Increase in Utilization of Afterhours Medical Imaging: A Study of Three Canadian Academic Centers
Bibliographic record
Abstract
OBJECTIVES: The objectives of our study were to assess trends in afterhours medical imaging utilization for emergency department (ED) and inpatient (IP) patient populations from 2006-2013, including analysis by modality and specialty and with adjustment for patient volume. METHODS: For this retrospective study, we reviewed the number of CT, MRI, and ultrasound studies performed for the ED and IP patients during the afterhours time period (5pm - 8am on weekdays and 24 hours on weekends and statutory holidays) from 2006-2013 at three different Canadian academic hospitals. We used the Jonckheere-Terpstra (JT) test to determine statistical significance of imaging and patient volume trends. A regression model was used to examine whether there was an increasing trend over time in the volume of imaging tests per 1000 patients. RESULTS: For all three sites from 2006-2013 during the afterhours time period: There was a statistically significant increasing trend in total medical imaging volume, which also held true when the volumes were assessed by modality and by specialty. There was a statistically significant increasing trend in ED and IP patient volume. When medical imaging volumes were adjusted for patient volumes, there was a statistically significant increasing trend in imaging being performed per patient. CONCLUSION: Afterhours medical imaging volumes demonstrated a statistically significant increasing trend at all three sites from 2006-2013 when assessed by total volume, modality, and specialty. During the same time period and at all three sites, the ED and IP patient volumes also demonstrated a statistically significant increasing trend with more medical imaging, however, being performed per patient.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".