%;有重大傷病者較無重大傷病者之醫療點數使用多131%;有入住加護病房者較未入住者之醫療使用多103%。以上結果顯示,病患之疾病嚴重度與中風併肺炎病患至急診就醫後之醫療資源使用呈正相關。
結論:
醫院急診壅塞可能影響病患之死亡率。本研究雖僅發現兩者間具接近統計顯著之相關性,但有劑量效應關係。此外影響中風併肺炎病患之死亡率,以病患特質為主要因素,醫院特質之影響則不大,顯示弱勢病患照護之公平性並未受到影響。本研究亦發現降血脂用藥statins可能會降低肺炎之死亡率,但對入住加護病房則無明顯之保護作用。建議未來能繼續以不同疾病別來瞭解急診壅塞對病患急診醫療品質之影響。

Objectives: Emergency department (ED) overcrowding has become an issue of concern since late 1980s. Recently, the impacts of ED overcrowding on the quality of healthcare are under even more scrutiny. However no study has ever evaluated the effects of ED overcrowding on the management of acute illnesses that develop among patients with chronic disease. We studied all patients who visited the ED of hospitals in the Taipei Sector of the Taiwan National Health Insurance Bureau due to concomitant stroke and pneumonia between 2005 and 2007 to better understand the impacts of ED overcrowding on the healthcare of such patients.

Methods: The study was a case-control study that included all patients who visited the ED of 17 hospitals in the Taipei Sector of the Taiwan National Health Insurance Bureau due to concomitant stroke and pneumonia between 2005 and 2007. Patients who died within 30 days after the ED visit (index date) were defined as cases, while those patients who survived more than 1 year after the index date were defined as controls. Cases and controls were then 1:2 matched on age and sex to study the association between ED overcrowding and death within 30 days after the index date. The secondary study aims of this study were the probability of admission to intensive care unit (ICU) and its related factors, and the medical expenses incurred from the ED visit.
In the analysis of death within 30 days after the index date or the probability of ICU admission, we first employed descriptive analysis and chi-square test. We then used conditional logistic regression analysis to estimate univariate and multivariate odds ratio of all variables. As for the analysis of average medical expenses per capita that incurred from the ED visit, we employed descriptive analysis, F test for uniavariate analysis, and generalized lineqar regression model for multivariate analysis.

Results: The main findings of this study were as follows:
(1). There was no statistical association between ED overcrowding and the risk of death among stroke patients complicated with pneumonia; however there was a dose-response relationship between the magnitude of ED overcrowding and the risk of death.
After controlling for patient’s characteristics (e.g. complication of limb paralysis, the presence of catastrophic illnesses, low household income), hospital’s characteristics (accreditated level of the hospital, and occupancy rate), time (season and calendar year of ED visit), ICU admission, classification of antibiotics, use of lipid-lowering drugs, and hospitalization in the prior 1 year, the odds ratio of death within 30 days after the index date for 2nd, 3rd, 4th, and 5th quintiles of ED overcrowding was 1.04, 95% CI 0.77~1.40,p= 0.80), 1.11 (95% CI 0.83~1.47,p= 0.50), 1.16 (95% CI 0.87~1.56,p= 0.31), and 1.32 (95% CI 0.99~1.76,p= 0.06) respectively, as compared with the 1st quintile, and there was a dose-response relationship
(2).Patient’s characteristics were the major risk factors of mortality.
Patients classified as ED triage level 1 had higher mortality rate as compared with patients classified as ED triage level 3 (OR 4.79 for all study patients; OR 4.19 for patients without paralys, OR 5.49 for patients with mild paralysis, OR 5.39 for patients with moderate paralysis, OR 5.51 for patients with severe paralysis; OR 4.83 for patients visiting medical centers, and OR 5.32 for patients visiting regional hospitals). Moreover, patients who had more than 3 hospitalizations in the previous year before the index date had higher mortality rate as compared to patients without prior hospitalization (OR 2.03 for all study patients; OR 2.23 for patients without paralysis, OR 1.95 for patients with severe paralysis; OR 2.00 for patients visiting medical centers, and OR 2.11 for patients visiting regional hospitals).

(3). Lipid-lowering drugs were associated with a lower risk of mortality, but were not associated with the risk of ICU admission.
Patients who ever used statins were associated with a lower risk of mortality (OR 0.73, 95% CI 0.57~0.92, p= 0.01 for all study patients; OR 0.56, 95 % CI 0.36~0.85,p= 0.01 for patients with severe paralysis; and OR 0.65, 95% CI 0.46~0.92,p< 0.01 for patients visiting medical centers). The use of statins however was not associated with the risk of ICU admission (OR 0.68, 95% CI 0.90~1.96,p= 0.16).
(4). Patient’s acuity and severity of patient’s illness were the risk factors of ICU admission.
After controlling for confounding variables, patients classified as ED Trige level 1 were 10.31 times more likely to be hospitalized to ICU, as compared with patients classified as ED Trige level 1. Moreover, patients with catastrophic illness were 1.65 times more likely to be hospitalized to ICU, and patients who received both 1st and 2nd generation antibiotios were 2.14 times more likely to have ICU admission, as compared with patients receiving 1st generation antibiotics. All of the aforementioned findings suggested that patient’s acuity and severity of patient’s illness were the risk factors of ICU admission. On the contrary, ED overcrowding and hospital’s occupancy rate were inversely associated with the risk of ICU admission.

