目的：本研究旨在探討臺灣心衰竭（Heart Failure, HF）患者的藥物依從性對再入院天數間隔的影響。透過分析患者的藥物依從性（以藥物覆蓋日比例 Proportion of Days Covered, PDC 為指標），比較不同依從性組別在1–30天、31–90天、91–365天及366天以上再入院天數間隔的分布差異，進一步揭示藥物依從性對再入院天數的關鍵影響，為精準的臨床疾病管理和患者長期預後提供實證依據。
方法：本研究採用回溯性世代研究設計，利用2018至2023年高雄某公立醫學中心的次級資料，篩選符合條件的HF新診斷患者（最終納入2,159名患者）。根據ICD9/ICD10診斷碼及ATC藥物代碼，將PDC分為高（≥80%）、中（40%~79%）、低（≤39%）三組，並以再入院天數間隔（1–30天、31–90天、91–365天及366天以上）為依變項。使用Stata 18.0進行描述性統計、卡方檢定及多項式邏輯斯迴歸，分析PDC與再入院天數間隔的關聯，並校正相關變項影響。
結果：本研究納入2,159位HF患者，平均年齡68.77 ± 15.48歲（21–102歲），男性占66.47%。低藥物依從性（PDC≤39%）比例為27.70%，高依從性（PDC ≥ 80%）為64.80%。再入院間隔天數分布中，1–30天占62.90%，31–90天占15.89%，91–365天占13.25%，超過一年未再入院者為7.97%，平均再入院天數103.76±239.14天。多項式邏輯斯迴歸顯示，高依從性（PDC ≥ 80%）患者的再入院機率在31–90天、91–365天和366天以上分別降低至0.20倍、0.25倍和0.30倍（P < 0.001），顯示提升用藥依從性可顯著降低再入院機率。與20–44歲相比，65–84歲及≥85歲患者的短期再入院機率分別提高至1.23倍及1.64倍。此外，共病指數（CCI = 4）患者在中等依從性組中的機率提高至2.18倍（P < 0.001），而LVEF = 41%–49%患者在低依從性組中的機率提高至1.58倍（P < 0.001），顯示高風險患者在用藥依從性上的挑戰較大，年齡、性別及共病指數（CCI）亦對再入院天數具有顯著影響。
結論：本研究證實， HF患者的藥物依從性（PDC）對再入院天數間隔具有顯著影響，高依從性（PDC ≥ 80%）患者的再入院機率降低，且再入院天數間隔延長，顯示提升藥物依從性是降低再入院率的重要策略。研究受限於單一數據來源及回溯性設計，未來建議進行健保資料庫研究，並結合更多依從性評估工具以提高準確性，醫療機構應加強用藥教育與管理，特別是針對高風險患者，以改善預後並提升醫療資源效率。

Objective:This study aimed to investigate the impact of medication adherence on the readmission interval among heart failure (HF) patients in Taiwan. By analyzing medication adherence, measured using the Proportion of Days Covered (PDC) index, the distribution of readmission intervals (1-30 days, 31-90 days, 91-365 days, and more than 366 days) was compared across different adherence groups. This study highlights the critical role of medication adherence in readmission intervals, providing empirical evidence for precise clinical disease management and long-term patient outcomes.
Methods:A retrospective cohort study design was adopted, utilizing secondary data from a public medical center in Kaohsiung, Taiwan, from 2018 to 2023. Newly diagnosed HF patients meeting inclusion criteria were selected, resulting in a final sample of 2,159 patients. PDC was categorized into high (≥80%), medium (40%~79%), and low (≤39%) adherence groups, with readmission intervals (1-30 days, 31-90 days, 91-365 days, and more than 366 days) as the dependent variable. Descriptive statistics, chi-square tests, and multinomial logistic regression were conducted using Stata 18.0 to assess the association between PDC and readmission intervals, adjusting for covariates.
Results:This study included 2,159 HF patients with a mean age of 68.77±15.48 years (range: 21-102 years), of whom 66.47% were male. Low medication adherence (PDC ≤39%) accounted for 27.70%, while high adherence (PDC≥80%) accounted for 64.80%. Readmission intervals were distributed as follows: 1-30 days (62.90%), 31-90 days (15.89%), 91-365 days (13.25%), and more than one year (7.97%), with an average readmission interval of 103.76 ± 239.14 days. Multinomial logistic regression showed that patients with high adherence (PDC ≥ 80%) had significantly lower odds of readmission at different intervals, reducing to 0.20 times at 31–90 days, 0.25 times at 91–365 days, and 0.30 times at over 366 days (P < 0.001). This indicates that improving medication adherence significantly reduces the likelihood of readmission. Compared to those aged 20–44 years, patients aged 65–84 years and ≥85 years had increased short-term readmission odds of 1.23 times and 1.64 times, respectively. Additionally, patients with a CCI of 4 in the moderate adherence group had an increased readmission likelihood of 2.18 times (P < 0.001), while patients with LVEF of 41%–49% in the low adherence group had increased odds of 1.58 times (P < 0.001). These findings highlight the challenges of medication adherence among high-risk patients, with age, gender, and CCI also significantly influencing readmission intervals.
Conclusion:This study confirms that medication adherence (PDC) significantly impacts readmission intervals among HF patients. Patients with high adherence (PDC ≥80%) demonstrated reduced readmission risks and prolonged readmission intervals, emphasizing the importance of improving medication adherence as a key strategy to reduce readmission rates. Limitations include reliance on single-center data and a retrospective design. Future studies should leverage national health insurance databases and incorporate additional adherence assessment tools to enhance accuracy. Healthcare institutions should strengthen medication education and management, particularly for high-risk patients, to improve outcomes and optimize healthcare resource efficiency.

