查詢結果分析
相關文獻
- 運用管制圖進行藥物異常事件監控與改善
- The Development of Supplementary Rules for 竍 Control Chart under Nonrandom Patterns
- 非常態性資料下中位數管制圖之研究
- 使用尼曼A型分配於積體電路晶圓缺陷管制圖之經濟性設計
- 破管制圖迷思 造品質之功
- 時間序列分析在品質管制上的應用
- Further Discussions of Quality Control Tools
- 應用管制圖作好持續改善
- 少量連串生產下R管制圖之最適設計
- A Simple and Efficient Procedure for the Economic Designs of np-Charts to Maintain Current Control of a Process
頁籤選單縮合
題名 | 運用管制圖進行藥物異常事件監控與改善=The Use of Control Chart to Monitor and Improve Medication Incident |
---|---|
作者 | 吳文祥; 王瑛玫; 黃婉翠; 王惠蓉; 馮介凡; | 書刊名 | 臺灣臨床藥學雜誌 |
卷期 | 20:4 2012.12[民101.12] |
頁次 | 頁301-314 |
分類號 | 419.38 |
關鍵詞 | 病人安全通報系統; 藥物異常事件; 醫療照護品質指標; 管制圖; 醫囑錯誤; 醫師處方箋錯誤率; Patient safety reporting system; Medication incident; Quality indicator; Control chart; Prescribing error; |
語文 | 中文(Chinese) |
中文摘要 | 目的:在複雜之醫療過程中,藥物異常事件極難避免,因此衛生署將用藥安全列為病人安全之首要目標,而國內亦有相關用藥安全管理指標,目的皆在於避免與及時發現藥物異常事件。因此本研究將運用管制圖以及現有之台灣病人安全通報系統與台灣醫療照護指標兩大系統,進行藥物異常事件之監控與改善。方法:本研究以藥物異常事件之門診醫師處方箋錯誤率為例,從病人安全通報系統收集資料,進行台灣醫療照護指標通報,並運用管制圖進行監控。若發現異常,則以病人安全通報系統之錯誤型態與原因進行分析,透過魚骨圖與柏拉圖等分析工具找出原因,並進行改善方案。結果:經本研究監控發現,2010年3月醫師處方箋錯誤率上升至0.218%,因此第一階段進行醫師處方箋錯誤資料分析,並針對頻率錯誤、途徑錯誤、劑型錯誤以及重複用藥等主要原因設置醫令系統防錯機制,7月時醫師處方箋錯誤率下降至0.170%。第二階段針對人為因素進行改善,直接將錯誤回饋給醫師,則醫師處方箋錯誤率降低至2011年6月份之0.050%。結論:經過本研究流程設計,從前端之通報至後續之監控與改善,可隨時監控藥物異常事件發生率,即時發現異常狀態,及早進行改善。除此之外,可與同儕醫院比較,提升服務品質與用藥安全,以防範重大藥物不良事件發生。 |
英文摘要 | Objective Medication incident is hard to avoid during the complicated medical process. The Taiwan Department of Health set the first aim of patient safety as "to elevate drug safety ". In addition, there are several drug safety indicators to monitor medication incident. This study wants to monitor and prevent the medication incident by using Taiwan Patient Safety Reporting System (TPR) data, Taiwan Healthcare Indicator Series (THIS) data and control chart. Methods The researchers collected prescribing error, one of the medication incidents, from TPR system during 2009 to 2010 and calculated THIS indicator. If prescribing error rate monitored by control chart is abnormal, the researchers should analyze original data to find the cause of abnormality and improve it. Results In the monitoring process, the researchers detected prescribing error rate elevated over upper control limit in March, 2010 and found its causes to be related to wrong frequency, wrong route, wrong dosage and duplication. By targeting these causes, the researchers developed block-off function to avoid systemic-related error and feedback to doctors in minimizing human-related causes. After those interventions, prescribing error rate decreased to 0.05% in June 2011. Conclusions Using this process, from reporting, monitoring to improvement, hospital can monitor medication incident in real-time in order to prevent sentinel drug events. In addition, the process can be used to compare with other hospitals' performances to elevate quality and safety. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。