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"Talk-Through Walk-Through"-A Simulation Approach Adapted During Preparation for COVID-19
Matthew Lee1, Stephanie Chen, Shervin Tosif
1From the Department of Anesthesia, Austin Health, Melbourne, Victoria, Australia.
Summary
Talk-through walk-through is an efficient simulation method for improving complex patient care systems. This approach rapidly develops and tests processes, proving valuable for managing COVID-19 patient care.
Area of Science:
- Healthcare Systems Engineering
- Patient Safety
- Clinical Process Improvement
Background:
- Complex patient care systems require robust development and testing.
- The COVID-19 pandemic necessitated rapid adaptation of care processes.
- Existing methods may not adequately address time and resource constraints.
Purpose of the Study:
- To adapt and apply the talk-through walk-through simulation format for developing and testing patient care processes.
- To enhance the safe management of COVID-19 patients.
- To evaluate the efficiency of the talk-through walk-through approach in resource-limited settings.
Main Methods:
- Adapted the talk-through walk-through simulation format from task analysis literature.
- Paired a 'talk-through' phase (identifying process issues, building shared mental models) with a 'walk-through' phase (testing solutions, uncovering challenges).
- Applied the method to develop and test processes for COVID-19 patient management.
Main Results:
- The talk-through walk-through enabled rapid identification and resolution of major process issues.
- The approach successfully uncovered unanticipated system and process challenges during testing.
- Process development and testing were achieved within a single session.
Conclusions:
- Talk-through walk-through is an effective simulation format for the rapid development and improvement of complex patient care systems.
- This method is particularly valuable for multi-disciplinary, multi-location care settings with time scarcity, such as during the COVID-19 pandemic.
- The approach facilitates the creation of shared mental models and robust process testing.
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