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机构整合中选择人工智能解决方案的战略考量:单中心经验

Strategic Considerations for Selecting Artificial Intelligence Solutions for Institutional Integration: A Single-Center Experience.

作者信息

Pascoe Janice L, Lu Luqing, Moore Matthew M, Blezek Daniel J, Ovalle Annie E, Linderbaum Jane A, Callstrom Matthew R, Williamson Eric E

机构信息

Department of Information Technology, Mayo Clinic, Rochester, MN.

Strategy Department, Mayo Clinic, Phoenix, AZ.

出版信息

Mayo Clin Proc Digit Health. 2024 Nov 5;2(4):665-676. doi: 10.1016/j.mcpdig.2024.10.004. eCollection 2024 Dec.

Abstract

Artificial intelligence (AI) promises to revolutionize health care. Early identification of disease, appropriate test selection, and automation of repetitive tasks are expected to optimize cost-effective care delivery. However, pragmatic selection and integration of AI algorithms to enable this transformation remain challenging. Health care leaders must navigate complex decisions regarding AI deployment, considering factors such as cost of implementation, benefits to patients and providers, and institutional readiness for adoption. A successful strategy needs to align AI adoption with institutional priorities, select appropriate algorithms to be purchased or internally developed, and ensure adequate support and infrastructure. Further, successful deployment requires algorithm validation and workflow integration to ensure efficacy and usability. User-centric design principles and usability testing are critical for AI adoption, ensuring seamless integration into clinical workflows. Once deployed, continuous improvement processes and ongoing algorithm support ensure continuous benefits to the clinical practice. Vigilant planning and execution are necessary to navigate the complexities of AI implementation in the health care environment. By applying the framework outlined in this article, institutions can navigate the ever-evolving and complex environment of AI in health care to maximize the benefits of these innovative technologies.

摘要

人工智能有望给医疗保健带来变革。疾病的早期识别、恰当的检查选择以及重复性任务的自动化有望优化具有成本效益的医疗服务提供。然而,切实选择和整合人工智能算法以实现这一转变仍然具有挑战性。医疗保健领导者在进行人工智能部署时必须做出复杂决策,要考虑实施成本、对患者和医疗服务提供者的益处以及机构对采用人工智能的准备情况等因素。一项成功的策略需要使人工智能的采用与机构优先事项保持一致,选择合适的算法进行购买或内部开发,并确保有足够的支持和基础设施。此外,成功部署需要算法验证和工作流程整合,以确保有效性和可用性。以用户为中心的设计原则和可用性测试对于人工智能的采用至关重要,可确保无缝融入临床工作流程。一旦部署,持续改进流程和持续的算法支持可确保临床实践持续受益。在医疗保健环境中应对人工智能实施的复杂性,谨慎的规划和执行是必要的。通过应用本文概述的框架,机构能够在医疗保健领域不断发展且复杂的人工智能环境中前行,以最大限度地发挥这些创新技术的益处。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c04/11975996/de87dcf5f0d7/gr1.jpg

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