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Virtual immediate feedback with POCUS in Belize.

Anita Mulye¹, Ajay Bhasin¹, Bonita Borger²

¹Division of Hospital Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.

Frontiers in Digital Health

|November 29, 2023

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Point of care ultrasound (POCUS) training in Belize enhanced pneumonia diagnosis. A hybrid curriculum using virtual feedback improved provider skills in low-resource settings.

Area of Science:

Medical Education
Diagnostic Imaging
Global Health

Background:

Point of care ultrasound (POCUS) offers significant potential for improving diagnostic accuracy and medical education in low- and middle-income countries (LMICs).
Implementing POCUS training in resource-limited settings presents unique challenges and opportunities.

Purpose of the Study:

To describe the implementation of a hybrid in-person and virtual training curriculum for lung ultrasound in Belize.
To share experiences and challenges encountered during POCUS training in an LMIC.
To provide an effective training methodology example for clinicians in similar settings.

Main Methods:

A hybrid training curriculum combining in-person and virtual components was developed.
Providers in Belize were trained in basic lung ultrasound techniques for pneumonia diagnosis.

Keywords:

LMIC POCUS global health medical education training virtual feedback

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Lung ultrasound images were shared virtually via the ButterflyIQ platform for expert feedback.

Communication and image sharing were facilitated using Butterfly iQ+ and WhatsApp.

Main Results:

Eleven lung scans were performed for patients with respiratory complaints between August 2021 and June 2022.
Virtual, immediate feedback through common interfaces solidified training and guided diagnostic reasoning.
The methodology proved effective in enhancing POCUS skills.

Conclusions:

A hybrid POCUS training model is effective for improving diagnostic capabilities in LMICs.
Virtual feedback mechanisms are crucial for successful skill acquisition and knowledge consolidation.
This approach can be adapted for widespread implementation in resource-limited healthcare settings.