Evaluation of a regional trauma registry.
Bibliographic record
Abstract
BACKGROUND: For decades, trauma registries have been the primary source of data for resource allocation, quality improvement efforts and hypothesis-generating research in trauma care. Surprisingly, the quality and completion of data in these registries has rarely been reported. In preparation for a research program on population-based epidemiology of severe trauma, we evaluated the Calgary component of the Alberta Trauma Registry (ATR). METHODS: We identified the ATR records of all adult trauma patients (aged > or = 16 yr) admitted to hospitals in the Calgary Health Region (CRH) between April 1, 2001 and March 31, 2002 with severe injuries (Injury Severity Score > or = 12). From these registry data, we randomly selected 100 patient records, and we compared 14 fields, sampling parameters from prehospital care to discharge, with information from the hospital chart. RESULTS: Only 9 of 100 records were found to be incomplete. Of these, none had more than 1 field incomplete. Of the approximately 1400 data fields assessed, only 9 were missing data, resulting in a 99% (1391/1400) completion rate. Of 100 records, 22 were found to have inaccurate data; of these, 18 had 1 incorrect field, 2 had 2 incorrect fields and 2 had 3 incorrect fields. Overall, the ATR is 98% accurate. CONCLUSIONS: The Calgary component of the ATR can be considered accurate and complete. Some of its inaccuracy is attributable to a change in the way time to operating room was recorded. Data from all other fields collected in a standard manner can continue to be used with confidence for administrative and research purposes.
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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 | 0.000 |
| 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 | 0.000 |
| 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".