Artificial Intelligence Governance of Emergency Blood Bank Inventory Models Under Unmeasured Transfusion Committee Emergency Release Latitude: A Healthcare Political Robustness Evaluation

Emergency blood bank inventory models increasingly inform artificial intelligence governance decisions, yet their evaluations typically assume that transfusion committee emergency release latitude is either absent or fully measured. the present analysis treats that latitude as an unmeasured governance parameter and asks how robust the before-after-control-impact estimator is when the parameter is ignored. The analysis is a design-based power evaluation, not an observational study: it characterises the operating characteristics of the estimator under a declared variance structure with between-cluster SD of 6.0, residual SD of 4.5 and intraclass correlation of 0.64, across 2000 replications per design cell for cluster counts of 8, 16, 24 and 32 and effect sizes of 3, 5 and 8 percentage points. The design required 54 clusters to detect a 5 percentage point effect at 80% power. Estimated power rose with cluster count and effect size, and the minimum detectable effect at 80% power fell as clusters increased. Transfusion committee latitude functions as a politically consequential omitted parameter whose neglect inflates apparent governance confidence, and it specifies the conditions under which before-after-control-impact designs remain defensible for AI governance evaluation in emergency blood banking.