Where Should We Use AI First? — Prioritization & Safe-Pilot Workshop Kit

Welcome

This workshop kit helps healthcare teams choose their first AI pilots by balancing the potential clinical and operational impact against feasibility, safety, and clinician adoption. Use this guide to run a 90–150 minute prioritization workshop that produces a ranked pilot roadmap and a clear set of next steps, ownership, and monitoring measures.

Why this matters

AI pilots can create measurable gains but also introduce workflow disruption, bias, safety, and regulatory burdens if chosen or executed poorly. This kit is designed to protect patient safety and clinician trust while helping you find pilots that deliver clear, measurable benefit quickly.

Before the workshop: pre-work (1–2 weeks ahead)

• Collect 4–8 candidate use-cases (brief 1-paragraph description each) from clinical, operational, and IT stakeholders.
• Assemble a one-page data readiness summary for each candidate: available data sources, quality issues, linkage feasibility, and sample size.
• Identify 1–2 domain experts who can attend to confirm clinical value and safety concerns.
• Share a 5-minute primer on your AI governance principles so participants understand guardrails before scoring.

Suggested participants

• Clinical lead (physician, nurse or therapist)
• Quality & patient safety representative
• Operational manager (scheduling, bed flow, lab)
• Data/analytics or informatics lead
• IT/security representative
• Patient experience or equity representative (when available)
• Facilitator (neutral, timekeeper)

Agenda (90–150 minutes)

1. Welcome & objectives (5–10 min) — clarify desired outcomes and decision rules.
2. Quick grounding: AI governance & safety guardrails (5–10 min).
3. Present candidate use-cases (10–20 min) — 2–3 min per use-case with data-readiness highlights.
4. Stakeholder mapping & risks (10–15 min) — who owns the problem, who benefits, who might be harmed.
5. Scoring walkthrough & calibration (10 min) — explain rubric and do one practice score together.
6. Scoring and discussion (20–30 min) — participants score each use-case independently then discuss outliers.
7. Rank, agree pilots and assign owners (10–15 min) — agree on 1–2 pilots to start and immediate next steps.
8. Define minimum viable monitoring & safety checklist for chosen pilots (10–15 min).
9. Wrap-up & actions (5–10 min) — confirm owners, milestones, and timeline.

Stakeholder map (facilitation note)

For each candidate, quickly map:

• Primary owner (problem owner)
• Primary beneficiaries (patients, staff, system)
• Those at risk (who could be harmed or burdened)
• Data owners and system integrators
• Policy / compliance stakeholders

Weighted scoring rubric (example)

Use numeric scores (0–5) for each criterion and apply weights to compute a final score. Adjust weights to reflect your organization’s priorities. Example default weights sum to 100%.

1. Clinical impact & patient safety — Weight 30%. Questions: Will this reduce harm or improve measurable outcomes? Score 0–5.
2. Risk to safety, bias, or equity — Weight 20%. Questions: Could this introduce harm or unfairness? Lower score for higher risk.
3. Data readiness — Weight 15%. Questions: Are the required data available, high-quality, representative, and accessible?
4. Workflow fit & clinician burden — Weight 10%. Questions: Will this integrate smoothly or add cognitive/administrative burden?
5. Regulatory & privacy complexity — Weight 10%. Questions: Does this require new approvals, consents, or complex de-identification?
6. Adoption likelihood / clinical ownership — Weight 10%. Questions: Is there a champion and a clear path to clinician adoption?
7. Operational & financial feasibility — Weight 5%. Questions: Is the technical build and ongoing cost reasonable for the expected benefit?

How to calculate the final score

For each criterion: normalize raw score (0–5) to percent, multiply by weight, then sum across criteria. Example: if clinical impact = 4 (80%) × 30% = 24 points. Sum gives a 0–100 score. Use score bands (e.g., 75–100 = high priority, 50–74 = consider with mitigations, <50 = low priority).

Use-case canvas (fill one per candidate)

Sample scored example (illustrative)

Use-case: Early sepsis risk alert in the ED

• Clinical impact: 5 (high) — weight 30% → 30 × 1.0 = 30
• Safety/bias risk: 3 — weight 20% → 20 × 0.6 = 12
• Data readiness: 4 — weight 15% → 15 × 0.8 = 12
• Workflow fit: 3 — weight 10% → 10 × 0.6 = 6
• Regulatory complexity: 3 — weight 10% → 10 × 0.6 = 6
• Adoption likelihood: 4 — weight 10% → 10 × 0.8 = 8
• Operational feasibility: 3 — weight 5% → 5 × 0.6 = 3

Approximate final score = 77 → High priority, proceed to a controlled pilot with safety monitoring and equity review.

Output template: prioritized pilot roadmap

For each prioritized pilot capture:

• Pilot name and owner
• Objective and success metrics (primary & secondary)
• Baseline measures and data sources
• Key milestones (design, validation, deploy in shadow, controlled live, scale)
• Monitoring plan (performance, safety events, drift, bias checks)
• Stop/go criteria and review cadence
• Estimated effort and budget

Minimum viable monitoring & safety checklist (to agree in workshop)

1. Define real-time clinician contact path for any safety concerns.
2. Identify primary performance metrics and drift thresholds for automated alerts.
3. Agree on test dataset and fairness checks before deployment.
4. Plan shadow runs (system predictions visible but not actionable) when possible.
5. Document data lineage and access controls.
6. Set review cadence (weekly during pilot ramp, monthly after stabilization).

Facilitator tips

• Keep scoring independent initially to avoid groupthink, then discuss differences openly.
• Encourage clinicians to speak to real workflow burden — adoption is as important as accuracy.
• Be explicit about acceptable risk and what would stop a pilot early.
• Capture dissenting opinions and unresolved questions as action items.

Artifacts to save in your domain

• Completed use-case canvases and scorecards
• Prioritized pilot roadmap with owners and milestones
• Monitoring & safety checklist and checklist results
• Post-pilot evaluation template (outcomes, lessons, clinician feedback)

Next steps template (after the workshop)

1. Owner finalizes pilot charter and shares with governance group (within 1 week).
2. Data & privacy review completes feasibility checklist (2 weeks).
3. Technical prototype/shadow evaluation planned (4–8 weeks) with specified metrics.
4. Pilot review at agreed cadence; stop/go decisions documented.

Where interactivity helps

This static kit is ready to use, but an interactive scoring form that stores scores, generates ranked lists, and saves completed canvases would speed workshops and preserve organizational memory.

Appendix: quick checklist for choosing first pilots

• Is there a clear, measurable outcome the pilot will change?
• Is a clinician champion willing to test and iterate?
• Are the required data accessible and of sufficient quality?
• Can the pilot start in a contained environment (unit, shift, or user group)?
• Is there a monitoring plan with clear stop criteria?