Work-related injuries and attendance at a Canadian regional emergency department
Bibliographic record
Abstract
BACKGROUND: Monitoring trends in the burden of illness and injury attributable to work is key in assessing occupational health hazards; however, New Brunswick does not participate in the Canadian National Ambulatory Care Reporting System which itself does not collect details of occupation and industry. AIMS: We set out to determine the proportion of emergency department attendances that were attributable to a work-related cause. We also wanted to evaluate the recording of occupation in the electronic health record system, and to describe the characteristics of patients with a work-related presentation. METHODS: A retrospective observational study over a 1-year period was conducted using an administrative database obtained from Canadian Emergency Department Information System. Descriptive statistics are used to present the analysis of categorical and continuous data. RESULTS: A total of 49 365 patients were included for analysis. Two per cent of patients presented with a self-reported work-related condition. Health care and social assistance, construction, retail trade and manufacturing were the most common industries reported by patients. CONCLUSIONS: This study found the rate of work-related medical conditions to be substantially less than expected, and that occupation was not captured for any patients presenting to the emergency department with a work-related condition, despite a field being available in the electronic health record registration system. We were able to analyse the industry sectors for work-related presentations. The recording and coding of occupation and industry would significantly benefit occupational epidemiology in emergency medicine as well as potentially improving patient outcomes and health system efficiencies.
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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 | 0.001 |
| 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".