Make the model card usable at the bedside
Convert model-card facts into clinically useful limits, use conditions, and escalation guidance.
The move: turn documentation into decision support about the AI itself. Intended use State the clinical setting, patient population, user role, and decision point. "Risk prediction" is too vague; "supports nurse outreach prioritization for adult heart-failure discharge follow-up" is usable. Evaluation slices Show where the model performs differently: site, language, age band, device type, payer, missingness, or comorbidity. In healthcare, subgroup performance can become subgroup harm. Limits and escalation Write the practical boundary: when to ignore, verify, escalate, or report. The user should not have to infer safety behavior from a metric table.
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