Owoyemi Ayomide, Okpara Ebere, Salwei Megan, Boyd Andrew
Department of Biomedical and Health Informatics, University of Illinois at Chicago, Chicago, IL 60612, United States.
Department of Pharmacy Systems, Outcomes and Policy, University of Illinois at Chicago, Chicago, IL 60612, United States.
JAMIA Open. 2024 Oct 7;7(4):ooae096. doi: 10.1093/jamiaopen/ooae096. eCollection 2024 Dec.
Research on the Epic Sepsis System (ESS) has predominantly focused on technical accuracy, neglecting the user experience of healthcare professionals. Understanding these experiences is crucial for the design of Artificial Intelligence (AI) systems in clinical settings. This study aims to explore the socio-technical dynamics affecting ESS adoption and use, based on user perceptions and experiences.
Resident doctors and nurses with recent ESS interaction were interviewed using purposive sampling until data saturation. A content analysis was conducted using Dedoose software, with codes generated from Sittig and Singh's and Salwei and Carayon's frameworks, supplemented by inductive coding for emerging themes.
Interviews with 10 healthcare providers revealed mixed but generally positive or neutral perceptions of the ESS. Key discussion points included its workflow integration and usability. Findings were organized into 2 main domains: workflow fit, and usability and utility, highlighting the system's seamless electronic health record integration and identifying design gaps.
This study offers insights into clinicians' experiences with the ESS, emphasizing the socio-technical factors that influence its adoption and effective use. The positive reception was tempered by identified design issues, with clinician perceptions varying by their professional experience and frequency of ESS interaction.
The findings highlight the need for ongoing ESS refinement, emphasizing a balance between technological advancement and clinical practicality. This research contributes to the understanding of AI system adoption in healthcare, suggesting improvements for future clinical AI tools.
对重症脓毒症系统(ESS)的研究主要集中在技术准确性上,而忽视了医疗保健专业人员的用户体验。了解这些体验对于临床环境中人工智能(AI)系统的设计至关重要。本研究旨在基于用户的认知和体验,探索影响ESS采用和使用的社会技术动态。
采用目的抽样法对近期与ESS有交互的住院医生和护士进行访谈,直至数据饱和。使用Dedoose软件进行内容分析,代码来自西蒂格和辛格以及萨尔韦和卡拉扬的框架,并辅以对新出现主题的归纳编码。
对10名医疗保健提供者的访谈显示,他们对ESS的看法不一,但总体上是积极或中性的。关键讨论点包括其工作流程整合和可用性。研究结果分为两个主要领域:工作流程适配性以及可用性和实用性,突出了该系统无缝的电子健康记录整合,并识别出设计差距。
本研究深入了解了临床医生使用ESS的体验,强调了影响其采用和有效使用的社会技术因素。已识别出的设计问题削弱了积极的反馈,临床医生的认知因其专业经验和与ESS交互的频率而异。
研究结果凸显了持续改进ESS的必要性,强调了技术进步与临床实用性之间的平衡。这项研究有助于理解医疗保健领域中AI系统的采用情况,为未来临床AI工具的改进提供了建议。