Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Appl Clin Inform. 2021 Jan;12(1):164-169. doi: 10.1055/s-0041-1723023. Epub 2021 Mar 3.
The data visualization literature asserts that the details of the optimal data display must be tailored to the specific task, the background of the user, and the characteristics of the data. The general organizing principle of a concept-oriented display is known to be useful for many tasks and data types.
In this project, we used general principles of data visualization and a co-design process to produce a clinical display tailored to a specific cognitive task, chosen from the anesthesia domain, but with clear generalizability to other clinical tasks. To support the work of the anesthesia-in-charge (AIC) our task was, for a given day, to depict the acuity level and complexity of each patient in the collection of those that will be operated on the following day. The AIC uses this information to optimally allocate anesthesia staff and providers across operating rooms.
We used a co-design process to collaborate with participants who work in the AIC role. We conducted two in-depth interviews with AICs and engaged them in subsequent input on iterative design solutions.
Through a co-design process, we found (1) the need to carefully match the level of detail in the display to the level required by the clinical task, (2) the impedance caused by irrelevant information on the screen such as icons relevant only to other tasks, and (3) the desire for a specific but optional trajectory of increasingly detailed textual summaries.
This study reports a real-world clinical informatics development project that engaged users as co-designers. Our process led to the user-preferred design of a single binary flag to identify the subset of patients needing further investigation, and then a trajectory of increasingly detailed, text-based abstractions for each patient that can be displayed when more information is needed.
数据可视化文献断言,最佳数据显示的细节必须针对特定任务、用户背景和数据特征进行定制。面向概念的显示的一般组织原则已知对许多任务和数据类型都有用。
在这个项目中,我们使用数据可视化的一般原则和共同设计过程,为特定认知任务(选自麻醉领域)量身定制了临床显示,但具有明确的通用性,可以应用于其他临床任务。为了支持主治麻醉师(AIC)的工作,我们的任务是为给定的一天,描绘出次日接受手术的患者集合中每个患者的 acuity 水平和复杂性。AIC 使用此信息在手术室之间最优地分配麻醉人员和资源。
我们使用共同设计过程与担任 AIC 角色的参与者合作。我们对 AIC 进行了两次深入访谈,并让他们对迭代设计解决方案提供后续输入。
通过共同设计过程,我们发现 (1) 需要仔细匹配显示的详细程度与临床任务所需的详细程度,(2) 屏幕上无关信息(如仅与其他任务相关的图标)造成的干扰,以及 (3) 对特定但可选的、越来越详细的文本摘要轨迹的需求。
本研究报告了一个真实的临床信息学开发项目,该项目让用户作为共同设计者参与其中。我们的过程导致了用户首选的设计,即使用一个单一的二进制标志来标识需要进一步调查的患者子集,然后是每个患者的越来越详细的基于文本的抽象轨迹,可以在需要更多信息时显示。