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姓名 呂春輝(Chun-Hui Lu) 電子郵件信箱 lue0203@yahoo.com.tw
畢業系所 企業管理學系研究所(Department of Business Management)
畢業學位 博士(Ph.D.) 畢業時期 108學年第2學期
論文名稱(中) 以藥師為基礎之智慧臨床決策支援系統如何影響慢性病患者之用藥安全─以慢性腎臟病使用Metformin為例
論文名稱(英) How a pharmacist-based intelligent clinical decision support system affects the safety of medication for patients with chronic diseases-Taking Metformin for chronic kidney disease as an example
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    摘要(中) 研究目的:慢性腎臟病是第2型糖尿病患者的常見合併症,且慢性腎臟病及糖尿病是台灣醫療資源花費最多的疾病,這類患者可能存在許多用藥安全問題。現今科技進步下,臨床決策支援系統(CDSSs)更能快速整合特定臨床知識、病人資訊及其他健康資訊,提供臨床決策運用。本研究以慢性腎臟病使用metformin為案例,依循理性決策的步驟,開發以藥師為基礎之智慧CDSSs,來保障慢性病患者用藥安全。
    研究方法:首先在醫師與藥師信任基礎下,合作共同制定醫院藥物治療指引,於新系統介入前對藥師及醫師訪談,並依指引分析2年醫院慢性腎臟病病患使用metformin資料,之後於藥師調劑階段,開發新智慧CDSSs介入來建議處方決策,並自動以簡訊通知醫師。新系統介入後,進行訪談及分析就醫資料來評估成效。
    研究結果:分析CDSSs介入前發現,門診及住院患者確實存在未依指引檢測腎功能及調整藥物劑量問題;另訪談結果發現,藥師及醫師存在對藥物治療指引不熟悉及醫院相關資訊取得較無效率等問題,另於介入後發現藥師處理用藥問題的不確定性下降、效率提升及時間大幅縮短;研究也發現醫師對於藥師的專業建議介入前後,大都是願意接受的,另比較介入前後資料分析發現住院患者腎功能檢測較介入前有顯著改善,其他變項可能因為觀察時間不足較無明顯差異。
    研究結論:本研究發展以智慧CDSSs是依循理性決策的步驟建置,可大幅提升藥師及醫師執行臨床藥物治療的決策的效率,模組化設計方便擴大應用與管理,完整有效率的將患者檢驗與藥物等資料快速整合,對於各類慢性病日趨複雜的藥物治療決策,提供新的思維來維護病患用藥安全。
    摘要(英) Objectives: Chronic kidney disease is a common comorbidity of patients with type 2 diabetes, and chronic kidney disease and diabetes are the most expensive diseases of medical resources in Taiwan. These patients may have many drug-related problems. Clinical Decision Support Systems (CDSSs) can quickly integrate specific clinical knowledge, patient information and other health information to assist clinical decision-making. This research takes the use of metformin for chronic kidney disease as an example, and follows the steps of rational decision-making to design intelligent pharmacist-based CDSSs to ensure the safety of medication for patients with chronic diseases.
    Methods: First, doctors and pharmacists cooperate to formulate hospital medication guidelines based on the trust relationship. Interviewed pharmacists and physicians before the intervention of the new system, and analyzed the data on the use of metformin by patients with chronic kidney disease in the hospital for 2 years according to the drug treatment guidelines. In the stage of dispensing prescriptions by pharmacists, intelligent CDSSs are developed to suggest prescription decisions and automatically notify physicians via SMS. After the intervention of the new system, questionnaire interviews and data analysis were used to evaluate the effectiveness of CDSSs.
    Results: Before the intervention of CDSSs, some outpatients and inpatients had problems with eGFR testing and drug dosage adjustments that did not follow the guidelines. The results of the interview found that some pharmacists and physicians were not familiar with the drug treatment guidelines, and found that the decision-making information provided by the hospital is less convenient to obtain. After the intervention, it was found that the uncertainty of the pharmacist's handling of the medication problem was reduced, the efficiency was improved, and the time was greatly shortened. The research also found that physicians are always willing to accept the professional advice of pharmacists before and after intervention.Comparing the data analysis before and after intervention, it is found that the detection of renal function in inpatients has significantly improved compared with before intervention. Other variables may have no significant difference due to insufficient observation time.
    Conclusions: This research develops intelligent CDSSs, which can greatly improve the efficiency of pharmacists and physicians in implementing clinical drug treatment decisions. The modular design is convenient for application and maintenance, and complete and efficient integration of inspection and drug information. For the increasingly complex drug treatment decisions of various chronic diseases, provide new thinking to maintain the safety of patients' medication.
