Family physician referral rates for lumbar spine computed tomography in Newfoundland and Labrador: a cross-sectional analysis using routinely collected data
Bibliographic record
Abstract
BACKGROUND: Reducing computed tomography (CT) examinations of the lumbar spine is one of Choosing Wisely Canada's initial top 10 recommendations. This study's objective was to report the age- and-sex standardized rates of lumbar spine CT ordered by family physicians in 1 health region in Newfoundland and Labrador. METHODS: We conducted a retrospective study using local health data from Meditech, an electronic health record system, from 2013 to 2016 for the Eastern Health Region of Newfoundland and Labrador, the largest health region in the province. Records were included if the referral was for an adult aged 20 years or more, and CT was ordered by a family physician. Lumbar spine CT rates were contextualized with age- and sex-stratified estimates. Population estimates were provided by the Newfoundland and Labrador Centre for Health Information to calculate age- and sex-standardized rates per 100 000 people. We calculated rate ratios to test for statistical significance in differences in rates between years. RESULTS: A total of 14 370 records were examined. The age- and sex-standardized rates of lumbar spine CT per 100 000 were 1225 in 2013, 1393 in 2014, 1556 in 2015 and 1395 in 2016. The rate ratio was 1.137 (95% confidence interval [CI] 1.084-1.194) for the comparison between 2014 and 2013, 1.117 (95% CI 1.067-1.169) between 2015 and 2014, and 0.896 (95% CI 0.857-0.938) between 2016 and 2015. INTERPRETATION: The age- and sex-standardized rates suggest that there was a steady rate of lumbar spine CT examinations being ordered by family physicians in Newfoundland and Labrador in 2013-2016. Although all rate ratios were statistically significant, the magnitude of the difference between years is likely not clinically relevant. These rates are important because they serve as a benchmark for future initiatives to reduce unnecessary referrals for lumbar spine CT.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".