Trends in needlestick injury incidence following regulatory change in Ontario, Canada (2004–2012): an observational study
Bibliographic record
Abstract
BACKGROUND: A number of jurisdictions have used regulation to promote the adoption of safety-engineered needles as a primary solution to reduce the risk of needlestick injuries among healthcare workers. Regulatory change has not been complemented by ongoing efforts to monitor needlestick injury trends which limits opportunities to evaluate the need for additional investment in this area. The objective of this study was to describe trends in the incidence of needlestick injuries in Ontario prior to and following the establishment of regulation to promote the adoption of safety-engineered needles. METHODS: An observational study of needlestick injuries obtained from two independent administrative data sources (emergency department records for the treatment of work-related disorders and workers' compensation claims) for a population of occupationally-active adults over the period 2004-2012. RESULTS: Comparing the year prior to the regulation being established (2006) to three years after the regulation came into effect (2011), needlestick injury rates in the health and social services sector that were captured by workers' compensation claims declined by 31% and by 43% in the work-related emergency department records. Rates of workers' compensation claims associated with needlestick injuries declined by 31% in the hospital sector, by 67% in the long-term care sector and have increased by approximately 1% in nursing services over the period 2004-2012. CONCLUSIONS: Two independent administrative data sources documented an overall reduction in needlestick injuries in the province of Ontario following a regulatory requirement to adopt safety-engineered needles; however, a substantial burden of occupational needlestick injuries persists in this setting.
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".