O-359 THE NATIONAL BURDEN OF WORKING TIME LOST TO COMPENSABLE OCCUPATIONAL INJURY AND DISEASE: A RETROSPECTIVE POPULATION BASED STUDY
Bibliographic record
Abstract
Abstract Introduction Population-based measures of working time lost to occupational injury and disease have not been previously reported in Australia. This study sought to determine the national burden of working time lost to compensable occupational injury and disease, and to characterise the distribution of working time loss by age, sex, injury and disease. Methods Retrospective population-based study of all accepted workers’ compensation claims involving payment of wage replacement benefits between July 2012 and June 2017 nationally. Primary outcome measure is Working Years Lost (WYL) per annum, defined as the total number of years of wage replacement benefits paid to injured and ill nationally, by sex, age, injury and disease. Results Compensable occupational injury and disease resulted in 45,642 WYL nationally per annum. Male workers incurred 28,676 (62.8%) WYL while female workers accounted for 16,966 (37.2%). More than half of WYL (53.5%) were from workers aged over 45 years, despite these workers accounting for less than half (43.9%) of accepted claims. Traumatic injury resulted in 18,584 (40.7%) WYL per annum, followed by Musculoskeletal disorders (9,211WYL; 20.2%) and Mental health conditions (5,412 WYL, 11.9%). Discussion Annually, compensable occupational injury and disease in Australia results in a substantial burden of lost working time, equivalent to over 45,000 lost full time jobs. The distribution of burden reflects the higher labour force participation of males, slower rehabilitation in older workers, and the relative impact of common occupational injuries and diseases. Conclusion Effective occupational health surveillance, policy development and resource allocation will benefit from population-based monitoring of working time loss.
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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 | 0.001 |
| 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) | 0.001 | 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 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".