checklist

Clinical Decision Support & AI Safety Checklist

An interactive pre-deployment checklist to assess clinical appropriateness, dataset validation, workflow fit, alert risk, monitoring readiness, rollback criteria, and governance before deploying CDS or clinical AI.

Interactive Tool

Clinical Decision Support & AI Safety Checklist

This interactive checklist helps teams systematically assess safety, validity, workflow fit, monitoring, and governance before deploying a clinical decision support (CDS) or clinical AI tool. Use this during pilot readiness reviews and before any production rollout. Save responses to create an auditable record; update and resubmit after pilot or remediation.

Keep answers factual and attach or link validation artifacts where possible (validation reports, dataset snapshots, clinician feedback, test-case logs).

Confirm the intended use, target population, decision point, and supporting evidence or guidelines.
Include setting (ED, inpatient, outpatient), actors (nurse, physician, pharmacist), and the action expected after the recommendation.
Who is expected to use/act on recommendations?
Describe the datasets used for validation, sample sizes, populations, time ranges, and where artifacts are stored.
Call out under-represented groups, missing data patterns, labeling quality, or covariate shifts.
Attach validation report or link to metrics.
List metrics and target thresholds used to decide acceptable performance.
1 = poor fit (major workflow change), 5 = excellent (minimal change).
1.0 10.0
Describe UI changes, order entry integrations, order sets, or training required.
Estimate risk that the tool will increase noisy alerts or interrupt clinicians unnecessarily.
Describe thresholds, filtering, batching, or role-specific routing to reduce unnecessary interruptions.
Monitoring should include metric thresholds, ownership, frequency, and data sources.
List the live metrics (e.g., drift indicators, outcome measures, alert volumes) and how often they are reviewed.
Describe statistical monitoring, population shift checks, and automated alerts for performance degradation.
Examples: sustained metric breach for X days, safety events, clinician-reported harms.
Detail who can enact rollback, communication plan, technical steps, and quick mitigations.
At least clinical, informatics, safety, and legal should be represented.
URLs or document locations for sign-off records.
Confirm a focused 30-day review to capture early issues and clinician feedback.
Owner, date, and expected evidence to review.
Confirm a more comprehensive 90-day evaluation of outcomes and safety signals.
Owner, date, and expected evidence to review.
Select the governance decision and attach justification in the comment field.
Summarize reasons for the decision, remaining risks, and next steps.
Person responsible for monitoring, incident response, and governance.
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