The role of physicians in increasing workers' compensation benefits for individuals with mesothelioma in British Columbia, Canada
Bibliographic record
Abstract
Objectives Mesothelioma is a cancer principally caused by occupational exposure to asbestos, but less than one-half of mesothelioma patients receive workers9 compensation in Canada. We evaluated a letter sent to physicians of patients newly diagnosed with mesothelioma by the British Columbia Cancer Agency informing them of workers9 compensation benefits and asking them to advise their patients to seek compensation. Methods Mesothelioma cases in the BC cancer registry were linked with accepted workers9 compensation mesothelioma claims. The proportion of compensation cases in the pre-letter period (Jan 2000 to Oct 2004) was compared to the proportion in the post-letter period (Nov 2004 to Dec 2009), by demographic, clinical and geographic characteristics. Adjusted incidence rate ratios investigated the effect of the letter on compensation status. Results Between 2000 and 2009, 668 mesothelioma cases were diagnosed in BC. During the letter period, 216 of 364 cases received a physician letter. Those with a longer survival time were more likely to receive the letter. The proportion of compensation was 43 claims per 100 cases during the pre-letter period compared to 40 claims per 100 cases during the post-letter period (IRR=1.12, 95% CI: 0.84 to 1.49). Among those sent the letter, there were modest increases for women, younger (<55 years) workers and those with a shorter survival time (<2 months). Conclusions The letter intervention had little effect in increasing mesothelioma compensation except among groups with historically low compensation rates (eg, women). Interventions such as physician and patient education may be needed to increase the compensation rate of mesothelioma.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".