(5). Severity of patient’s illness and diseases requiring higher cost of treatment were associated with more medical expenses.
Among the controls, patients classified as ED trige level 1 used 2.55 times the medical expenses than patients classified as ED triage level 3. Similarily, the patients who had catastrophic illness and patients with ICU admission used 2.31 times and 2.03 times the medical expenses than patients without catastrophic illness and patients without ICU admission, respectively. The above-noted findings showed that severity of patient’s illness was positively associated with the medical expenses after ED visit for pneumonia among stroke patients.

Conclusions: ED overcrowding may affect the mortality of patients. In this study, we found a borderline statistical significance and a dose-response relationship between ED overcrowding and mortality among patients with concomitant stroke and pneumonia. Moreover, the mortality of patients with both stroke and pneumonia was primarily associated with patient’s characteristics rather than the hospital’s characteristics, which indicated that the medial rights of vulnearable patients were not jeopardized. We also found that the use of statins might be associated with a lower risk of pneumonia related mortality, but did not protective against ICU admission. The study of the impacts of ED overcrowding on the quality of care among ED patients by using other diseases is warranted in the future.

目錄
目錄--------------------------------------------------------I
論文電子檔著作權授權書-------------------------------------
論文審定同意書---------------------------------------------
誌謝-------------------------------------------------------VI
中文摘要--------------------------------------------------VII
英文摘要---------------------------------------------------XI
第一章 緒論---------------------------------------------1~6
第一節 研究背景--------------------------------------1~4
第二節 研究目的--------------------------------------4~6
第二章 文獻探討----------------------------------------7~32
第一節 中風及肺炎流行病學---------------------------7~13
第二節 台灣急診醫療使用現況------------------------14~16
第三節 急診壅塞的因素及造成影響--------------------17~24
第四節 急診壅塞定義及量化指標----------------------25~32
第三章 研究方法與材料---------------------------------33~41
第一節 資料來源及研究對象--------------------------33~35
第二節 研究架構與研究變項--------------------------35~38
第三節 統計分析------------------------------------38~41
第四章 研究結果---------------------------------------42~69
第一節 急診後30日死亡率之分析結果-----------------42~56
第二節 入住加護病房比率之分析結果------------------57~63
第三節 急診後醫療點數使用之分析結果----------------63~69
第五章 討論及建議-------------------------------------70~87
第一節 討論----------------------------------------70~81
第二節 研究優點及限制------------------------------82~84
第三節 結論與建議----------------------------------84~87
參考文獻------------------------------------------------88~95
附錄--------------------------------------------------120~120









表目錄---------------------------------------------------96~105
表2-1.2007年肺炎急診發生率-------------------------------96~96
表2-2.2005-2007年台灣健保急診醫療依疾病分類每十萬人口就診率排行-----------------------------------------------------------97~97
表2-3.全國及肺炎疾病急診就醫診次及醫療點數統計-------------98~98
表2-4.健保台北分局及其他分局之急診醫療供給與需求面比較-----99~99
表2-5.急診壅塞造成醫療品質之影響-------------------------100~101
表3-1.各變項之操作型定義---------------------------------102~104
表3-2.研究變項之共線性診斷-------------------------------105~105
表4-1.醫院急診室中風併肺炎急診病患急診後30日內(控制組)與存活一
年以上(對照組)基本資料描述-------------------------------106~106
表4-2.醫院急診室中風併肺炎病患急診後30日內發生死亡風險粗勝算比
及校正後勝算比-------------------------------------------107~107
表4-3.醫院急診室中風併肺炎病患無併發偏癱 、併發中度及重度偏癱急
診後30日內發生死亡風險校正後勝算比----------------------108~108
表4-4.醫院急診室中風併肺炎病患於醫學中心、區域醫院急診後30日內
發生死亡風險校正後勝算比---------------------------------109~109
表4-5.醫院急診室中風併肺炎病患入住加護病房控制組與對照組基本資料描述----------------------------------------------------110~110
表4-6.醫院急診室中風併肺炎病患入住加護病房因素粗勝算比及校正後
勝算比--------------------------------------------------111~111
表4-7.醫院急診室中風併肺炎病患急診後30日內(控制組)與存活一年以
上(對照組)急診後醫療點數基本資料描述--------------------112~112
表4-8.醫院急診室中風併肺炎病患急診後30日內發生死亡風險控制危險
因子後之急診後醫療點數----------------------------------113~113
表4-9.醫院急診室中風併肺炎病患存活一年以上控制危險因子後之急診
後醫療點數----------------------------------------------114~114
表附錄全民健康保險醫療常用第一線抗微生物製劑品名表------120~120









圖目錄-------------------------------------------------115~119
圖1.研究假設-------------------------------------------115~115
圖2.醫院急診壅塞之概念模式架構-------------------------116~116
圖3-1.研究架構-----------------------------------------117~117
圖3-2.資料處理流程(醫院急診案件篩選急診肺炎併發中風病患)
--------------------------------------------------------118~118
圖3-3.資料處理流程(住院每日床率案件)--------------------119~119

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