Performance of High-Quality Point-of-Care Ultrasound by Advanced Practice Providers in an Academic Emergency Department

Introduction Point-of-care ultrasound (POCUS) is a valuable tool in emergency medicine, enhancing diagnostic accuracy and guiding patient care. While emergency physicians have long utilized POCUS, advanced practice providers (APPs), including physician assistants and nurse practitioners, were only formally supported by the American College of Emergency Physicians in 2019. This study evaluates the impact of an educational intervention on APPs' ability to perform high-quality, billable POCUS in a high-volume academic emergency department (ED) (75,000 visits/year). Materials and methods This study included three components: (1) a one-hour didactic session followed by hands-on training and direct clinical observation in soft tissue (ST) and fetal heart tone (FHT) POCUS, (2) a quality assurance review of scans performed by APPs, and (3) a voluntary survey assessing APP's perceptions of POCUS use. Data were collected between 2015 and 2018. Descriptive statistics were used to analyze the survey data. Survey responses were reported as frequencies. Descriptive statistics, including percentages, means for interval scales, and medians for ordinal scales, were generated using SPSS Statistics version 26.0 (IBM Corp. Released 2019. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp). Results Fourteen APPs performed 471 POCUS exams, with 87% (N=412) initially meeting criteria for billing. The remaining 13% (N=59) scans required additional steps, either completion of electronic health record documentation in 87% (N=51) or an attending physician signature in 13% (N=8), before they were considered billable. Following standard departmental procedures for addressing charting deficiencies, all required documentation and signatures were completed, making 100% of scans ultimately billable, with no rejections due to image quality. Survey respondents (N=6) reported increased confidence and changes in clinical management due to POCUS. The primary barrier to POCUS use was limited training in additional applications. APPs used POCUS more frequently for ST evaluations than for FHT assessments, with self-reported confidence scores of 7.8 and 4.4 out of 10, respectively. Conclusion This study demonstrates that APPs can perform high-quality, billable POCUS in the ED following structured training and quality review feedback.

Authors

Institutions

Publication Details

Journal
Cureus
Published
2025-04-01
DOI
https://doi.org/10.7759/cureus.81564
Citations
1
Primary Topic
Ultrasound in Clinical Applications
Type
article
Field-Weighted Citation Impact
1.55
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Performance of High-Quality Point-of-Care Ultrasound by Advanced Practice Providers in an Academic Emergency Department

Robert Treat, Jamie Aranda, Dan Dwyer, Jennifer Trimboli et al.
1 citations
Cureus
Ultrasound in Clinical Applications
1.55
article

Performance of High-Quality Point-of-Care Ultrasound by Advanced Practice Providers in an Academic Emergency Department

Robert Treat, Jamie Aranda, Dan Dwyer, Jennifer Trimboli, Mary Beth Phelan
article en
1 citations

Abstract

Introduction Point-of-care ultrasound (POCUS) is a valuable tool in emergency medicine, enhancing diagnostic accuracy and guiding patient care. While emergency physicians have long utilized POCUS, advanced practice providers (APPs), including physician assistants and nurse practitioners, were only formally supported by the American College of Emergency Physicians in 2019. This study evaluates the impact of an educational intervention on APPs' ability to perform high-quality, billable POCUS in a high-volume academic emergency department (ED) (75,000 visits/year). Materials and methods This study included three components: (1) a one-hour didactic session followed by hands-on training and direct clinical observation in soft tissue (ST) and fetal heart tone (FHT) POCUS, (2) a quality assurance review of scans performed by APPs, and (3) a voluntary survey assessing APP's perceptions of POCUS use. Data were collected between 2015 and 2018. Descriptive statistics were used to analyze the survey data. Survey responses were reported as frequencies. Descriptive statistics, including percentages, means for interval scales, and medians for ordinal scales, were generated using SPSS Statistics version 26.0 (IBM Corp. Released 2019. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp). Results Fourteen APPs performed 471 POCUS exams, with 87% (N=412) initially meeting criteria for billing. The remaining 13% (N=59) scans required additional steps, either completion of electronic health record documentation in 87% (N=51) or an attending physician signature in 13% (N=8), before they were considered billable. Following standard departmental procedures for addressing charting deficiencies, all required documentation and signatures were completed, making 100% of scans ultimately billable, with no rejections due to image quality. Survey respondents (N=6) reported increased confidence and changes in clinical management due to POCUS. The primary barrier to POCUS use was limited training in additional applications. APPs used POCUS more frequently for ST evaluations than for FHT assessments, with self-reported confidence scores of 7.8 and 4.4 out of 10, respectively. Conclusion This study demonstrates that APPs can perform high-quality, billable POCUS in the ED following structured training and quality review feedback.

CureusVol. 17(4)
Medical College of Wisconsin (US)
Openalex Percentile: Top 21%
Ultrasound in Clinical Applications
1.55
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.