提高2023年酒标准的可用性:老年人处方安全的结构框架
Ying-Mei Wang1, Pei-Chen Lee2, Hung-Wei Shen3
1Department of Medical Education and Research, Taipei Veterans General Hospital Hsinchu Branch, Hsinchu, Taiwan, ROC; No. 81, Sec. 1, Zhongfeng Rd., Zhudong Township, Hsinchu County 310, Taiwan, ROC; Department of Pharmacy, Taipei Veterans General Hospital Hsinchu Branch, Hsinchu, Taiwan, ROC; No. 81, Sec. 1, Zhongfeng Rd., Zhudong Township, Hsinchu County 310, ROC, Taiwan; School of Medicine, National Tsing Hua University, Hsinchu, Taiwan, ROC; No. 101, Sec. 2, Kuang-Fu Rd., Hsinchu City 300, ROC, Taiwan.
一个新的框架使AGS Beers标准可用于自动识别老年人潜在不合适的药物 (PIM). 这有助于提高老年人药物监测的药物安全性和EHR整合.
科学领域:
- 老年人药物监测
- 卫生信息学
- 临床决策支持
背景情况:
- 美国老年病学协会 (AGS) 的酒标准是识别老年人潜在不合适药物的关键工具.
- 它的叙述格式和机器可读性不足限制了与电子健康记录 (EHR) 和临床决策支持系统的整合.
- 自动识别PIM对于提高药物安全性至关重要.
研究的目的:
- 为2023年AGS酒标准制定一个结构化,可编程和多维的评估框架.
- 将标准转化为可计算的逻辑组件,用于自动化PIM识别.
- 支持加强临床应用和现实数据分析.
主要方法:
- 从2023年AGS酒标准中对87个与PIM相关的陈述进行系统审查.
- 一个多学科团队将标准分解成结构化的逻辑组件.
- 分为五个领域 (处方,建议,关键问题,解释性信息) 和24个子类别.
主要成果:
- 仅有8. 0%的标准可以仅根据药物名称进行评估,92. 0%需要多因素分析.
- 确定了404个可计算的元素:30.2%只需处方,25.2%需要外部数据,44.6%涉及解释复杂性.
- 这一框架揭示了药物名称之外的复杂性.
结论:
- 这一新框架克服了对AGS酒标准的程序性实施的障碍.
- 能够使用人工智能支持的PIM识别和无EHR集成.
- 建立一个可扩展的老年药物监测基础设施,提高药物安全性.
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