Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States.
Department of Pediatrics, Wake Forest Baptist Health, Winston-Salem, North Carolina, United States.
Appl Clin Inform. 2019 May;10(3):471-478. doi: 10.1055/s-0039-1692401. Epub 2019 Jun 26.
This study attempts to characterize the inpatient communication network within a quaternary pediatric academic medical center by applying network analysis methods to secure text-messaging data.
We used network graphing and statistical software to create network models of an inpatient communication system with secure text-messaging data from physicians, nurses, and other ancillary staff in an academic medical center. Descriptive statistics about the network, users within the network, and visualizations informed the team's understanding of the network and its components.
Analysis of messages exchanged over approximately 23 days revealed a large, scale-free network with 4,442 nodes and 59,913 edges. Quantitative description of user behavior (messages sent and received) and network metrics (i.e., importance of nodes within a network) revealed several operational and clinical roles both sending and receiving > 1,000 messages over this time period. While some of these nodes represented expected "dispatcher" roles in our inpatient system, others occupied important frontline clinical roles responsible for bedside clinical care.
Quantitative and network analysis of secure text-messaging logs revealed several key operational and clinical roles at risk for alert fatigue and information overload. This analysis also revealed a communication network highly reliant on these key roles, meaning disruption to these individuals or their workflows could lead to dysfunction of the communication network. While secure text-messaging applications play increasingly important roles in facilitating inpatient communication, little is understood about the impact these systems have on health care providers. Developing methods to understand and optimize communication between inpatient providers might help operational and clinical leaders to proactively prevent poorly understood pitfalls associated with these systems and build resilient and effective communication structures.
本研究试图通过应用网络分析方法对安全短信数据进行分析,来描述四级儿科学术医疗中心的住院患者沟通网络。
我们使用网络图和统计软件,以安全短信数据为基础,创建了来自学术医疗中心的医生、护士和其他辅助人员的住院患者沟通系统的网络模型。网络、网络中的用户以及可视化的描述性统计信息帮助团队了解网络及其组成部分。
对大约 23 天内交换的消息进行分析后,发现了一个大型无标度网络,其中有 4442 个节点和 59913 条边。用户行为(发送和接收的消息)和网络指标(即网络中节点的重要性)的定量描述揭示了在此期间发送和接收>1000 条消息的几个操作和临床角色。虽然这些节点中的一些代表了我们住院系统中的预期“调度员”角色,但其他节点则承担着重要的前线临床角色,负责床边临床护理。
对安全短信日志进行定量和网络分析,揭示了几个在面临警报疲劳和信息过载时处于高风险的操作和临床角色。该分析还揭示了一个高度依赖这些关键角色的沟通网络,这意味着这些个体或其工作流程的中断可能导致沟通网络的功能失调。虽然安全短信应用程序在促进住院患者沟通方面发挥着越来越重要的作用,但对于这些系统对医疗保健提供者的影响,我们知之甚少。开发了解和优化住院患者之间沟通的方法,可能有助于运营和临床领导者主动预防与这些系统相关的未被充分理解的陷阱,并构建有弹性和有效的沟通结构。