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短信提醒急诊医师识别潜在的研究对象可增加临床试验的入组人数。

Text message alerts to emergency physicians identifying potential study candidates increase clinical trial enrollment.

机构信息

Division of Research, Kaiser Permanente, Oakland, California, USA.

Emergency Department, Kaiser Permanente South San Francisco Medical Center, South San Francisco, California, USA.

出版信息

J Am Med Inform Assoc. 2019 Nov 1;26(11):1360-1363. doi: 10.1093/jamia/ocz118.

Abstract

Prospective enrollment of research subjects in the fast-paced emergency department (ED) is challenging. We sought to develop a software application to increase real-time clinical trial enrollment during an ED visit. The Prospective Intelligence System for Clinical Emergency Services (PISCES) scans the electronic health record during ED encounters for preselected clinical characteristics of potentially eligible study participants and notifies the treating physician via mobile phone text alerts. PISCES alerts began 3 months into a cluster randomized trial of an electronic health record-based risk stratification tool for pediatric abdominal pain in 11 Northern California EDs. We compared aggregate enrollment before (2577 eligible patients, October 2016 to December 2016) and after (12 049 eligible patients, January 2017 to January 2018) PISCES implementation. Enrollment increased from 10.8% to 21.1% following PISCES implementations (P < .001). PISCES significantly increased study enrollment and can serve as a valuable tool to assist prospective research enrollment in the ED.

摘要

在快节奏的急诊部(ED)中,前瞻性地招募研究对象具有挑战性。我们试图开发一种软件应用程序,以便在 ED 就诊期间实时增加临床试验的入组率。前瞻性临床急诊服务智能系统(PISCES)在 ED 就诊期间扫描电子健康记录,寻找有潜在资格的研究参与者的预先选定的临床特征,并通过手机短信提醒通知主治医生。在加利福尼亚北部 11 家 ED 中进行的一项基于电子健康记录的儿科腹痛风险分层工具的电子病历基础的前瞻性随机试验中,PISCES 提醒在试验开始后 3 个月开始。我们比较了实施 PISCES 前后(2016 年 10 月至 12 月,2577 名符合条件的患者;2017 年 1 月至 2018 年 1 月,12049 名符合条件的患者)的总体入组率。实施 PISCES 后,入组率从 10.8%增加到 21.1%(P<.001)。PISCES 显著增加了研究的入组率,可作为协助 ED 前瞻性研究入组的有价值工具。

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