AI: Promise or Peril for Patient Safety.

IF 1.7 3区 医学 Q3 HEALTH CARE SCIENCES & SERVICES Journal of Patient Safety Pub Date : 2025-01-01 Epub Date: 2024-11-25 DOI:10.1097/PTS.0000000000001301
Beth Daley Ullem, Martin J Hatlie, Olivia Lounsbury
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引用次数: 0

Abstract

Abstract: Patient safety advocates identify concerns for the impact of AI on patient safety. Patients identified the following 4 main areas that AI developers, regulatory bodies, and clinical users of AI are asked to consider: data integrity and bias, efficacy, payment, and transparency toward shared learning. Increased patient involvement in the development, use assessment and oversight of the technology is critical to ensure trust and trustworthiness in the use of AI in patient care.

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人工智能:患者安全的希望还是危险?
摘要:患者安全倡导者对人工智能对患者安全的影响表示担忧。患者提出了要求人工智能开发商、监管机构和人工智能临床用户考虑的以下 4 个主要方面:数据完整性和偏差、疗效、支付和共享学习的透明度。加强患者对技术开发、使用评估和监督的参与,对于确保在患者护理中使用人工智能的信任度和可信度至关重要。
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来源期刊
Journal of Patient Safety
Journal of Patient Safety HEALTH CARE SCIENCES & SERVICES-
CiteScore
4.60
自引率
13.60%
发文量
302
期刊介绍: Journal of Patient Safety (ISSN 1549-8417; online ISSN 1549-8425) is dedicated to presenting research advances and field applications in every area of patient safety. While Journal of Patient Safety has a research emphasis, it also publishes articles describing near-miss opportunities, system modifications that are barriers to error, and the impact of regulatory changes on healthcare delivery. This mix of research and real-world findings makes Journal of Patient Safety a valuable resource across the breadth of health professions and from bench to bedside.
期刊最新文献
From Missed Appointments to Missed Opportunities: The Patient Safety Challenge. SCALPEL: A Structured Handoff Protocol for Scrub Nurses in the Operating Room for Patient Safety. Application of the IMB Model in the Vision of Zero Harm Caused by Magnetic Resonance Ferromagnetic Projection Accidents. Intelligent Verification Tool for Surgical Information of Ophthalmic Patients: A Study Based on Artificial Intelligence Technology. Implementation of a Standardized Tool for Root Cause Analysis Selection.
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