Artificial Intelligence for Learning Point-of-Care Ultrasound

Study Overview
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Brief Summary
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Point-of care-ultrasonography has the potential to transform healthcare delivery through its diagnostic and therapeutic utility. Its use has become more widespread across a variety of clinical settings as more investigations have demonstrated its impact on patient care. This includes the use of point-of-care ultrasound by trainees, who are now utilizing this technology as part of their diagnostic assessments of patients. However, there are few studies that examine how efficiently trainees can learn point-of-care ultrasound and which training methods are more effective. The primary objective of this study is to assess whether artificial intelligence systems improve internal medicine interns' knowledge and image interpretation skills with point-of-care ultrasound. Participants shall be randomized to receive personal access to handheld ultrasound devices to be used for learning with artificial intelligence vs devices with no artificial intelligence. The primary outcome will assess their interpretive ability with ultrasound images/videos. Secondary outcomes will include rates of device usage and performance on quizzes.

Official Title
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Use of Artificial Intelligence for Acquisition of Limited Echocardiograms

Conditions
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Education, Medical, Ultrasound Imaging

Intervention / Treatment
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* Other: Ultrasound with Artificial Inteligence Engabled
* Other: Ultrasound without Artificial Intelligence Enabled


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Internal medicine residents rotating on the general inpatient wards service. Exclusion Criteria: Residents who had taken an ultrasound elective offered by our residency program
Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Other
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Single


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Artificial Intelligence Group<br> | Other: Ultrasound with Artificial Inteligence Engabled<br>* Participants shall be randomized 1:1 to receive personal access to a handheld ultrasound device with artificial intelligence vs a device with no artificial intelligence. The groups shall not cross over in which intervention they received.<br>|
| Active Comparator: Non Artificial Intelligence Group<br> | Other: Ultrasound without Artificial Intelligence Enabled<br>* Participants shall be randomized 1:1 to receive personal access to a handheld ultrasound device with artificial intelligence vs a device with no artificial intelligence. The groups shall not cross over in which intervention they received.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Time to acquire cardiac ultrasound images | This will be measured as the time to acquire a cardiac ultrasound image on a standardized patient, measured in seconds. | During procedure (300 seconds) | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Assessment of the quality of captured images | Participants will acquire cardiac ultrasound images on a standardized patient. Two reviewers will review the images and provide a numerical assessment of image quality based on the Rapid Assessment for Competency in Echocardiography (RACE) Scale. This is a 0-20 point scale, with higher scores denoting higher image quality (e.g. a better quality image). | During procedure (300 seconds) | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Medical Education, Point-of-Care Ultrasound