Can emergency physicians predict severity and time away from work?
Bibliographic record
Abstract
BACKGROUND: Emergency and primary care physicians are often asked to estimate patients' likely duration of sickness absence or temporary disability following work-related injury or illness. However, return to work is a complex interaction of multiple factors and often difficult to predict accurately. AIMS: To compare physician estimates of expected time away from work and severity of injury, made at the time of the initial presentation, with actual duration of temporary disability following work-related shoulder or knee injury. METHODS: Patients aged 18-65 with work-related shoulder or knee injuries who attended one of three Edmonton Emergency Departments were recruited. For each participant the treating physician made an estimate of severity and expected time before they would return to their work. This was compared with information on actual temporary disability (TDdays) obtained from the Alberta Workers' Compensation Board (WCB) data. RESULTS: Over the study period, 443 (88%) of 501 patients were enrolled into the study; however, only 177 (35%) agreed to linking their data with WCB. Median TDdays increased with the physicians' estimates of both severity and likely temporary disability. Physicians tended to underestimate time off work for those with long duration of TDdays, but overestimated this for those with short durations. CONCLUSIONS: Emergency physicians' estimates of expected lost work time and severity of injury were correlated with actual temporary disability, although their accuracy was fairly low. Further work to define why differences between estimated and actual temporary disability occur could help physicians and others planning return to work.
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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 | 0.000 |
| 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) | 0.002 | 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".