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Setting Up a Stroke Team Algorithm and Conducting Simulation-based Training in the Emergency Department - A Practical Guide

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Physician, know thyself: implicit and explicit decision-making for mechanical thrombectomy in stroke.

Kyle M Fargen¹, Thabele M Leslie-Mazwi², Michael Chen³

¹Department of Neurological Surgery, Wake Forest University, Winston-Salem, North Carolina, USA kfargen@wakehealth.edu.

Journal of Neurointerventional Surgery

|May 6, 2020

Summary

This summary is machine-generated.

Selecting acute stroke patients for mechanical thrombectomy (MT) is critical. Understanding cognitive biases in physician decision-making can improve patient outcomes and treatment selection for emergent large vessel occlusion.

Keywords:

Intervention Stroke Thrombectomy

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Area of Science:

Neurology
Medical Decision-Making
Cognitive Psychology

Background:

Mechanical thrombectomy (MT) offers significant benefits for acute stroke patients with emergent large vessel occlusion.
Despite successful reperfusion, many patients experience persistent neurologic deficits, highlighting the complexity of MT selection.
Clinical decisions for MT are often made under pressure with incomplete information.

Purpose of the Study:

To review the cognitive mechanisms influencing physician decisions regarding mechanical thrombectomy for acute stroke.
To identify prominent cognitive biases affecting judgment in MT selection.
To explore strategies for improving decision-making quality in time-sensitive stroke care.

Main Methods:

Review of literature on cognitive errors and biases in medical decision-making.
Application of dual process theory (System 1 and System 2) to physician judgment in MT.
Analysis of factors influencing MT decisions, including confidence and aggressiveness.

Main Results:

Physician decisions in MT selection are susceptible to implicit (System 1) cognitive biases due to rapid, heuristic-based processing.
Factors such as confidence, decisional stress, and incomplete data can exacerbate bias.
Understanding these biases is crucial for optimizing the application of MT.

Conclusions:

Cognitive biases significantly impact the selection of acute stroke patients for mechanical thrombectomy.
Implementing strategies to mitigate bias can enhance the accuracy and effectiveness of MT decisions.
Improved decision-making processes are essential for maximizing functional outcomes in stroke patients undergoing MT.