Zarzeczny Amy, Babyn Paul, Adams Scott J, Longo Justin
Johnson Shoyama Graduate School of Public Policy, 6846University of Regina, Regina, Saskatchewan, Canada.
Department of Medical Imaging, Saskatchewan Health Authority, Saskatoon City Hospital, Saskatoon, Saskatchewan, Canada.
Healthc Manage Forum. 2021 May;34(3):169-174. doi: 10.1177/0840470420975062. Epub 2020 Dec 10.
Lung cancer is a leading cause of cancer death in Canada, and accurate, early diagnosis are critical to improving clinical outcomes. Artificial Intelligence (AI)-based imaging analytics are a promising healthcare innovation that aim to improve the accuracy and efficiency of lung cancer diagnosis. Maximizing their clinical potential while mitigating their risks and limitations will require focused leadership informed by interdisciplinary expertise and system-wide insight. We convened a knowledge exchange workshop with diverse Saskatchewan health system leaders and stakeholders to explore issues surrounding the use of AI in diagnostic imaging for lung cancer, including implementation opportunities, challenges, and priorities. This technology is anticipated to improve patient outcomes, reduce unnecessary healthcare spending, and increase knowledge. However, health system leaders must also address the needs for robust data, financial investment, effective communication and collaboration between healthcare sectors, privacy and data protections, and continued interdisciplinary research to achieve this technology's potential benefits.
肺癌是加拿大癌症死亡的主要原因，准确的早期诊断对于改善临床结果至关重要。基于人工智能（AI）的影像分析是一项有前景的医疗创新，旨在提高肺癌诊断的准确性和效率。要在降低风险和局限性的同时最大化其临床潜力，需要具备跨学科专业知识和全系统洞察力的有力领导。我们召集了萨斯喀彻温省卫生系统的不同领导人和利益相关者参加知识交流研讨会，以探讨在肺癌诊断成像中使用人工智能的相关问题，包括实施机会、挑战和优先事项。预计这项技术将改善患者预后、减少不必要的医疗支出并增加知识。然而，卫生系统领导人还必须满足对强大数据、资金投入、医疗部门之间有效的沟通与协作、隐私和数据保护以及持续的跨学科研究的需求，以实现这项技术的潜在益处。
