Predictors and economic burden of serious workplace falls in health care
Bibliographic record
Abstract
AIMS: To examine the demographic and workplace risk factors of serious falls and associated economic burden in Canadian health care workers. METHODS: Fall injury data during 2005-2008 from a workplace health and safety surveillance system were linked with workers' compensation claims and payroll records. The costs for treatment and wage loss and days lost for accepted time-loss claims were calculated. Demographic and work-related factors were identified to distinguish the risk for more serious falls from less serious falls. RESULTS: Nine hundred and thirty-eight fall injury claims were captured among 48 519 full-time equivalent workers. Workers >60 years, part time or employed in the long-term care sector sustained a higher proportion of serious falls (>70%). Over 75% of falls were serious for care aides, facility support service workers and community health workers. In the multivariate analysis, the risk of serious falls remained higher for workers in the long-term care sector [odds ratio (OR) 1.71; P < 0.05] compared with those in acute care and for care aides (OR 1.72; P < 0.05), facility support service workers (OR 2.58; P < 0.01) and community health workers (OR 3.61; P < 0.001) compared with registered nurses (RNs). The median number of days lost was higher for females, long-term care workers, licensed practical nurses and care aides. Females, long-term care workers, RNs, licensed practical nurses, care aides and maintenance workers had the most costly falls. CONCLUSIONS: Reducing work-related serious fall injuries would be expected to bring about significant benefits in terms of reduced pain and suffering, improved workplace productivity, reduced absenteeism and reduced compensation costs.
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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 | 0.001 | 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) | 0.001 | 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".