論文審定書 i
致謝 ii
摘要 iii
Abstract v
目錄 vii
圖次 x
表次 xi
第一章 緒論 1
第一節 研究背景與動機 1
第二節 問題陳述與研究目的 3
一、 研究問題 3
二、 研究重要性 4
第二章 文獻探討 5
第一節 HF 5
一、 HF疾病 5
二、 HF用藥的重要性 8
三、 HF現況及相關研究 9
第二節 藥物依從性 11
一、 藥物依從性定義 11
二、 藥物依從性評估方式 12
三、 影響藥物依從性相關研究 15
第三節 HF不同再入院時間間隔相關研究 20
一、 HF不同時間間隔再入院狀況 20
二、 藥物依從性與再入院天數 24
第四節 文獻小節 25
第三章 研究方法 27
第一節 研究設計與研究架構 27
第二節 研究對象與資料來源 28
一、 收案條件及資料庫資料取得方法 28
二、 樣本篩選步驟 28
三、 資料定義 31
第三節 研究假設 37
第四節 研究變項與操作型定義 38
一、 自變項 38
二、 依變項 38
三、 控制變項 38
第五節 資料處理與分析 41
一、 描述性統計 41
二、 推論性統計 41
第四章 資料分析結果 43
第一節 研究對象基本特性 43
一、 人口學資料 43
二、 臨床特性 45
第二節 連續變項比較分析結果 47
一、 第一次出院至再入院天數與人口學特性之檢定結果 47
二、 第一次出院至再入院天數與臨床特性之檢定結果 49
第三節 類別變項比較分析結果 50
一、 性別與再入院間隔天數卡方檢定結果 50
二、 年齡與再入院間隔天數卡方檢定結果 51
三、 教育程度與再入院間隔天數卡方檢定結果 52
四、 婚姻狀況與再入院間隔天數卡方檢定結果 53
五、 子女數與再入院間隔天數卡方檢定結果 54
六、 CCI與再入院間隔天數卡方檢定結果 55
七、 LVEF與再入院間隔天數卡方檢定結果 56
八、 PDC與再入院間隔天數卡方檢定結果 57
第四節 多項式邏輯斯迴歸分析 58
一、 再入院天數與各項影響因素的多項式邏輯斯迴歸分析結果 58
二、 PDC與各項影響因素的多項式邏輯斯迴歸結果 62
三、 PDC 與人口學因素交互作用對再入院間隔天數多項式邏輯斯迴歸分析 64
四、 PDC 與臨床因素交互作用對再入院間隔天數多項式邏輯斯迴歸分析 66
第五章 討論與建議 68
第一節 研究假設驗證 68
第二節 研究討論 70
第三節 實務涵義 76
第四節 研究限制 78
第五節 研究建議 79
參考文獻 82
附件 92
附錄一：人體研究計畫同意函 92

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