Changes in employer-sponsored private health insurance among retirees in Ontario: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Employer-sponsored health insurance, particularly for retirees with limited incomes, plays a major funding role in Canadian health care, including prescription drugs and dental services. We aimed to investigate the changes in retiree health insurance availability over time. METHODS: We performed a secondary analysis of data from the 2005 and 2013-2014 cycles of the Canadian Community Health Survey using multivariate logistic regression to study changes in retiree coverage availability over time in Ontario. We estimated the adjusted odds ratios of having employer coverage for likely retirees (people over age 65 yr who reported not working and those over age 75 yr), adjusting for a number of potential confounders. Sensitivity analysis was also performed for coverage of different treatments separately. RESULTS: The response rate was 76% for the 2005 cycle and 66% for 2013-2014 for the entire survey. The characteristics of respondents in the 2 survey cycles were similar, except respondents in 2013-2014 were wealthier. In our adjusted model, respondents in 2013-2014 had lower odds of reporting retiree coverage than respondents in 2005 (adjusted odds ratio 0.87; 95% confidence interval 0.77-0.99). This represents an absolute reduction in the probability of receiving retiree coverage of up to 3.4%. INTERPRETATION: Our analysis suggests that the rate of retiree health insurance has declined for Canadians with similar characteristics over the past decade. As we know insurance coverage has a strong association with use of treatments such as prescription drugs and dental care, this decline may result in decreased access to treatment and is an issue that warrants further investigation.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".