臺灣博碩士論文加值系統

研究背景
隨著台灣的人口老化，慢性病日益盛行，台灣慢性腎臟病的人數亦逐年增加，跟其他國家比較，台灣透析人口不論是盛行率或是發生率都是排名世界第一。透析發生率在台灣不但很高，亦存在區域分佈的差異，但就目前的文獻結果，只知道透析發生率各地區有別，仍不清楚受哪些因素影響。

研究目的
本研究目的為瞭解台灣各地區末期腎臟病發生率和不同環境因子的聚集情形，並且透過空間回歸模型評估影響因子。

研究方法
本研究為cross-sectional study，運用2002-2011年之全民健保資料庫，針對慢性腎臟病族群，納入2004/01/01至2011/12/31之間首次發生ESRD的患者(重大傷病代碼585)，將ESRD重大傷病申請日定義為指標日期，並以鄉鎮為單位定義居住地，排除條件包含：居住地無法定義個案、生日性別無法確定者、非台灣本島居民、指標日前一年被診斷惡性腫瘤者、指標日期在2004/01/01以前或2011/12/31以後者、年齡小於20歲者。
針對研究族群，我們首先計算各鄉鎮每年度之ESRD發生率，並分析糖尿病和高血壓之共病症比例，計算可能引起腎功能惡化的藥品如NSAIDs、aminoglycosides和contrast medias使用之平均DDD。另外從各縣市政府開放資料平台收集各縣市之社會環境變項: 人口密度、老年人口、教育程度、原住民比例、醫療資源、失業率、平均收入和空氣汙染。
接著，運用空間相關性局部指標(Lisa Indicators of Spatial Association, LISA)分析ESRD發生率與研究用藥之空間分布和聚集情況，並以空間回歸模型spatial Durbin Panel Model (SDPM)探討影響ESRD發生率之相關因子。


研究結果
本研究共納入73995位研究對象，平均年齡為63.77歲，男性占50.9%。在共病症部分，有90.6%的人患有高血壓，而有60.4%的病人患有糖尿病。在藥物使用的部分，有74.5%的病人在ESRD發生前一年內有暴露NSAIDs，而有17.4%的病人在ESRD前一年內有暴露aminoglycosides，另外contrast media則是沒有任何病人有暴露的狀況。
LISA結果指出，ESRD發生率以南部和東部為明顯的熱點地區，而NSAIDs和aminoglycosides的使用熱點集中在北部和東部，南部大多呈現冷點區域，尤其是aminoglycosides。後續的空間迴歸結果指出，在同時考慮環境因子、病人狀況和疾病的情況下，社會環境因子如老年人口比例、原住民比例、醫療資源、失業率和ESRD發生率有顯著正向關係，而教育程度則呈現顯著負向關係；病人本身若是男性(P〈0.001)或有高血壓或糖尿病(P〈0.001)的共病症，或者是ESRD發生前90天內有接觸到高劑量NSAIDs (P=0.011)和aminoglycosides (P=0.009)對於ESRD的發生風險呈現正相關，而在181-365天內接觸aminoglycoside和ESRD發生率則呈現負相關(p=0.009)。

結論
本研究發現台灣ESRD發生率確實具有空間聚集性，高發生率的地區主要集中在高雄市、臺南市和屏東縣與少部分台東地區。其次，空間迴歸模型指出，社會環境因子如老年人口、原住民比例、醫療資源、失業率、教育程度，病人本身因素如性別、糖尿病或高血壓等共病症，和ESRD發生前90天內用藥如NSAIDs、aminoglycosides皆為影響ESRD發生率具有空間分布差異的顯著相關因子。
偏鄉地區醫療人力不足，導致病人疾病無法獲得妥善控制，因此，建議主管機關能增加偏鄉醫療人力，減緩當地居民疾病的惡化，並透過講座或會議宣導，減少不適當高劑量的NSAIDs和aminoglycosides暴露機率，才能有效減少ESRD發生的風險。

