PDF(Pubmed)
Abstract：
UNASSIGNED: Artificial intelligence (AI) enabled tools have been proposed as 1 solution to improve health care delivery. However, research on downstream effects of AI integration into the clinical workflow is lacking.
UNASSIGNED: We aim to analyze how integration of an automated basal cell carcinoma detection and tumor mapping algorithm in a Mohs micrographic surgery unit impacts the work efficiency of clinical and laboratory staff.
UNASSIGNED: Slide, staff, and histotechnician waiting times were analyzed over a 20-day period in a Mohs micrographic surgery unit. A simulated AI workflow was created and the time differences between the real and simulated workflows were compared.
UNASSIGNED: Simulated nonautonomous algorithm integration led to savings of 35.6% of slide waiting time, 18.4% of staff waiting time, and 18.6% of histotechnician waiting time per day. Algorithm integration on days with increased reconstruction complexity resulted in the greatest time savings.
UNASSIGNED: One Mohs micrographic surgery unit was analyzed and simulated AI integration was performed retrospectively.
UNASSIGNED: AI integration results in reduced staff waiting times, enabling increased productivity and a streamlined clinical workflow. Schedules containing surgical cases with either increased repair complexity or numerous tumor removal stages stand to benefit most. However, significant logistical challenges must be addressed before broad adoption into clinical practice is realistic.
UNASSIGNED: We aim to analyze how integration of an automated basal cell carcinoma detection and tumor mapping algorithm in a Mohs micrographic surgery unit impacts the work efficiency of clinical and laboratory staff.
UNASSIGNED: Slide, staff, and histotechnician waiting times were analyzed over a 20-day period in a Mohs micrographic surgery unit. A simulated AI workflow was created and the time differences between the real and simulated workflows were compared.
UNASSIGNED: Simulated nonautonomous algorithm integration led to savings of 35.6% of slide waiting time, 18.4% of staff waiting time, and 18.6% of histotechnician waiting time per day. Algorithm integration on days with increased reconstruction complexity resulted in the greatest time savings.
UNASSIGNED: One Mohs micrographic surgery unit was analyzed and simulated AI integration was performed retrospectively.
UNASSIGNED: AI integration results in reduced staff waiting times, enabling increased productivity and a streamlined clinical workflow. Schedules containing surgical cases with either increased repair complexity or numerous tumor removal stages stand to benefit most. However, significant logistical challenges must be addressed before broad adoption into clinical practice is realistic.
摘要：
■支持人工智能（AI）的工具已被提议作为改善医疗保健服务的1个解决方案。然而,缺乏对人工智能整合到临床工作流程中的下游影响的研究。
■我们旨在分析Mohs显微手术单元中自动基底细胞癌检测和肿瘤映射算法的集成如何影响临床和实验室人员的工作效率。
■幻灯片，工作人员,在Mohs显微外科单元中分析了20天期间和组织技术人员的等待时间。创建了模拟的AI工作流，并比较了真实工作流和模拟工作流之间的时间差。
■模拟非自治算法集成可节省35.6%的滑梯等待时间，18.4%的员工等待时间，和18.6%的组织技术人员每天等待时间。在具有增加的重建复杂度的日子中进行算法集成可以最大程度地节省时间。
■分析了一个Mohs显微手术单元，并回顾性地进行了模拟AI整合。
■人工智能整合导致员工等待时间减少，能够提高生产率和简化的临床工作流程。包含具有增加的修复复杂性或多个肿瘤切除阶段的手术病例的时间表最受益。然而,在广泛采用临床实践成为现实之前，必须解决重大的后勤挑战。
■我们旨在分析Mohs显微手术单元中自动基底细胞癌检测和肿瘤映射算法的集成如何影响临床和实验室人员的工作效率。
■幻灯片，工作人员,在Mohs显微外科单元中分析了20天期间和组织技术人员的等待时间。创建了模拟的AI工作流，并比较了真实工作流和模拟工作流之间的时间差。
■模拟非自治算法集成可节省35.6%的滑梯等待时间，18.4%的员工等待时间，和18.6%的组织技术人员每天等待时间。在具有增加的重建复杂度的日子中进行算法集成可以最大程度地节省时间。
■分析了一个Mohs显微手术单元，并回顾性地进行了模拟AI整合。
■人工智能整合导致员工等待时间减少，能够提高生产率和简化的临床工作流程。包含具有增加的修复复杂性或多个肿瘤切除阶段的手术病例的时间表最受益。然而,在广泛采用临床实践成为现实之前，必须解决重大的后勤挑战。
