Artificial Intelligence for Learning Point-of-Care Ultrasound
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Ultrasound with Artificial Inteligence Engabled, Ultrasound without Artificial Intelligence Enabled.
- Who it may be relevant to
- Registry conditions: Education, Medical, Ultrasound Imaging. Basic parameters: No limits · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- United States
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Use of Artificial Intelligence for Acquisition of Limited Echocardiograms
Overview
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.
Interventions
- Other Ultrasound with Artificial Inteligence Engabled
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. - Other Ultrasound without Artificial Intelligence Enabled
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.
Primary outcome measures
- Time to acquire cardiac ultrasound images [Time frame: During procedure (300 seconds)]
Secondary outcome measures (1)
- Assessment of the quality of captured images [Time frame: During procedure (300 seconds)]
Eligibility criteria
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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Allocation
- Randomized
- Model
- Parallel assignment
- Masking
- Single blind
- Primary purpose
- Other
Study locations
United States · 1 center
- Stanford University School of Medicine — Stanford
Publications
- Kumar A, Weng Y, Wang L, Bentley J, Almli M, Hom J, Witteles R, Ahuja N, Kugler J. Portable Ultrasound Device Usage and Learning Outcomes Among Internal Medicine Trainees: A Parallel-Group Randomized Trial. J Hosp Med. 2020 Feb 11;15(2):e1-e6. doi: 10.12788/jhm.3351. Online ahead of print. PMID 32118565
Identifiers
NCT: NCT05900440 · IRB-42094