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一种适用于数字病理学实施的经过调整和改进的验证方案。

An adapted & improved validation protocol for digital pathology implementation.

作者信息

Hsu Ying-Han R, Ahmed Iman, Phlamon Juliana, Carment-Baker Charlotte, Chan Joyce Yin Tung, Prassas Ioannis, Weiser Karen, Zeidan Shaza, Clarke Blaise, Yousef George M

机构信息

Laboratory Medicine Program, University Health Network, Toronto, ON Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON Canada.

Laboratory Medicine Program, University Health Network, Toronto, ON Canada; Office of Strategy Management, University Health Network, Toronto, ON Canada.

出版信息

Semin Diagn Pathol. 2025 Jul;42(4):150905. doi: 10.1016/j.semdp.2025.150905. Epub 2025 Apr 15.

Abstract

Digital Pathology (DP) is transforming disease diagnosis by providing rapid and efficient analysis of tissue samples. However, ensuring the accuracy and reliability of diagnoses is crucial. This manuscript outlines University Health Network (UHN)'s journey towards the development of a customized validation protocol for implementing a digital workflow for primary clinical assessment. Drawing on guidelines from the Royal College of Pathologists (RCPath) UK and the College of American Pathologists (CAP), UHN has tailored its approach to accommodate the unique needs of its 14 subspecialty groups. Our protocol emphasizes pathologist-led self-validation, integration of diverse subspecialty cases, and a phased rollout with continuous monitoring. Additionally, the use of change management principles inspired by Leeds University (CCP) played a critical role in guiding the process, ensuring pathologists' comfort with digital workflows, and addressing subspecialty-specific challenges. This comprehensive validation protocol supports UHN's broader goals of leveraging DP for clinical practice while ensuring patient safety and data integrity.

摘要

数字病理学(DP)通过对组织样本进行快速高效的分析,正在改变疾病诊断方式。然而,确保诊断的准确性和可靠性至关重要。本手稿概述了大学健康网络(UHN)为制定定制化验证方案以实施用于初级临床评估的数字工作流程所经历的过程。借鉴英国皇家病理学家学院(RCPath)和美国病理学家学会(CAP)的指南,UHN调整了其方法,以满足其14个亚专业组的独特需求。我们的方案强调由病理学家主导的自我验证、整合不同亚专业病例以及分阶段推出并持续监测。此外,受利兹大学(CCP)启发的变革管理原则的运用在指导该过程、确保病理学家对数字工作流程的适应度以及应对亚专业特定挑战方面发挥了关键作用。这一全面的验证方案支持UHN利用数字病理学进行临床实践的更广泛目标,同时确保患者安全和数据完整性。

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