Introduction: Point-of-care ultrasound (POCUS) is an essential diagnostic and procedural tool in pediatric critical care. However, many institutions lack standardized workflows for storing and documenting POCUS studies. At our institution, we identified the need to: (1) securely archive POCUS images within the Picture Archiving and Communication System (PACS), (2) integrate studies directly into the electronic medical record (EMR) for clinical documentation, and (3) establish a centralized database for quality assurance (QA) review. We describe our institutional experience implementing a fully integrated POCUS workflow. Methods: In collaboration with our Epic EMR development team, we designed a native workflow that avoids the need for costly third-party middleware. The process includes: 1. Providers place a POCUS order in Epic before performing the scan. 2. Orders are set to “Silent Schedule” and auto-advance to “End Exam. ” 3. The ultrasound machine uses the Modality Worklist to sync with the Epic order. 4. Acquired images are transmitted to PACS, with a hyperlink generated in the patient’s chart. 5. Providers document their interpretation using Epic’s iProc tool. 6. Finalizing the iProc report triggers both technical and professional billing charges. This EMR-based workflow is currently a cost-effective, scalable, and functional solution. As POCUS volume increases, middleware may eventually be required to support advanced features such as routing and automation. Results: The workflow was launched in Q3 2024. Since implementation, 63 studies were completed in 2024 and 297 in 2025 year-to-date. All studies were successfully ordered, uploaded, interpreted, and reviewed for QA. Billing charges totaling 47, 784 were generated, with 9, 555 in net reimbursement. The majority of studies were performed by critical care and emergency medicine providers. No studies were lost, and all charges were appropriately captured. Conclusions: Implementing a structured Epic-based POCUS workflow is feasible and effectively integrates into routine clinical care. This approach facilitates real-time documentation, centralized QA review, and appropriate revenue capture. Future efforts will focus on clinical outcome measures and user satisfaction.
Bhargava et al. (2026) studied this question.