Strauss Alexandra T, Morgan Cameron, El Khuri Christopher, Slogeris Becky, Smith Aria G, Klein Eili, Toerper Matt, DeAngelo Anthony, Debraine Arnaud, Peterson Susan, Gurses Ayse P, Levin Scott, Hinson Jeremiah
Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Center for Social Design, Maryland Institute College of Art, Baltimore, MD, United States.
JMIR Hum Factors. 2022 Mar 23;9(1):e30130. doi: 10.2196/30130.
The availability of patient outcomes-based feedback is limited in episodic care environments such as the emergency department. Emergency medicine (EM) clinicians set care trajectories for a majority of hospitalized patients and provide definitive care to an even larger number of those discharged into the community. EM clinicians are often unaware of the short- and long-term health outcomes of patients and how their actions may have contributed. Despite large volumes of patients and data, outcomes-driven learning that targets individual clinician experiences is meager. Integrated electronic health record (EHR) systems provide opportunity, but they do not have readily available functionality intended for outcomes-based learning.
This study sought to unlock insights from routinely collected EHR data through the development of an individualizable patient outcomes feedback platform for EM clinicians. Here, we describe the iterative development of this platform, Linking Outcomes Of Patients (LOOP), under a human-centered design framework, including structured feedback obtained from its use.
This multimodal study consisting of human-centered design studios, surveys (24 physicians), interviews (11 physicians), and a LOOP application usability evaluation (12 EM physicians for ≥30 minutes each) was performed between August 2019 and February 2021. The study spanned 3 phases: (1) conceptual development under a human-centered design framework, (2) LOOP technical platform development, and (3) usability evaluation comparing pre- and post-LOOP feedback gathering practices in the EHR.
An initial human-centered design studio and EM clinician surveys revealed common themes of disconnect between EM clinicians and their patients after the encounter. Fundamental postencounter outcomes of death (15/24, 63% respondents identified as useful), escalation of care (20/24, 83%), and return to ED (16/24, 67%) were determined high yield for demonstrating proof-of-concept in our LOOP application. The studio aided the design and development of LOOP, which integrated physicians throughout the design and content iteration. A final LOOP prototype enabled usability evaluation and iterative refinement prior to launch. Usability evaluation compared to status quo (ie, pre-LOOP) feedback gathering practices demonstrated a shift across all outcomes from "not easy" to "very easy" to obtain and from "not confident" to "very confident" in estimating outcomes after using LOOP. On a scale from 0 (unlikely) to 10 (most likely), the users were very likely (9.5) to recommend LOOP to a colleague.
This study demonstrates the potential for human-centered design of a patient outcomes-driven feedback platform for individual EM providers. We have outlined a framework for working alongside clinicians with a multidisciplined team to develop and test a tool that augments their clinical experience and enables closed-loop learning.
在急诊科等非连续性护理环境中,基于患者结局的反馈的可得性有限。急诊医学(EM)临床医生为大多数住院患者设定护理轨迹,并为更多出院回到社区的患者提供确定性治疗。EM临床医生通常并不了解患者的短期和长期健康结局,以及他们的行为可能对此产生的影响。尽管患者数量众多且数据丰富,但针对个体临床医生经验的以结局为导向的学习却很少。集成电子健康记录(EHR)系统提供了机会,但它们没有易于获取的用于基于结局的学习的功能。
本研究旨在通过为EM临床医生开发一个可个性化的患者结局反馈平台,从常规收集的EHR数据中挖掘见解。在此,我们描述了该平台“患者结局关联(LOOP)”在以人为主的设计框架下的迭代开发过程,包括从其使用中获得的结构化反馈。
在2019年8月至2021年2月期间进行了这项多模式研究,包括以人为主的设计工作室、调查(24名医生)、访谈(11名医生)以及一次LOOP应用可用性评估(12名EM医生,每人≥30分钟)。该研究跨越三个阶段:(1)在以人为主的设计框架下进行概念开发;(2)LOOP技术平台开发;(3)可用性评估,比较EHR中使用LOOP前后的反馈收集实践。
最初的以人为主的设计工作室和EM临床医生调查揭示了EM临床医生与患者在诊疗后存在脱节的共同主题。确定死亡(15/24,63%的受访者认为有用)、护理升级(20/24,83%)和重返急诊科(16/24,67%)等基本诊疗后结局对于在我们的LOOP应用中展示概念验证具有很高的价值。该工作室有助于LOOP的设计和开发,在整个设计和内容迭代过程中让医生参与其中。最终的LOOP原型在推出前进行了可用性评估和迭代优化。与现状(即使用LOOP前)反馈收集实践相比,可用性评估表明,在使用LOOP后,所有结局在获取方面都从“不容易”转变为“非常容易”,在估计结局方面从“不自信”转变为“非常自信”。在从0(不太可能)到10(最有可能)的量表上,用户非常有可能(9.5)向同事推荐LOOP。
本研究证明了以人为主设计一个针对个体EM提供者的以患者结局为驱动的反馈平台的潜力。我们概述了一个与临床医生和多学科团队合作开发和测试一种工具的框架,该工具可增强他们的临床经验并实现闭环学习。