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Updated: Sep 20, 2025

Modeling Brain Metastases Through Intracranial Injection and Magnetic Resonance Imaging

Modeling Brain Metastases Through Intracranial Injection and Magnetic Resonance Imaging

Published on: June 7, 2020

Modeling anesthesia medication delivery using the SEIPS 101 tools.

Elise DeForest¹, Ken Catchpole², Connor Lusk²

¹College of Medicine, Medical University of South Carolina, Charleston, SC, USA.

Applied Ergonomics

|May 23, 2025

Summary

This summary is machine-generated.

Patient safety during anesthesia medication delivery is crucial. This study used Systems Engineering Initiative for Patient Safety (SEIPS) tools to map complex anesthesia medication systems, identifying key interactions and potential risks.

Keywords:

Anesthesia medication delivery Human factors SEIPS SEIPS 101 Systems safety

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Area of Science:

Anesthesiology
Patient Safety
Systems Engineering

Background:

Patient harm during anesthesia medication administration is a persistent safety concern.
The Systems Engineering Initiative for Patient Safety (SEIPS) offers tools to analyze complex clinical systems.
Mapping perioperative medication delivery systems is essential for improving patient safety.

Purpose of the Study:

To apply SEIPS 101 tools to map and understand the complexity of anesthesia medication delivery systems.
To identify facilitators and barriers within the anesthesia care delivery system.
To enhance awareness of system limitations and improve interventions for patient safety.

Main Methods:

Direct observation of 38 anesthetics (over 100 hours) focusing on provider tasks and interactions.
Utilized SEIPS 101 tools including Anesthesia PETT Scan, People Map, Task x Tools Matrix, Journey Map, Anesthesia Work System Interactions Map, and Outcome Matrix.
Integrated observation data, notes, interviews, and literature review to create system maps.

Main Results:

Developed six SEIPS 101 tools illustrating the complexity of anesthesia medication delivery.
The Anesthesia PETT Scan highlighted provider differences and conflicts.
Maps detailed interactions with people, environment, tools, and tasks, revealing system complexity and stakeholder outcomes.

Conclusions:

Understanding the complexity of the anesthesia care delivery system is critical for effective interventions.
This systems analysis can improve methods for understanding errors, safety, clinical expertise, and decision-making.
Increased awareness of system limitations can lead to improved patient safety in perioperative settings.