    關鍵字(中)
  • 藥師為基礎智慧臨床決策支援系統
  • 用藥安全
  • metformin
  • 慢性腎臟病
  • 關鍵字(英)
  • safety of medication
  • chronic kidney disease
  • pharmacist-based intelligent clinical decision support system
  • metformin
  • 論文目次 目錄
    論文審定書…………………………………………………………………………… i
    誌謝………………………………………………………………………………........ii
    中文摘要………………………………………………………….…………………. iii
    英文摘要………………………………………..………………………………….. iv
    第一章 緒論 1
    第一節 研究緣起 1
    第二節 研究背景與動機 1
    第三節 研究目的及問題 4
    第二章 文獻探討 6
    第一節 CDSSs的角色對決策的影響 6
    第二節 慢性腎臟病、糖尿病用藥及醫療資源相關議題 7
    第三節 使用CDSSs於慢性腎臟病患用藥相關研究 10
    第三章 理論與架構 16
    第一節 智慧臨床決策支援系統 16
    第二節 藥師於臨床決策支援系統之角色 19
    第三節 藥師為基礎之智慧臨床決策支援系統在慢性腎病患者、抗糖尿病藥物Metformin治療相關議題之研究與研究假設 21
    第四節 研究架構 23
    第四章 研究設計與方法 24
    第一節 研究流程 24
    第二節 研究設計 26
    第三節 研究對象 32
    1. CKD檢查及用藥資料來源 32
    2. 資料收集、變項操作型定義與測量工具 33
    第四節 以藥師為基礎之CDSSs使用者訪問 37
    第五節 研究假設 37
    第六節 分析方法 37
    第五章 研究結果 39
    第一節 eGFR檢驗及藥物劑量合理性分析結果 39
    1. CDSSs介入前住院資料分析結果 39
    2. CDSSs介入前門診資料分析結果 47
    3. CDSSs介入後與介入前住院資料分析比較結果 56
    4. CDSSs介入後與介入前門診資料分析結果 64
    第二節 CDSSs介入前後各訪問結果 77
    第三節 CDSSs介入前後訪問結果差異說明 93
    第六章 討論 96
    第一節 研究結果討論 96
    第二節 研究限制 101
    第七章 結論與建議 103
    第一節 結論 103
    第二節 建議 103
    參考文獻 105

    圖次
    圖3-1:知識庫基礎的和非知識庫基礎的CDSSs中的關鍵交互圖 17
    圖3-2:傳統臨床決策支援系統運作示意圖。 21
    圖3-3:藥師為基礎之智慧臨床決策支援系統運作示意圖。 21
    圖3-3:研究架構圖。 23
    圖4-1:研究流程圖 25
    圖4-2:門急診及住院之藥師為基礎智慧CDSSs進入畫面。 29
    圖4-3:開立之metformin處方後,電腦跨系統自動檢查醫療各系統內,是否最近六個月內有檢查,於藥師調劑畫面呈現。 30
    圖4-4:模組化方式建立最新治療指引對應的適當藥物治療劑量。 30
    圖4-5:電腦智慧判斷eGFR值及對應合理藥物劑量後,自動顯示須調整劑量,並主動建議簡訊通知醫師。 31
    圖4-6:除自動依常用片語通知外,亦可經藥師修正建議內容後,主動簡訊通知醫師。 31

    表次
    表2 1:電腦化CDSSs及人工CDSSs分類整理文獻研究要點及成果 12
    表3-1:依據慢性腎臟病分期建議預估檢驗eGFR 頻率 22
    表4-1:電腦檢核各分級及藥物建議最大每日劑量 26
    表4-2:本研究metformin門診及住院用藥種類之基本資料 27
    表4-3:第十版國際疾病分類標準(ICD-10-CM) 慢性腎臟病疾病分類碼 33
    表4-4:研究對象基本資料表 35
    表4-5:資料篩選及剔除重複資料定義 35
    表4-6:門診及住院資料處理步驟 36
    表4-7:本研究統計分析方法 38
    表5-1-1:住院慢性腎臟病使用metformin病人(人次)基本資料 39
    表5-1-2:住院慢性腎臟病分級比例 40
    表5-1-3:住院就診科別 40
    表5-1-4:住院開立Metformin前半年內之eGFR檢測紀錄結果 41
    表5-1-5:住院開立Metformin前半年內有eGFR檢測紀錄病患年齡 42
    表5-1-6:住院病人慢性腎臟病分期比例 42
    表5-1-7:住院就診科別比例 43
    表5-1-8:住院開立Metformin前半年內無eGFR檢測紀錄病患年齡 44
