Simulation Maturity Assessment Tool: a metric for organizational maturity

The Simulation Maturity Assessment Tool (SMAT) is an innovative model for measuring the level of integration of simulation in clinical, organizational, and risk management processes. Based on a structured questionnaire and a six-dimensional analysis, SMAT helps healthcare organizations understand their simulation maturity and guide continuous improvement strategies. A tool for self-assessment and growth, it serves as a compass for enhancing safety, a culture of resilience, and systemic learning in hospitals.

Introduction

Simulation in healthcare is no longer just a training method: it has become a strategic lever for improving the safety, quality, and resilience of hospital systems. (Nickson et al, 2021) But how can we understand how “mature” an organization really is in using simulation as a tool for risk management and continuous learning?

To answer this question, the Simulation Maturity Assessment Tool (SMAT) was created, an innovative self-assessment model developed by the Quality and Patient Safety Service of the Regional Hospital of Bellinzona and Valleys (ORBV) in collaboration with the Simulation Center (CeSi) of the Professional Medical-Technical Social-Health Center (CPS-MT) in Lugano. SMAT measures the degree of integration of simulation into clinical and organizational processes, providing a compass for systemic improvement.

Simulation at the service of clinical risk

From maturity models to healthcare simulation

Maturity models are organizational management tools that allow the level of development and integration of processes and skills within an organization to be assessed. Widespread in many sectors, they are also increasingly used in healthcare, where they help to understand how capable a hospital is of improving systematically, moving from fragmented practices to structured and sustainable processes over time. As Chassin and Loeb (2013) state, maturity models are self-assessment tools that allow organizations to measure their level of development, identify areas for improvement, and promote a process of continuous growth.

A recent review from 2024 (Aiwerioghene et al, 2024) identified 19 maturity models useful for hospital management. These models help organizations evaluate and improve their performance, particularly in complex contexts such as hospitals, where it is necessary to balance quality, safety, efficiency, and economic sustainability.

This review highlights some significant examples, such as the following:

• High Reliability Health Care Maturity Model (HRHCM): assesses a hospital’s ability to become a high-reliability organization, with safety-oriented leadership, sustainable processes, and continuous improvement.
• Healthcare Analytics Adoption Model (HAAM): measures the use of data and predictive analytics to optimize care and reduce costs.
• Continuity of Care Maturity Model (CCMM): assesses the ability to coordinate care across multiple settings and professionals.
• Business Process Orientation Maturity Model (BPOMM): helps to understand how integrated and improvement-oriented clinical and organizational processes are.

All these models share one principle: a mature organization is one that learns from itself and systematizes improvement processes.

From simulation to organizational maturity

The Simulation Maturity Assessment Tool (SMAT) was developed based on this same logic by the Quality and Patient Safety Service of the Bellinzona and Valli Regional Hospital (ORBV) together with the Simulation Center (CeSi) of the CPS-MT in Lugano.

The tool allows you to assess how much and how simulation is integrated into clinical, training, organizational, and risk management processes.

In recent years, ORBV has integrated simulation into clinical risk management practices, transforming it into a real driver of systemic learning and a pillar of safety culture. A healthcare system can be said to be mature in risk management when it uses simulation not only to train individual professionals, but also to test systems, identify vulnerabilities in processes, and prevent adverse events before they can occur in real patients. This approach, in line with Hollnagel’s (2014) Safety-II philosophy focused on system adaptability and resilience, has been tested at ORBV through the SIMPAS (Simulation for Patient Safety) project with tangible results in terms of cultural and systemic improvement (e.g., greater psychological safety and proactive interception of near misses). (Rabito & Ingrassia, 2025).

Unlike other tools that measure the quality of simulation centers, SMAT analyzes the entire healthcare organization: the culture of simulation, governance, planning, and the systemic impact of activities. The goal is to analyze how much simulation is part of the hospital’s operational and cultural DNA, i.e., to understand how much simulation contributes to safety, resilience, and organizational learning. Simulation thus becomes not only a training technique but also a strategic lever for understanding and improving the functioning of the system, anticipating critical issues, and strengthening resilience.

Structure and Functioning of SMAT

SMAT is based on a 24-question Likert scale (1–5) questionnaire, divided into six dimensions of analysis:

1. Resources: infrastructure, personnel, time, and support dedicated to simulation.
2. Planning and Management: presence of a structured strategy and monitoring of activities.
3. Design and Evaluation: ability to create scenarios consistent with real needs and measure their impact.
4. Culture and Skills: dissemination of a safety- and learning-oriented mindset.
5. Strategy and Governance: alignment between simulation and business objectives.
6. Communication and Collaboration: integration between professionals, services, and decision-making levels.

For each question, five maturity levels are described (initial, intermediate, advanced, optimized, excellent).

The compilation, carried out by an interdisciplinary group (risk managers, trainers, clinicians, and executives), provides a visual representation in a radar chart showing the average scores for each area.

This “snapshot” allows you to identify strengths and areas for improvement and to define a development roadmap consistent with the corporate strategy. At ORBV, for example, the SMAT analysis led to the enhancement of facilitator training, the creation of the SIMPAS interdisciplinary group, and the integration of simulation into corporate events dedicated to patient safety, such as Patient Safety Action Week, promoted every year in September as part of the national campaign. In subsequent years, we have taken further action, including the definition of a structured annual plan and, above all, the development of clear criteria for case selection, in order to guide the design of our simulation scenarios in a more consistent and strategic manner.

A model for learning and adapting

SMAT is inspired by the principle of business continuity: the ISO 22301 standard requires regular testing and drills of emergency plans, including realistic simulations. SMAT explores dimensions ranging from organizational culture and training to clinical risk management and the organization’s ability to adapt and respond effectively in complex contexts.

During development, we also drew inspiration from the principles of continuous improvement found in various quality models such as ISO 9001, the EFQM criteria, and the more recent ISO 7101 standards, with the aim of creating a structured framework for self-assessment and organizational growth. Following this logic, SMAT was designed as a tool for systemic self-awareness, based on a radar representation that allows for immediate visualization of strengths and areas for development. This approach allows the organization not only to measure itself, but also to strategically orient improvement actions in line with an evolutionary and integrated vision of simulation. We consider it a kind of compass to guide healthcare facilities on their organizational learning journey through simulation. The model is currently in the pilot implementation phase, and we plan to refine it with feedback from the patient safety professional community. Our hope is that it will help increase organizational resilience in other healthcare settings as well, providing a common language and a reference point for integrating simulation into risk management and continuous improvement strategies in general.

Conclusion

The Simulation Maturity Assessment is therefore a guiding tool designed not only to capture the current state, but also to plan for the future in a resilient and sustainable way. The hope is that it will become a reference point for comparison and dialogue between different healthcare facilities, encouraging the sharing of experiences and supporting the path of organizational evolution in safety management. As for future developments, we intend to launch an external validation process for the tool, involving an interdisciplinary community of experts—risk managers, healthcare professionals, training and simulation experts—who, through a structured process, we expect will contribute to further refining the model, consolidating its validity, reliability, and adaptability over time. The ultimate goal is to grow a community that shares results, adaptations, and best practices, promoting a culture of in situ simulation as a strategic lever for safety and organizational resilience.

To express your interest in validating the model, please write to: giovanni.rabito@eoc.ch.

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