期刊文献

Defining key deprescribing measures from electronic health data: A multisite data harmonization project 收藏

从电子健康数据定义关键的划分措施：一个多站点数据协调项目

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作者

Sascha Dublin (0000-0002-6649-3659) [1];Ladia Albertson‐Junkans [2];Thanh Phuong Pham Nguyen (0000-0003-3589-764X) [3];Juliessa M. Pavon (0000-0002-9047-0051) [4];S. Nicole Hastings [5];Matthew L. Maciejewski [6];Allison Willis [7];Lindsay Zepel [8];Sean Hennessy [9];Kathleen B. Albers [10];Danielle Mowery [11];Amy G. Clark [12];Sunil Thomas [13];Michael A. Steinman (0000-0002-9564-9480) [14];Cynthia M. Boyd [15];Elizabeth A. Bayliss [16];

作者单位

[1]Kaiser Permanente Washington Health Research Institute Seattle Washington USA; [2]Kaiser Permanente Washington Health Research Institute Seattle Washington USA; [3]University of Pennsylvania Perelman School of Medicine Philadelphia Pennsylvania USA; [4]Duke University School of Medicine Durham North Carolina USA; [5]Duke University School of Medicine Durham North Carolina USA; [6]Duke University School of Medicine Durham North Carolina USA; [7]University of Pennsylvania Perelman School of Medicine Philadelphia Pennsylvania USA; [8]Department of Population Health Sciences Duke University Durham North Carolina USA; [9]University of Pennsylvania Perelman School of Medicine Philadelphia Pennsylvania USA; [10]Kaiser Permanente Colorado Institute for Health Research Aurora Colorado USA; [11]University of Pennsylvania Perelman School of Medicine Philadelphia Pennsylvania USA; [12]Department of Population Health Sciences Duke University Durham North Carolina USA; [13]University of Pennsylvania Perelman School of Medicine Philadelphia Pennsylvania USA; [14]Division of Geriatrics University of California San Francisco San Francisco California USA; [15]Division of Geriatric Medicine and Gerontology and Center for Transformative Geriatric Research Johns Hopkins University School of Medicine Baltimore Maryland USA; [16]Kaiser Permanente Colorado Institute for Health Research Aurora Colorado USA;

发布日期

2024-11-28

页码

399-410

DOI

10.1111/jgs.19280

来源信息

Journal of the American Geriatrics Society ISSN：0002-8614, 2025年, 73卷, 2期, 399-410页

摘要

【Abstract】【Background】Stopping or reducing risky or unneeded medications (“deprescribing”) could improve older adults' health. Electronic health data can support observational and intervention studies of deprescribing, but there are no standardized measures for key variables, and healthcare systems have differing data types and availability. We developed definitions for chronic medication use and discontinuation based on electronic health data and applied them in a case study of benzodiazepines and Z‐drugs in five diverse US healthcare systems.【Methods】We conducted a retrospective cohort study of adults age 65+ from 2017 to 2019 with chronic benzodiazepine or Z‐drug use. We determined whether sites had access to medication orders and/or dispensings. We developed definitions for chronic use and discontinuation using both data types. Discontinuation definitions were based on (1) gaps in medication availability during follow‐up or (2) not having medication available at a fixed time point. We examined the impact of varying the gap length and requiring a 30‐day period without orders/dispensings (“halo”) around the fixed time point. We compared results derived from orders versus dispensings at one site.【Results】Approximately 1.6%–2.6% of older adults had chronic benzodiazepine/Z‐drug use (total N = 6775, ranging from 431 to 2122 across sites). Depending on the definition and site, the proportion discontinuing use during 12 months ranged from 6% to 49%. Requiring a longer gap or a 30‐day “halo” resulted in lower estimates. At one site, only 56% of those with chronic use defined from orders also qualified based on dispensings, and the discontinuation rate at 180 days was 20% from orders versus 32% from dispensings.【Conclusions】Requiring a gap of ≥90 days or a “halo” around a time point may more accurately capture discontinuation than using a shorter gap or no halo. Orders data underestimate discontinuation compared to dispensings. Work is needed to adapt these definitions for other drug classes and settings.

摘要译文

【摘要】【背景】停止或减少危险或不需要的药物（“分类”）可以改善老年人的健康状况。电子健康数据可以支持对排除的观察性和干预研究，但是没有针对关键变量的标准化措施，医疗保健系统具有不同的数据类型和可用性。我们基于电子健康数据开发了慢性药物使用和中断的定义，并在五种美国医疗保健系统中的苯二氮卓类和Z -Drugs的案例研究中应用了定义。方法【方法】我们对2017年至2019年的65岁以上的成年人进行了回顾性群体研究。我们确定站点是否可以使用药物订单和/或分配。我们使用两种数据类型开发了长期使用和中断的定义。停用定义基于（1）随访期间药物可用性的差距，或（2）在固定时间点没有可用的药物。我们检查了改变间隙长度并需要在固定时间点附近没有订单/分配（“ halo”）的30天期间的影响。我们比较了一个地点的订单与分配的结果。【结果】大约1.6％–2.6％的老年人患有慢性苯二氮卓/z -frug使用（总n = 6775，范围从431到2122个地点）。根据定义和站点，在12个月内停止使用的比例范围从6％到49％。需要更长的差距或30天的“光晕”导致估计值较低。在一个站点上，只有56％的慢性使用定义的订单定义的人也有资格根据分配的资格，并且在180天的停用率是订单的20％，而订单的停用率为20％，而分配为32％。【结论】结论需要≥90天或在一个时间点附近的“ halo”可能更准确地捕捉到不使用shorer shorer gap的时间点。与分配相比，订单数据低估了终止。需要工作以适应其他药物类别和设置。