Characterizing worker compensation claims in long-term care and examining the association between facility characteristics and severe injury: a repeated cross-sectional study from Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: Despite the physical demands and risks inherent to working in long-term care (LTC), little is known about workplace injuries and worker compensation claims in this setting. The purpose of this study was to characterize workplace injuries in LTC and to estimate the association between worker and organizational factors on severe injury. METHODS: We used a repeated cross-sectional design to examine worker compensation claims between September 1, 2014 and September 30, 2018 from 25 LTC homes. Worker compensation claim data came from The Workers Compensation Board of Alberta. LTC facility data came from the Translating Research in Elder Care program. We used descriptive statistics to characterize the sample and multivariable logistic regression to estimate the association between staff, organizational, and resident characteristics and severe injury, measured as 31+ days of disability. RESULTS: We examined 3337 compensation claims from 25 LTC facilities. Less than 10% of claims (5.1%, n = 170) resulted in severe injury and most claims did not result in any days of disability (70.9%, n = 2367). Most of the sample were women and over 40 years of age. Care aides were the largest occupational group (62.1%, n = 2072). The highest proportion of claims were made from staff working in voluntary not for profit facilities (41.9%, n = 1398) followed by public not for profit (32.9%, n = 1098), and private for profit (n = 25.2%, n = 841). Most claims identified the nature of injury as traumatic injuries to muscles, tendons, ligaments, or joints. In the multivariable logistic regression, higher staff age (50-59, aOR: 2.26, 95% CI 1.06-4.83; 60+, aOR: 2.70, 95% CI 1.20-6.08) was associated with more severe injury, controlling for resident acuity and other organizational staffing factors. CONCLUSIONS: Most claims were made by care aides and were due to musculoskeletal injuries. In LTC, few worker compensation claims were due to severe injury. More research is needed to delve into the specific features of the LTC setting that are related to worker injury.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".