Informing the Revolution: A Needs Assessment of Ultrasound Knowledge and Skills Among Graduating Physician Assistant Students

Barnett, Melissa; Pillow, M. Tyson; Carnell, Jennifer; Rohra, Anita; DeSandro, Stephanie; Gardner, Aimee K.

doi:10.1097/jpa.0000000000000210

Cited by 14 publications

(16 citation statements)

References 7 publications

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“…Despite PA students' desire for POCUS education, current medical school trends, and general clinical practice trends, few PA programs have successfully integrated POCUS education into their curricula. 3,4,6 Even with a majority of medical schools incorporating some amount of POCUS education into their curricula, very few have reported successful models of horizontal and vertical integration across the entirety of the curricula. 3,7 Barriers to incorporating POCUS into PA education are well described, with the top perceived barriers being lack of ultrasound machines, expense, and lack of faculty trained in POCUS.…”

Section: Discussionmentioning

confidence: 99%

“…In a 2018 survey of graduating physician assistant (PA) students, 82% of respondents desired formal POCUS training, and the same percentage of students believed that their POCUS education was insufficient to prepare them for clinical practice. 4 Yet, implementation of POCUS into the didactic education of PA students has been shown to be feasible and effective. 5 Still, although 68% of PA programs surveyed in 2019 believed POCUS skills should be taught in the didactic curriculum, only 11.2% of programs reported teaching these skills in their curricula.…”

Section: Introductionmentioning

confidence: 99%

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An Integrated Point-of-Care Ultrasound Curriculum: An Evidence-Based Approach

Breunig

Huckabee

Rieck

2022

J Physician Assist Educ

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Point-of-care ultrasound (POCUS) has been demonstrated to improve students' medical knowledge and clinical exam skills and advances patient care through numerous diagnostic and therapeutic applications. Despite the growing use of ultrasound in medical education and clinical practice, few physician assistant (PA) programs have successfully integrated POCUS education into their curricula. This manuscript describes an evidence-based approach for integrating POCUS education throughout a 2-year PA curriculum, with the goal of serving as a useful guidepost for other PA programs as they strive to incorporate this valuable skill into their curricula.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Integrated Point-of-Care Ultrasound Curriculum: An Evidence-Based Approach

Breunig

Huckabee

Rieck

2022

J Physician Assist Educ

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“…Ultrasound technicians require much more training relative to other types of radiologists, training which necessarily must include exposure to a wide variety of pathologies across a wide variety of patients in a format that enables dynamic investigation, historically in-person workshops, with the confluence of these factors resulting in fewer opportunities to receive this training. Indeed, a 2018 study found that 84% of the physician assistants surveyed believed that the training they received during their clinical rotations was insufficient preparation for clinical practice [43]. Among the many potential solutions to achieving sufficient ultrasonography expertise, increasing access to effective training opportunities via computer-based simulation platforms and developing automated image analysis systems to assist radiologists are two of the more promising areas.…”

Section: The Evolution Of Modern Segmentation Networkmentioning

confidence: 99%

Catalyzing Clinical Diagnostic Pipelines Through Volumetric Medical Image Segmentation Using Deep Neural Networks: Past, Present, & Future

Zosa

2021

Preprint

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Deep learning has made a remarkable impact in the field of natural image processing over the past decade. Consequently, there is a great deal of interest in replicating this success across unsolved tasks in related domains, such as medical image analysis. Core to medical image analysis is the task of semantic segmentation which enables various clinical workflows. Due to the challenges inherent in manual segmentation, many decades of research have been devoted to discovering extensible, automated, expert-level segmentation techniques. Given the groundbreaking performance demonstrated by recent neural network-based techniques, deep learning seems poised to achieve what classic methods have historically been unable. This paper will briefly overview some of the state-of-the-art (SoTA) neural network-based segmentation algorithms with a particular emphasis on the most recent architectures, comparing and contrasting the contributions and characteristics of each network topology. Using ultrasonography as a motivating example, it will also demonstrate important clinical implications of effective deep learning-based solutions, articulate challenges unique to the modality, and discuss novel approaches developed in response to those challenges, concluding with the proposal of future directions in the field.Given the generally observed ephemerality of the best deep learning approaches (i.e. the extremely quick succession of the SoTA), the main contributions of the paper are its contextualization of modern deep learning architectures with historical background and the elucidation of the current trajectory of volumetric medical image segmentation research.

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“…7,9 Yet, in one study, 84% of PA students did not feel the instruction they had received on clinical rotations was sufficient to prepare them for clinical practice. 9…”

Section: Introductionmentioning

confidence: 99%

“…5,7 The majority of PA program directors think PA programs should teach hands-on US skills, 8 and the majority of PA students report an interest in learning how to use ultrasound. 7,9 Yet, in one study, 84% of PA students did not feel the instruction they had received on clinical rotations was sufficient to prepare them for clinical practice. 9 Barriers to adoption of US into PA programs include cost, lack of trained faculty members, and lack of time in academic schedules.…”

Section: Introductionmentioning

confidence: 99%

Student Ultrasound Interest Group: A Novel Method of Introducing Ultrasound to Physician Assistant Students

Lolar¹

2022

J Physician Assist Educ

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Purpose:This study describes a student ultrasound interest group (SUIG) in a resource-limited physician assistant (PA) program. The benefits of PA student attitudes and knowledge of ultrasound (US) are described.Methods:Participation in the SUIG was voluntary. Didactics included free online access medical education (FOAMed) materials. Initial scanning sessions focused on the Focused Assessment with Sonography in Trauma (FAST) exam and were led by a faculty champion with limited US experience. A survey on attitudes and a basic US knowledge test were administered before and after the first session and again 2 months later.Results:Thirty-seven students (76% female, mean age 26.4) participated in the initial FAST scanning sessions. All participants agreed that the SUIG session was useful. There was a slight increase in confidence after SUIG sessions (1.27 vs 2.92 on a 5-point scale), and 94% reported increased motivation to seek out ultrasound opportunities on clinical rotations. The average score on the knowledge test increased from 37% to 90% after the scanning sessions; the average score waned over time to 80% after 2 months.Conclusion:SUIGs are a valuable way to introduce US to PA students using limited resources. Even minimal exposure can increase PA student confidence and knowledge.

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Informing the Revolution: A Needs Assessment of Ultrasound Knowledge and Skills Among Graduating Physician Assistant Students

Abstract: Existing PA program curricula are insufficient for developing critical skills related to ultrasonography.

Cited by 14 publications

References 7 publications

An Integrated Point-of-Care Ultrasound Curriculum: An Evidence-Based Approach

An Integrated Point-of-Care Ultrasound Curriculum: An Evidence-Based Approach

Catalyzing Clinical Diagnostic Pipelines Through Volumetric Medical Image Segmentation Using Deep Neural Networks: Past, Present, & Future

Student Ultrasound Interest Group: A Novel Method of Introducing Ultrasound to Physician Assistant Students

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