    表5-1-9:住院病人慢性腎臟病分期比例及就診科別 44
    表5-1-10:住院就診科別比例 44
    表5-1-11:住院Metformin用藥治療指引遵循度分析結果 46
    表5-1-12:住院慢性腎臟病分期比例 46
    表5-1-13:住院就診科別比例 46
    表5-2-1:門診慢性腎臟病開立Metformin病人基本資料 47
    表5-2-2:門診慢性腎臟病分期比例 48
    表5-2-3:門診就診科別比例 48
    表5-2-4:門診開立Metformin前半年內之eGFR檢測紀錄結果 49
    表5-2-5:門診開立Metformin前半年內有eGFR檢測紀錄 50
    表5-2-6:病人慢性腎臟病分期比例 50
    表5-2-7:門診就診科別比例 51
    表5-2-8:門診立Metformin前半年內沒有eGFR檢測紀錄 52
    表5-2-9:門診病人慢性腎臟病分期比例 52
    表5-2-10:門診就診科別比例 53
    表5-2-11:門診Metformin用藥治療指引遵循度 53
    表5-2-12:門診病人慢性腎臟病分期比例 55
    表5-2-13:門診就診科別比例 55
    表5-3-1:住院病人慢性腎臟病分期比例 56
    表5-3-2:住院就診科別比例 56
    表5-3-3:住院開立Metformin前半年內之eGFR檢測紀錄 57
    表5-3-4:病人慢性腎臟病分期比例 57
    表5-3-5:就診科別比例 57
    表5-3-6:住院Metformin用藥治療指引遵循度 57
    表5-3-7:病人慢性腎臟病分期比例 58
    表5-3-8:就診科別比例 58
    表5-3-9:開立Metformin前半年內之eGFR檢測紀錄 59
    表5-3-10:病人慢性腎臟病分期比例 59
    表5-3-11:就診科別比例 59
    表5-3-12:Metformin用藥治療指引遵循度 59
    表5-3-13:病人慢性腎臟病分期比例 60
    表5-3-14:就診科別比例 60
    表5-3-15:開立Metformin前半年內之eGFR檢測紀錄 61
    表5-3-16:病人慢性腎臟病分期比例 61
    表5-3-17:就診科別比例 61
    表5-3-18:Metformin用藥治療指引遵循度 61
    表5-3-19:病人慢性腎臟病分期比例 62
    表5-3-20:就診科別比例 62
    表5-4-1:門診病人慢性腎臟病分期比例 64
    表5-4-2:門診就診科別比例 64
    表5-4-3:開立Metformin前半年內之eGFR檢測紀錄 65
    表5-4-4:門診病人慢性腎臟病分期比例 66
    表5-4-5:門診就診科別比例 66
    表5-4-6:門診Metformin用藥治療指引遵循度 67
    表5-4-7:門診病人慢性腎臟病分期比例 67
    表5-4-8:門診就診科別比例 67
    表5-4-9:病人慢性腎臟病分期比例 68
    表5-4-10:就診科別比例 68
    表5-4-11:門診開立Metformin前半年內之eGFR檢測紀錄 69
    表5-4-12:門診病人慢性腎臟病分期比例 69
    表5-4-13:門診就診科別比例 70
    表5-4-14:門診Metformin用藥治療指引遵循度 70
    表5-4-15:門診病人慢性腎臟病分期比例 71
    表5-4-16:門診就診科別比例 71
    表5-4-17:門診病人慢性腎臟病分期比例 72
    表5-4-18:門診就診科別比例 72
    表5-4-19:門診開立Metformin前半年內之eGFR檢測紀錄 73
    表5-4-20:病人慢性腎臟病分期比例 73
    表5-4-21:門診就診科別比例 73
    表5-4-22:門診Metformin用藥治療指引遵循度 74
    表5-4-23:門診病人慢性腎臟病分期比例 74
    表5-4-24:門診就診科別比例 75
    表5-4-26:門診CDSSs介入後符合藥物治療指引情形與前2年數據比較 76
    表5-5:CDSSs介入前醫師訪問問題及結果 77
    表5-6:CDSSs介入後醫師訪問問題及結果 80
    表5-7:CDSSs介入前藥師訪問問題及結果 83
    表5-8:CDSSs介入後藥師訪問問題及結果 88
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    口試委員
  • 許弘毅 - 召集委員
  • 李英俊 - 委員
  • 陳崇鈺 - 委員
  • 陳盈凱 - 委員
  • 葉淑娟 - 指導教授
  • 口試日期 2020-07-29 繳交日期 2020-07-24

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