Anterior's Approach to Fairness Evaluation of Automated Prior Authorization System

Increasing staffing constraints and turnaround-time pressures in Prior authorization (PA) have led to increasing automation of decision systems to support PA review. Evaluating fairness in such systems poses unique challenges because legitimate clinical guidelines and medical necessity criteria often differ across demographic groups, making parity in approval rates an inappropriate fairness metric. We propose a fairness evaluation framework for prior authorization models based on model error rat

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ethics.ai (15 March 2026), “Anterior's Approach to Fairness Evaluation of Automated Prior Authorization System,” evidence record 7203, https://ethics.ai/record/7203 (originally published by arXiv).

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