OasisLMS

Point-of-Care Ultrasound (PoCUS) Core Knowledge Digital Badge

About This Credential

At the Core level, this digital badge verifies knowledge of ultrasound physics, instrumentation, image optimization, and sonographic interpretation, as well as the ability to apply POCUS findings to clinical decision-making.

This digital badge reflects current evidence and professional practice recommendations supporting the use of POCUS to improve diagnostic accuracy, accelerate clinical decision-making, enhance risk stratification, and strengthen patient outcomes in anesthesia care.

Requirements to Earn the Badge

To earn this digital badge, participants must:

  • Complete all required online modules (6 total)
  • Demonstrated mastery of core Point-of-Care Ultrasound concepts by successfully passing a 40-question post-test (80% or greater) (2 attempts)
  • Apply evidence-based principles across clinical scenarios throughout the modules

Program Content

Earners successfully completed the following learning modules:

  • Ultrasound Fundamentals
  • Gastric Ultrasound
  • Lung Ultrasound
  • Upper Airway Ultrasound
  • Inferior Vena Cava (IVC) Ultrasound
  • Transthoracic Echocardiography (TTE) Ultrasound

Credits Awarded:

8 MAC Ed CE Credits

Clinical Decision-Making
Integrates ultrasound findings into anesthetic planning, patient assessment, and perioperative management using evidence-based reasoning.
Clinical Interpretation
Correctly interprets sonographic findings and understands diagnostic limitations.
Communication & Teamwork
Effectively communicates ultrasound findings and collaborates with the healthcare team to optimize patient care.
Image Acquisition & Recognition
Recognizes appropriate anatomy, image quality, and common findings across gastric, airway, lung, IVC, and TTE ultrasound.
Patient Safety & Professional Practice
Uses POCUS appropriately within scope of practice while recognizing limitations, documentation requirements, and quality assurance expectations.
Technical Knowledge
Understands ultrasound physics, machine operation, transducer selection, and image optimization.