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Integrated simulation-based training models provide a framework for perioperative point-of-care ultrasound competencyNew training models improve ultrasound skills for surgical team members
Frontiers in MedicinePublished July 18, 2026DOI ↗Editorial oversight: Dr. Amelia Tan, PhD · Internal Medicine & Chronic Disease
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Key Takeaway
Utilize integrated simulation-based models and multi-faceted rubrics to develop perioperative POCUS competency.
This narrative review synthesizes current education models and assessment strategies for point-of-care ultrasound (POCUS) specifically tailored for perioperative teams, including anesthesiologists, surgeons, and emergency clinicians. The authors identify six complementary simulation-based training models: low-fidelity task training, standardized-patient and peer scanning, high-fidelity physiologic simulation, hybrid operating-room crisis simulation, virtual reality, and augmented reality platforms. Additionally, they propose a longitudinal simulation-based mastery learning approach.
To ensure competency, the review suggests a multi-faceted assessment framework. Recommended components include image-quality rubrics, interpretation tests, entrustable professional activities, objective structured clinical examinations, image portfolios, and longitudinal workplace-based feedback. These tools are intended to move learners toward safe bedside practice.
Limitations noted by the authors include an evidence base that varies significantly across different simulation modalities and assessment tools. Furthermore, a distinction is required between empirically tested instruments and those that are only locally adapted or theoretical. Clinical application should note that simulation is not a substitute for supervised clinical scanning.
When a patient is in surgery or recovery, doctors need to make quick decisions. Using point-of-care ultrasound (POCUS) allows them to see what is happening inside the body in real time. However, learning this skill requires more than just reading a textbook; it requires hands-on practice that feels like the real thing.
A review of current training methods identified six different ways to teach these skills. These include low-fidelity tasks, peer scanning, and high-fidelity simulations. Some models even use virtual or augmented reality to help clinicians practice in a safe environment before they ever touch a patient.
These tools help doctors move from knowing the theory to performing safely at the bedside. While different methods have different levels of evidence, these models provide a roadmap for training surgeons and emergency staff. It is important to remember that simulation is meant to prepare clinicians, not replace supervised clinical scanning.
What this means for you:
Six different simulation models help medical teams master ultrasound skills before using them on real patients.
Common questions
What kind of simulation methods are available for ultrasound training?
There are six identified models: low-fidelity task training, standardized-patient and peer scanning, high-fidelity physiologic simulation, hybrid operating-room crisis simulation, virtual reality, and augmented reality platforms. There is also longitudinal simulation-based mastery learning to help clinicians build skills over time.
How do experts measure if a clinician is competent in ultrasound?
Experts recommend several ways to check for skill, including image-quality rubrics, interpretation tests, and entrustable professional activities. Other methods include objective structured clinical examinations, image portfolios, and ongoing feedback from the workplace.
Is simulation a replacement for real-world practice?
No, simulation is not a substitute for supervised clinical scanning. It is designed to help medical teams move from theoretical knowledge to safe, competent bedside practice in perioperative settings before they work independently.
Study Details
Study typeSystematic review
EvidenceLevel 1
PublishedJul 2026
View Original Abstract ↓
Point-of-care ultrasound (POCUS) has become an increasingly important component of perioperative medicine, supporting real-time assessment of cardiovascular function, pulmonary pathology, gastric content, airway anatomy, vascular access, regional anesthesia, and perioperative complications. Perioperative POCUS is relevant to anesthesiologists and to the broader perioperative team, including critical care clinicians, pain physicians, emergency clinicians, surgeons, and ultrasound educators who participate in perioperative diagnosis, procedures, resuscitation, and postoperative care. Despite its growing clinical relevance, POCUS education in anesthesiology and perioperative medicine remains heterogeneous, with variable curricular scope, inconsistent assessment strategies, and persistent barriers related to faculty expertise, protected training time, equipment access, and competency verification. This narrative review used a transparent, targeted search strategy across biomedical and education databases, with adapted PRISMA reporting elements used to describe sources, search concepts, and selection boundaries while preserving the interpretive purpose of a narrative synthesis. Simulation-based education offers a practical and ethically sound approach for teaching POCUS before learners perform examinations in high-stakes perioperative environments. This review synthesizes educational theory, perioperative POCUS competency frameworks, empirical ultrasound simulation evidence, cross-disciplinary procedural simulation literature, and assessment scholarship to propose an integrated training model for perioperative POCUS. We organize simulation-based POCUS education into six complementary models: low-fidelity task training, standardized-patient and peer scanning, high-fidelity physiologic simulation, hybrid operating-room crisis simulation, virtual and augmented reality platforms, and longitudinal simulation-based mastery learning. Effective perioperative POCUS education should progress from cognitive preparation and deliberate image acquisition practice to interpretation, clinical integration, documentation, and team-based decision-making. Assessment should combine image-quality rubrics, interpretation tests, entrustable professional activities, objective structured clinical examinations, image portfolios, and longitudinal workplace-based feedback. Because the evidence base differs across simulation modalities and assessment tools, programs should distinguish empirically tested instruments from locally adapted or theoretical tools and should validate competency thresholds before using them for high-stakes credentialing. Key research priorities include multicenter validation of competency thresholds, comparative effectiveness studies of simulation modalities, cost-effectiveness analyses, faculty development models, responsible integration of artificial intelligence, and studies linking simulation-based training to clinical performance and patient outcomes. Simulation is not a substitute for supervised clinical scanning; rather, it is a bridge between theoretical knowledge and safe, competent bedside practice.
