Open & Act: Tracking Healthcare Team Response to EHR Asynchronous Alerts

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• 批准号: 8807431
• 负责人: Sarah LeLeiko Cutrona
• 金额: $ 11.84万
• 依托单位: UNIV OF MASSACHUSETTS MED SCH WORCESTER
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-30 至 2016-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8807431
• 关键词: Open; Act; Tracking; Healthcare; Team

DESCRIPTION (provided by applicant): Electronic Health Record (EHR)-based asynchronous messaging is a form of secure, email-style message exchange used widely by healthcare teams to communicate time-sensitive patient information without requiring sender and receiver to engage simultaneously. Asynchronous alerts are messages whose primary goal is to prompt timely, relevant healthcare team action aimed at improving patient outcomes. Unlike alerts that interrupt users mid-task, asynchronous alerts are delivered to a secure electronic "In-Basket" where they wait to be opened. While numerous studies describe interruptive alerts, little is known about the use, impact and risk of asynchronous alerts. This is an important gap. Often asynchronous alerts serve as the only notification to healthcare team members of time-sensitive issues; unopened alerts represent a potentially dangerous communication breakdown. Through previous AHRQ funding (R18 HS017203) we implemented an alert intervention notifying primary care teams of medication safety concerns and the need for close office follow-up post hospitalization. Automated asynchronous alerts were sent following 1282 hospital discharges of elderly patients but we found no evidence of an impact on patient outcomes. Preliminary review showed that 40% of staff-directed alerts and 19% of primary care provider alerts remained unopened at the end of day 1 post- delivery. A variety of sociotechnical factors likely influenced alert opening and subsequent actions. We compiled a rich collection of data with detailed information on alerts, the discharges triggering those alerts, contextual factors (e.g. number of unopened messages in the recipient's "In-Basket" at the time of alert delivery), patient and provider characteristics, and clinical outcome data. We enriched this data with electronic tracking data ("digital crumbs") recording the date and time of the creation and review of EHR data elements. We propose a secondary data analysis to identify contextual factors, types of alerts and characteristics of providers, patients and hospital discharges that relate to (a) timely opening of alerts following receipt and (b) timely first responsive action after alerts are receive and opened. We will also conduct a sequential pattern analysis describing the relevant actions taken by healthcare providers immediately following alert opening. Finally, we will assess the relationship between timely first responsive action following opening of alerts and key patient outcomes (office visits, rehospitalization, ER and urgicare visits, and adverse drug events). Our study is timely and innovative in its proposed use of digital crumbs, a largely untapped data source that will allow us to identify points of communication breakdown on the alert-response pathway. Epic Systems Corporation, the EHR system from which we have gathered our data, stores medical information for close to 127 million patients or nearly 40% of the U.S. population. What our research team learns by using digital crumbs to track alert opening and response will be broadly applicable to healthcare teams and researchers across the nation, and will inform design and implementation of future asynchronous alert systems.

描述（由申请人提供）：基于电子健康记录（EHR）的异步消息传递是一种安全的电子邮件式消息交换形式，被医疗团队广泛用于传达时间敏感的患者信息，而无需发送者和接收者同时参与。异步警报是一种消息，其主要目标是及时提示相关的医疗保健团队行动，以改善患者结局。与中断用户任务的警报不同，异步警报被传递到安全的电子“In-Basket”，在那里它们等待被打开。虽然许多研究描述了中断警报，但对异步警报的使用，影响和风险知之甚少。这是一个重要的差距。通常，异步警报是向医疗团队成员通知时间敏感问题的唯一通知;未打开的警报代表潜在的危险通信故障。通过之前的AHRQ资助（R18 HS 017203），我们实施了一项警报干预措施，通知初级保健团队药物安全问题和住院后密切随访的必要性。在1282名老年患者出院后，我们发送了自动异步警报，但我们没有发现对患者结局产生影响的证据。初步审查显示，40%的工作人员指导警报和19%的初级保健提供者警报在分娩后第1天结束时仍未打开。各种社会技术因素可能影响警报的开启和随后的行动。我们收集了丰富的数据，其中包括警报的详细信息，触发这些警报的放电，上下文因素（例如，在警报传递时收件人的“In-Basket”中未打开的消息数量），患者和提供者特征以及临床结果数据。我们使用电子跟踪数据（“数字碎屑”）丰富了这些数据，这些数据记录了EHR数据元素的创建和审查的日期和时间。我们提出了一个二级数据分析，以确定上下文因素，警报类型和特征的供应商，病人和医院出院，涉及（a）及时 在接收之后打开警报，以及（B）在接收和打开警报之后及时地第一响应动作。我们还将进行序列模式分析，描述警报开启后医疗保健提供者立即采取的相关行动。最后，我们将评估警报打开后及时采取的第一响应行动与关键患者结局（门诊访视、再住院、ER和药物治疗访视以及药物不良事件）之间的关系。我们的研究在数字碎片的拟议使用方面是及时且创新的，数字碎片是一种基本上未开发的数据源，将使我们能够识别警报响应路径上的通信故障点。Epic Systems Corporation是我们收集数据的EHR系统，存储了近1.27亿患者或近40%美国人口的医疗信息。我们的研究团队通过使用数字碎片来跟踪警报打开和响应所学到的知识将广泛适用于全国各地的医疗团队和研究人员，并将为未来异步警报系统的设计和实施提供信息。