加强电子健康记录中的安全信息传递:评估表情符号聊天反应对中断通知量的影响

ACI open Pub Date : 2024-07-01 DOI:10.1055/s-0044-1788621
John Will, William Small, Eduardo Iturrate, Paul Testa, Jonah Feldman
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引用次数: 0

摘要

背景 电子健康记录安全信息(EHRSM)是临床医生之间越来越常用的通信工具。然而,人们对其通过中断性通知造成的干扰日益增多表示担忧。研究目的 本研究的主要目的是评估在 EHRSM 中引入不会触发推送通知的表情符号反应是否能减轻干扰性通知的负担。第二个目的是利用信息通知元数据来识别可能从有针对性的干预措施中受益的亚群体,以帮助这一创新的采用。方法 我们在一个大型学术医疗系统的 EHRSM 中使用了表情符号反应功能。我们评估了在 EHRSM 中引入 emoji 反应功能之前(emoji 前)和之后(emoji 后)11 周的推送通知量。我们按照用户类型对通知元数据进行了分类,并根据通知量对用户进行了分层。结果 后 emoji 时期的推送通知减少了 1,387,506 条(减少了 4.7%)。在 Emoji 使用前,平均每日推送通知量不断增加的用户子群,在 Emoji 使用后,平均每日推送通知量也随之减少。在八个用户分组中,有六个分组的中断通知显著减少,而药店和 "其他 "分组的中断通知没有减少。在每个用户分组中,通知量最高的四分位数用户的负担减少幅度最大。结论 在一个大型学术医疗系统中,将表情符号反应整合到 EHRSM 中可显著减轻 EHRSM 用户的推送通知负担。利用消息通知元数据,我们可以识别出需要额外干预的亚组。
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Enhancing Secure Messaging in Electronic Health Records: Evaluating the Impact of Emoji Chat Reactions on the Volume of Interruptive Notifications
Background Electronic health record secure messaging (EHRSM) is an increasingly utilized tool for communication among clinicians. However, there is concern about the growing quantity of disruptions it presents via interruptive notification. Objectives The primary aim of this study is to assess whether introducing emoji reactions, which do not trigger push notifications in EHRSM, can alleviate the burden of interruptive notifications. The second aim is to use messaging notification metadata to identify subgroups that might benefit from targeted interventions to aid the adoption of this innovation. Methods We implemented the emoji reaction feature into EHRSM across a large academic health system. We evaluated the volume of push notifications 11 weeks before (pre-emoji period) and after (post-emoji period) introducing emoji reactions in EHRSM. Notification metadata was categorized by user type, and users were stratified based on notification volume. Results There were 1,387,506 fewer push notifications in the post-emoji period (a decrease of 4.7%). Subgroups of users with increasing mean daily push notifications in the pre-emoji period were associated with decreasing mean daily push notifications in the post-emoji period. Among the eight user subgroups, six experienced a significant reduction in interruptive notifications, with the pharmacy and “other” subgroups not observing a reduction. Users in the top quartile of notification volume saw the greatest reduction in burden across each user subgroup. Conclusion Integrating emoji reactions into EHRSM across a large academic health system significantly reduced the burden of push notifications among EHRSM users. Utilizing messaging notification metadata allowed us to identify subgroups that require additional intervention.
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