The prevalence and patterns of use of point-of-care ultrasound in Newfoundland and Labrador
Bibliographic record
Abstract
INTRODUCTION: Point-of-care ultrasound (POCUS) is used for diagnostic and procedural guidance by physicians in Newfoundland and Labrador (NL). POCUS use is largely limited to urban locations and the training is variable amongst physicians. The primary aim of this study was to determine the prevalence of POCUS devices in NL and the secondary aim was to characterise the patterns of POCUS use amongst physicians in NL. METHODS: This is a mixed-methods cross-sectional study. We determined the prevalence of POCUS devices from purchase records and the patterns of POCUS use through theme-based interviews. The interviews were transcribed, coded and analysed using standardised qualitative methods. RESULTS: Ten physicians (3 females, 5 rural) participated in the interviews. The overall prevalence of POCUS devices in NL was 12.5/100,000 population. Participants in urban areas had more access to POCUS training and devices. Participants used POCUS on a daily or weekly basis to rule in or out life-threatening conditions and improve access to specialist care. The benefits of POCUS included expedited investigations, decreased radiation and increased patient satisfaction. The barriers to using POCUS were lack of training, time, devices, image archiving software, difficulty generating and interpreting images and patient body habitus. CONCLUSION: This is the first study to our knowledge to report the prevalence of POCUS devices in Canada. Physicians who practise in rural NL have limited access to POCUS devices and have identified barriers to POCUS training. Connecting physicians in rural areas with POCUS experts through a province-wide POCUS network may address these barriers and improve healthcare access.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".