Gandhi Tejal K, Classen David, Sinsky Christine A, Rhew David C, Vande Garde Nikki, Roberts Andrew, Federico Frank
Press Ganey Associates LLC, Boston, MA 02109, United States.
Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT 84132, United States.
JAMIA Open. 2023 Aug 29;6(3):ooad079. doi: 10.1093/jamiaopen/ooad079. eCollection 2023 Oct.
Artificial intelligence (AI) has tremendous potential to improve the cognitive and work burden of clinicians across a range of clinical activities, which could lead to reduced burnout and better clinical care. The recent explosion of generative AI nicely illustrates this potential. Developers and organizations deploying AI have a responsibility to ensure AI is designed and implemented with end-user input, has mechanisms to identify and potentially reduce bias, and that the impact on cognitive and work burden is measured, monitored, and improved. This article focuses specifically on the role AI can play in reducing cognitive and work burden, outlines the critical issues associated with the use of AI, and serves as a call to action for vendors and users to work together to develop functionality that addresses these challenges.
人工智能（AI）在一系列临床活动中具有巨大潜力，可改善临床医生的认知负担和工作负担，这可能会减少职业倦怠并提供更好的临床护理。最近生成式人工智能的爆发很好地说明了这种潜力。部署人工智能的开发者和组织有责任确保人工智能在终端用户的参与下进行设计和实施，具备识别并可能减少偏差的机制，并且要对其对认知负担和工作负担的影响进行测量、监测和改进。本文特别关注人工智能在减轻认知负担和工作负担方面可发挥的作用，概述了与使用人工智能相关的关键问题，并呼吁供应商和用户共同努力开发应对这些挑战的功能。