Previous foreign studies showed that many risk factors may cause kidney injury, such as gender, aging, medications and disease. Besides these common cause, environmental factors, socioeconomic factors and race are also possible factors. We conducted a cross-sectional study using the Taiwan’s National Health Insurance Research Database (NHIRD) from 2002-2004, involving patients over 20 years old who were diagnosed with ESRD. Comorbidities and co-medications were observed within 1 year before first ESRD diagnosis. Study outcomes were to confirm the incidence rate of ESRD in each region, and to evaluate which factor would influence ESRD incidence rate. Local Indicators of Spatial Association (LISA) was applied to detect the spatial clusters of ESRD incidence rate, and then we used spatial regression model to identify the factors related to ESRD incidence. There were totally 73995 patients in our study, with a mean age of 63.77 years and 50.9% males. LISA analysis showed that high ESRD incidence rate was clustered in southern Taiwan. In social factors, results from spatial regression model found elderly population, aboriginal proportion, medical resources and unemployment rate had positive correlation with ESRD incidence (P〈0.001), but education level had negative correlation (P=0.025). In baseline characteristics, male proportion, diabetes and hypertension were positively associated with ESRD incidence (P〈0.001). As for medication use, the current users of NSAIDs (P=0.011) and aminoglycosides (P=0.009) might increase the risk of ESRD. Our findings suggested health providers to increase medical personnel proportion and improve the utilization of these medication in rural area.

Chapter 1 研究背景 1
Chapter 2 文獻回顧 2
2.1 慢性腎臟病簡介 2
2.1.1 流行病學 2
2.1.2 健保支出 2
2.2 腎功能損傷相關危險因子 4
2.2.1 基因遺傳和腎病家族史 4
2.2.2 性別 4
2.2.3 年齡 4
2.2.4 抽菸 5
2.2.5 腎毒性藥品 5
2.2.6 疾病 8
2.3 與末期腎臟病發生率空間分布差異之相關因子 9
2.3.1 環境因子 (Environment factors) 9
2.3.2 社經地位 (Social-Economic status) 11
2.3.3 醫療資源 (Health source) 11
2.3.4 種族差異 (Racial factor) 12
2.3.5 人口密度和都市化程度 12
2.4 空間分析方法與應用 14
2.4.1 空間分析於流行病學之應用 14
2.4.2 概念 14
2.4.3 鄰近關係 14
2.4.4 空間相關性局部指標(Lisa Indicators of Spatial Association, LISA) 48 15
2.4.5 空間迴歸模型 (Spatial regression model) 16
2.5 總結 17
Chapter 3 研究背景 18
3.1 研究目的 18
3.2 研究之重要性 18
Chapter 4 研究方法 19
4.1 研究設計 19
4.1.1 研究類型 19
4.1.2 研究材料與資料來源 19
4.1.3 研究對象 20
4.1.4 觀察時間及觀察內容 21
4.1.5 研究流程 21
4.2 居住地判別流程 22
4.3 研究變項與操作型定義 24
4.3.1 研究族群基本資料定義 24
4.3.2 各鄉鎮藥品耗用量定義 25
4.3.3 各鄉鎮進展為末期腎臟病之發生率 25
4.3.4 排除條件之操作定義 26
4.4 社會環境因子解釋及其操作定義 26
4.5 統計方法 29
4.6 空間分析方法 30
Chapter 5 研究結果 33
5.1 居住判別流程 33
5.2 研究對象納入與排除 35
5.3 人口學特性 36
5.4 描述性空間分析與空間相關性局部指標分析結果 38
5.4.1 ESRD各鄉鎮發生率 38
5.4.2 診斷ESRD前一年內被開立腎毒性藥品的情形 40
5.4.3 各變數間相關性 48
5.5 空間迴歸模型分析結果 50
Chapter 6 研究討論 54
6.1 研究人口特性 54
6.2 ESRD發生率分布差異 55
6.3 空間迴歸模型分析 56
6.4 環境社會因子與ESRD發生率的相關性 57
6.5 病人因素與ESRD發生率的相關性 59
6.6 藥品使用與ESRD發生率相關性 60
6.7 研究限制 63
6.7.1 OTC藥品的影響 63
6.7.2 環境社會因子資料不完整 64
6.7.3 研究族群過少 65
6.7.4 研究外推性 66
Chapter 7 結論與建議 68
Chapter 8 未來研究方向 69
Chapter 9 臨床藥事服務 – 8B、12C病房臨床藥師 70
9.1 服務緣起 70
9.2 服務內容 70
9.3 服務成果 71
9.3.1 8B–一般外科病房 71
9.3.2 12C–一般內科病房 72
9.4 服務反思 73
9.4.1 病房照護 73
9.4.2 生物製劑事前審查 74
9.5 服務感想 75
Chapter 10 附錄 82
10.1 2004-2011年ESRD發生率冷熱點之鄉鎮分布 82
10.2 2004-2011年各變項冷熱點之鄉鎮分布 87
10.3 ESRD發生率為0的鄉鎮市區 90
10.4 居住地校正方法 validation 92

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