使用SEIPS 101工具对麻醉药物给药进行建模

Modeling anesthesia medication delivery using the SEIPS 101 tools

Applied Ergonomics · 2025
被引 3
ABS 3

中文导读

通过直接观察38次麻醉过程(超100小时),运用SEIPS 101工具创建六种图表,展示麻醉药物给药的复杂性,帮助识别系统障碍与促进因素,为改进安全干预提供依据。

Abstract

BACKGROUND: Reducing the risk of patient harm during anesthesia medication administration in perioperative settings has been a long-term goal in patient safety. SEIPS 101 tools, provide a series of practice-orientated techniques to apply systems model in real clinical practice, potentially offering a straightforward approach to mapping perioperative medication delivery systems. Data was collected during direct observations of thirty-eight anesthetics, totaling over 100 h on anesthesia providers' common tasks and interactions with people, environments, tools, and technologies. Observation data, notes, interviews, and literature were organized to create six SEIPS 101 tools demonstrating the complexity of anesthesia medication delivery. The Anesthesia PETT Scan represents the facilitators and barriers associated with differences in individual expertise, preferences, and potential conflict between providers. The People Map demonstrates the wide range of relevant individuals in medication delivery. The Task x Tools Matrix depicts the broad range of interconnected processes to provide anesthesia. The Journey Map describes the path used to deliver a medication. The Anesthesia Work System Interactions Map identifies necessary interactions that providers have with tools, tasks, people, and environment for successful anesthetics. The Outcome Matrix describes various stakeholder experiences and outcomes that contribute to overall system complexity. Identifying and describing the complexity in the anesthesia care delivery system is critical for effective and efficient process-centric interventions. This systems analysis may increase awareness to the limitations of current approaches and improve upon methods and interventions for understanding errors, safety, and the nature of clinical expertise and decision making.

患者安全麻醉学系统建模围手术期护理