Department of Anesthesiology, Larner College of Medicine, University of Vermont, Burlington, Vermont.
Department of Anesthesiology and Perioperative Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama.
Curr Opin Anaesthesiol. 2024 Aug 1;37(4):406-412. doi: 10.1097/ACO.0000000000001382. Epub 2024 May 3.
Given the rapid growth of nonoperating room anesthesia (NORA) in recent years, it is essential to review its unique challenges as well as strategies for patient selection and care optimization.
Recent investigations have uncovered an increasing prevalence of older and higher ASA physical status patients in NORA settings. Although closed claim data regarding patient injury demonstrate a lower proportion of NORA cases resulting in a claim than traditional operating room cases, NORA cases have an increased risk of claim for death. Challenges within NORA include site-specific differences, limitations in ergonomic design, and increased stress among anesthesia providers. Several authors have thus proposed strategies focusing on standardizing processes, site-specific protocols, and ergonomic improvements to mitigate risks.
Considering the unique challenges of NORA settings, meticulous patient selection, risk stratification, and preoperative optimization are crucial. Embracing data-driven strategies and leveraging technological innovations (such as artificial intelligence) is imperative to refine quality control methods in targeted areas. Collaborative efforts led by anesthesia providers will ensure personalized, well tolerated, and improved patient outcomes across all phases of NORA care.
近年来，非手术室麻醉（NORA）迅速发展，因此有必要对其独特的挑战以及患者选择和护理优化策略进行综述。
最近的研究发现，在 NORA 环境中，老年和更高 ASA 身体状况的患者比例不断增加。尽管关于患者伤害的封闭索赔数据表明，与传统手术室病例相比，NORA 病例导致索赔的比例较低，但 NORA 病例死亡索赔的风险增加。NORA 面临的挑战包括特定地点的差异、工效学设计的局限性以及麻醉提供者的压力增加。因此，一些作者提出了一些策略，重点是标准化流程、特定地点的协议和工效学改进，以降低风险。
考虑到 NORA 环境的独特挑战，细致的患者选择、风险分层和术前优化至关重要。采用数据驱动的策略并利用人工智能等技术创新对于改进特定领域的质量控制方法至关重要。由麻醉提供者牵头的合作努力将确保在 NORA 护理的所有阶段实现个性化、耐受性好和改善的患者结局。
