What, If Anything, Does Amenable Mortality Tell Us about Regional Health System Performance?
Bibliographic record
Abstract
OBJECTIVES: Amenable mortality is proposed as a health system performance measure, and has been used in comparisons across countries and socio-economic strata. We assess its utility as a health region–level indicator in Canada. APPROACH: We classified all deaths in British Columbia from 2002 to 2009 using two common definitions of amenable mortality. Counts and standardized rates were calculated for 16 health regions. To assess reliability, sensitivity and validity, we compared rates across regions and over time, and examined correlations with premature and all-cause mortality. RESULTS: Of the 238,849 deaths in the study period, 6.6% or 13.7% were classified as amenable (depending on the definition used). Rates were stable or falling in more populated regions, but unstable with large confidence intervals elsewhere. Correlation with overall mortality was strong. CONCLUSION: Though amenable mortality is appealing as a feasible, understandable indicator, we question whether it is appropriate for comparisons at a subprovincial level.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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".