Applying Criterion-Based Indications for Vascular Ultrasound Studies: Planning Quality Improvement
Bibliographic record
Abstract
Introduction Although most ultrasound facilities rely on the referring physicians' request for testing, inappropriate indications for ultrasound studies have been cited as a quality metric and source of poor resource use. In 2015, the Intersocietal Accreditation Commission mandated that ultrasound facilities undertake educational and other strategies to address this as a quality improvement initiative, including education of referring physicians. We proposed to study the indications noted in referrals to develop such quality strategies. Methods Dedicated vascular ultrasound facilities were asked to participate. An electronic search of guidelines, standards, and criteria for testing was done. The indication for testing in consecutive patients was collated with adherence to standards and criteria for testing, type of referring physician, patient demographics, and findings. Care gaps were identified to serve as a “needs assessment” for educational and other strategies to address quality improvement. Results Three facilities agreed to participate (one academic, two community). A total of 4,654 studies were analyzed. The vascular domains included were: carotid (610), aorta (217), renal (52), upper extremity arteries (56), lower extremity arteries (1,465), lower extremity venous for deep venous thrombosis (1,377), and lower extremity venous for chronic venous insufficiency (877). Overall, appropriate criteria were cited for 76–96% of studies; the academic facility had higher adherence. There was no difference between family physician and specialist referrals. Diagnostic positive yields were found in 48–68% in different test categories; aortic screening yield was 8.1%. Specific “teaching points” included “headaches” and “neck pain” for carotid studies, aortic screening outside of “targets,” “numb toes,” and “swelling” for arterial duplex; no clear issues were identified for venous studies. Conclusions This study does identify inappropriate indications for vascular ultrasound with no systematic findings. There are specific teaching points that can be used to direct educational strategies for referring physicians.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".