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    3차 병원 입원환자의 지참약 불일치 검토 및 중재활동 결과 분석 연구 = Analysis of Review on Drug Discrepancies and Medication Reconciliation of Patients Admitted to a Tertiary Hospital

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    https://www.riss.kr/link?id=T17080577

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    Background : The problem of drug discrepancies (DD) occurs during the transition from personal medications to hospital medications, leading to potential medication errors. Such errors are preventable and can extend hospital stays and increase readmission risks. Despite existing reports on the types and intervention rates of DDs, there is a lack of in-depth analysis of intervention types, methods, and influencing factors. This study aims to provide a more detailed understanding to improve the efficiency of medication reconciliation (MR).
    Methods : This retrospective study reviewed Electronic Medical Record of patients admitted to Chosun University Hospital between January and March 2023, who had their personal medications switched to hospital medications within five days of admission. The study focused on analyzing the types and frequencies of DDs, the interventions made, and the factors influencing these discrepancies. For the basic characteristics of the study subjects, categorical variables were expressed as frequencies (N) and percentages (%), while continuous variables were expressed as means ± standard deviation. Fisher’s exact test was used to test the significance of intervention outcomes, and multivariable logistic regression analysis was employed to analyze the impact of patient characteristics and drug characteristics on DD.
    Results : Among the reviewed cases, 79 instances of DDs were identified and addressed. The most common intervention was correcting dosage errors in the prescribed hospital medications (68.35%). Acceptance rate of these interventions by medical staff was high (73.24%), with dosage errors being the most frequently accepted intervention (70.69%). Similar patterns were observed for non-accepted interventions, though specific reasons for non-acceptance were not ascertainable.
    Conclusion: MR significantly reduces medication errors related to unintended discrepancies, proving to be an effective method in preventing adverse drug reactions. However, the process is time-consuming and requires thorough comparison and communication of medication details between personal and hospital medications. The study highlights the need for prioritizing MR activities for patients at higher risk of DDs to optimize medication safety and healthcare outcomes. Keywords: Drug Discrepancies, Medication Reconciliation, Medication Error
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    Background : The problem of drug discrepancies (DD) occurs during the transition from personal medications to hospital medications, leading to potential medication errors. Such errors are preventable and can extend hospital stays and increase readmiss...

    Background : The problem of drug discrepancies (DD) occurs during the transition from personal medications to hospital medications, leading to potential medication errors. Such errors are preventable and can extend hospital stays and increase readmission risks. Despite existing reports on the types and intervention rates of DDs, there is a lack of in-depth analysis of intervention types, methods, and influencing factors. This study aims to provide a more detailed understanding to improve the efficiency of medication reconciliation (MR).
    Methods : This retrospective study reviewed Electronic Medical Record of patients admitted to Chosun University Hospital between January and March 2023, who had their personal medications switched to hospital medications within five days of admission. The study focused on analyzing the types and frequencies of DDs, the interventions made, and the factors influencing these discrepancies. For the basic characteristics of the study subjects, categorical variables were expressed as frequencies (N) and percentages (%), while continuous variables were expressed as means ± standard deviation. Fisher’s exact test was used to test the significance of intervention outcomes, and multivariable logistic regression analysis was employed to analyze the impact of patient characteristics and drug characteristics on DD.
    Results : Among the reviewed cases, 79 instances of DDs were identified and addressed. The most common intervention was correcting dosage errors in the prescribed hospital medications (68.35%). Acceptance rate of these interventions by medical staff was high (73.24%), with dosage errors being the most frequently accepted intervention (70.69%). Similar patterns were observed for non-accepted interventions, though specific reasons for non-acceptance were not ascertainable.
    Conclusion: MR significantly reduces medication errors related to unintended discrepancies, proving to be an effective method in preventing adverse drug reactions. However, the process is time-consuming and requires thorough comparison and communication of medication details between personal and hospital medications. The study highlights the need for prioritizing MR activities for patients at higher risk of DDs to optimize medication safety and healthcare outcomes. Keywords: Drug Discrepancies, Medication Reconciliation, Medication Error

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    목차 (Table of Contents)

    • I. 서론 1
    • A. 연구 배경 및 연구 목적 1
    • 1. 연구배경 1
    • 2. 연구목적 5
    • Ⅱ. 연구 방법 6
    • I. 서론 1
    • A. 연구 배경 및 연구 목적 1
    • 1. 연구배경 1
    • 2. 연구목적 5
    • Ⅱ. 연구 방법 6
    • A. 연구 대상 6
    • B. 연구 범위 6
    • 1. 포함 대상 6
    • 2. 제외 대상 6
    • C. 자료 수집 7
    • 1. 지참약 불일치 확인 및 약물조정 과정 7
    • 2. 자료수집 10
    • D. 분석 항목 11
    • 1. 연구대상자의 특성 분석 11
    • 2. 지참약 불일치 빈도 및 유형조사 11
    • 3. 지참약 불일치에 대한 중재여부 조사 11
    • 4. 지참약 불일치에 대한 영향인자 조사 11
    • E. 통계 방법 12
    • Ⅲ. 연구결과 13
    • A. 연구대상자의 지참약 처방에 따른 분류 13
    • B. 연구대상자의 기본 특성 15
    • C. 지참약 불일치 분석 17
    • 1. 지참약 불일치 분석 18
    • 2. 지침약 불일치 유형 분석 20
    • 3. 약효별 지참약 불일치 분류 22
    • 4. 약물 특성별 지참약 불일치 분석 24
    • 5. 지참약 불일치 진료과별 분석 26
    • D. 지참약 불일치에 대한 중재 분석 27
    • E. 지참약 불일치에서 중재여부에 영향을 주는 인자 분석 32
    • Ⅳ. 고찰 34
    • Ⅴ. 결론 38
    • Ⅵ. 참고문헌 39
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