Artificial Intelligence Governance of Hospital Triage Algorithm Decommissioning Under Unmeasured Post-Retirement Clinician Reliance: A Healthcare Political Accountability Evaluation

Hospitals retire triage algorithms without measuring the informal reliance that retired clinicians continue to place on them, and this unmeasured reliance creates a political accountability gap that existing governance frameworks cannot detect. The analysis specifies a before-after-control-impact design for detecting post-retirement reliance effects, characterises its operating characteristics under a declared variance structure with an intraclass correlation of 0.64, between-cluster standard deviation of 6.0 and residual standard deviation of 4.5, and reports that 54 clusters are required to detect a 5 percentage-point effect at 80 per cent power across 2000 replications per design cell. Accountability for algorithm retirement must be institutionalised through reliance registers, post-retirement audit obligations and explicit attribution of responsibility when informal reliance produces adverse triage outcomes. The contribution is a governance framework that makes the political cost of decommissioning visible before it is incurred.