Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois, USA.
J Am Med Inform Assoc. 2020 Feb 1;27(2):236-243. doi: 10.1093/jamia/ocz151.
Research to date focused on quantifying team collaboration has relied on identifying shared patients but does not incorporate the major role of communication patterns. The goal of this study was to describe the patterns and volume of communication among care team members involved in treating breast cancer patients.
We analyzed 4 years of communications data from the electronic health record between care team members at Vanderbilt University Medical Center (VUMC). Our cohort of patients diagnosed with breast cancer was identified using the VUMC tumor registry. We classified each care team member participating in electronic messaging by their institutional role and classified physicians by specialty. To identify collaborative patterns, we modeled the data as a social network.
Our cohort of 1181 patients was the subject of 322 424 messages sent in 104 210 unique communication threads by 5620 employees. On average, each patient was the subject of 88.2 message threads involving 106.4 employees. Each employee, on average, sent 72.9 messages and was connected to 24.6 collaborators. Nurses and physicians were involved in 98% and 44% of all message threads, respectively.
Our results suggest that many providers in our study may experience a high volume of messaging work. By using data routinely generated through interaction with the electronic health record, we can begin to evaluate how to iteratively implement and assess initiatives to improve the efficiency of care coordination and reduce unnecessary messaging work across all care team roles.
迄今为止,有关团队协作的研究主要依赖于确定共享患者,但并未纳入沟通模式的主要作用。本研究的目的是描述参与治疗乳腺癌患者的护理团队成员之间的沟通模式和沟通量。
我们分析了范德比尔特大学医学中心(VUMC)电子健康记录中来自护理团队成员的 4 年沟通数据。我们使用 VUMC 肿瘤登记处确定了被诊断患有乳腺癌的患者队列。我们根据机构角色对参与电子消息传递的每个护理团队成员进行分类,并按专业对医生进行分类。为了识别协作模式,我们将数据建模为社交网络。
我们的 1181 名患者队列是 322424 条消息的主题,这些消息是由 5620 名员工在 104210 个唯一的通信线程中发送的。平均而言,每个患者是涉及 106.4 名员工的 88.2 个消息线程的主题。平均而言,每个员工发送 72.9 条消息,与 24.6 个协作者相连。护士和医生分别参与了所有消息线程的 98%和 44%。
我们的结果表明,我们研究中的许多提供者可能会经历大量的消息传递工作。通过使用通过与电子健康记录交互生成的数据,我们可以开始评估如何迭代地实施和评估旨在提高护理协调效率并减少所有护理团队角色中不必要的消息传递工作的举措。