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The SIM-QI Framework: Embedding Simulation Into Quality Improvement Infrastructure.

Created on 04 Nov 2026

Authors

Farrukh N Jafri, Kenay Johnson, Christina J Yang, Roger A Edwards

Published in

Simulation in healthcare : journal of the Society for Simulation in Healthcare. Nov 02, 2026. Epub Nov 02, 2026.

Abstract

Health care simulation has matured as an educational modality, yet a persistent gap remains between simulation-based learning and measurable clinical improvement. Translational simulation offers a conceptual bridge, but the field lacks a practical methodology for embedding simulation within existing quality improvement (QI) infrastructure. This paper presents the Simulation-Quality Integration (SIM-QI) Framework, a structured approach that maps simulation onto 3 phases of QI work (Discovery, Intervention, and Sustainment) encompassing 5 steps, grounded in the Donabedian model, Deming's System of Profound Knowledge, the Model for Improvement, Lean principles, and the PEARLS for Systems Integration debriefing framework. Rather than positioning simulation as a standalone educational intervention, the framework operationalizes simulation as both a diagnostic tool for auditing processes and identifying latent safety threats, and as a vehicle for testing and implementing changes. When education is identified as a genuine need, the framework recommends active learning strategies paired with structural supports. Equity is integrated at every step, with process measures stratified by relevant demographic variables where data permit. The framework was derived iteratively from a decade of programmatic QI work spanning pediatric tracheostomy safety, COVID-19 airway management, cardiac catheterization laboratory safety, hemorrhage control, and AI-powered telehealth training, together with nonsimulation QI programs that applied the same methodology. This body of work supports individual components of the framework; the complete framework has not been prospectively evaluated, and its contribution is therefore presented as potential rather than demonstrated. A supplemental toolkit provides ready-to-use templates for each step.

PMID:
42976122
Bibliographic data and abstract were imported from PubMed on 04 Nov 2026.

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