Age- and sex-specific Canadian utility norms, based on the 2013–2014 Canadian Community Health Survey
Bibliographic record
Abstract
BACKGROUND: Although many Canadian studies have provided disease-specific or patient group-specific utility scores, the utility score norms currently available for the general Canadian population are outdated. Canadian guideline recommendations for the economic evaluation of health technologies advocate for utilities reflecting those of the general population and for stratified analyses when results are heterogeneous; as such, there is also a need for age-, sex- and jurisdiction-specific utility score norms. METHODS: We used data from the 2013-2014 Canadian Community Health Survey. We used the Health Utilities Index Mark 3 to calculate utility scores. We estimated means (with 95% confidence intervals [CIs]) and medians (with interquartile ranges [IQRs]) for utility scores. In addition to Canadian-level measures, we stratified all utility score norms by respondents' age, sex, and province or territory of residence. We weighted respondents' answers and computed 95% CIs using sampling weights and bootstrap weights provided by Statistics Canada to extrapolate the study findings to the Canadian population. RESULTS: Respondents to the 2013-2014 Canadian Community Health Survey represented 30 014 589 community-dwelling Canadians 12 years of age and older (98% of the Canadian population); half of the respondents were female (50.6%), and the weighted average age was 44.8 (95% CI 44.7-44.9) years. The mean and median self-reported utility scores for Canadians were estimated at 0.863 (95% CI 0.861-0.865) and 0.927 (IQR 0.838-0.972), respectively. INTERPRETATION: This study provides utility score norms for several age-, sex-and jurisdiction-specific strata in Canada. These results will be useful for future cost-utility analyses and could serve as benchmark values for comparisons with future studies.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".