Causal Mediation Analysis for Standardized Mortality Ratios
Bibliographic record
Abstract
Indirectly standardized mortality ratios (SMR) are often used to compare patient outcomes between health care providers as indicators of quality of care. Observed differences in the outcomes raise the question of whether these could be causally attributable to earlier processes or outcomes in the pathway of care that the patients received. Such pathways can be naturally addressed in a causal mediation analysis framework. Adopting causal mediation models allows the total provider effect on outcome to be decomposed into direct and indirect (mediated) effects. This in turn enables quantification of the improvement in patient outcomes due to a hypothetical intervention on the mediator. We formulate the effect decomposition for the indirectly standardized SMR when comparing to a health care system-wide average performance, propose novel model-based and semiparametric estimators for the decomposition, study the properties of these through simulations, and demonstrate their use through application to Ontario kidney cancer data.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".