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关于探讨“为何”的定性主题分析:一场医疗保健领域的人工智能研讨会

A Qualitative Thematic Analysis of Addressing the Why: An Artificial Intelligence (AI) in Healthcare Symposium.

作者信息

Borgstadt Joshua T, Kalpas Edward A, Pond Hayden M

机构信息

Medical Science, A.T. Still University, Phoenix, USA.

Clinical Informatics, Academic Affairs, HonorHealth and College of Health Solutions, Arizona State University, Scottsdale, USA.

出版信息

Cureus. 2022 Mar 31;14(3):e23704. doi: 10.7759/cureus.23704. eCollection 2022 Mar.

Abstract

Healthcare managers and clinicians are inefficient in the processes of workflows and documentation. The inefficiency is due in part by increasing demands of insurance companies, regulatory demands from the government, and human error. Artificial intelligence (AI) can improve healthcare processes by decreasing variability, thus improving patient and physician experience and patient outcomes. This project brings together a panel of five experts to discuss problems in medicine and some of the tools available through AI and technology to address these problems. The symposium modeled a "flipped classroom" format. The first five 20-minute modules were uploaded to a web-based platform for viewing in advance of the 60-minute moderated roundtable (Zoom, Zoom Video Communications, San Jose, CA, USA). The following themes emerged after reviewing the transcribed data: data privacy and access (N=3, number of times identified); process improvement (N=2); physician experience (N=1); value in data (N=2); and bias in healthcare and AI (N=3). For AI to become implemented on a large scale in healthcare, many areas will need continued discussion and research, including a continued look into how AI can add value to workflow and knowledge augmentation. In addition, standards for the implementation of AI and a methodical approach to the analysis of the effectiveness of algorithms coupled with training of healthcare professionals in the language of AI algorithms will be helpful to ensure that AI is integrated safely.

摘要

医疗保健管理人员和临床医生在工作流程和文档记录过程中效率低下。这种低效率部分归因于保险公司需求的增加、政府的监管要求以及人为错误。人工智能(AI)可以通过减少变异性来改善医疗保健流程,从而改善患者和医生的体验以及患者的治疗效果。该项目召集了一个由五位专家组成的小组,讨论医学中的问题以及一些可通过人工智能和技术来解决这些问题的工具。该研讨会采用了“翻转课堂”的形式。前五个20分钟的模块被上传到一个基于网络的平台上,以便在美国加利福尼亚州圣何塞市的Zoom视频通信公司主持的60分钟圆桌会议之前进行观看。在审查转录数据后出现了以下主题:数据隐私和访问(N = 3,识别次数);流程改进(N = 2);医生体验(N = 1);数据价值(N = 2);以及医疗保健和人工智能中的偏差(N = 3)。为了使人工智能在医疗保健领域大规模实施,许多领域需要持续的讨论和研究,包括持续研究人工智能如何为工作流程和知识扩充增加价值。此外,人工智能实施的标准以及对算法有效性进行分析的系统方法,再加上用人工智能算法语言对医疗保健专业人员进行培训,将有助于确保人工智能的安全集成。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/afcd/9060766/ef50d5f81b0c/cureus-0014-00000023704-i01.jpg

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