Raekis AI Implementation Playbook (DSO)

Executive Summary

Raekis AI automates diagnostic interpretation of intraoral and extraoral dental imaging, reducing clinician review time by 40-60% while flagging pathology with radiologist-grade accuracy. For DSOs operating 10+ locations, this translates to standardized diagnostic protocols across the network, faster patient turnaround, and measurable liability reduction—critical when managing clinical consistency at scale.

Pre-Implementation Checklist

• Imaging infrastructure audit: Confirm all 10+ locations have compatible PACS systems (compatibility with Raekis integrations) and verify network bandwidth supports cloud-based image uploads without bottlenecks.
• Clinical champion identification: Designate a senior clinician or ops lead at each location who will own staff training and troubleshoot adoption friction before escalating to support.
• Data governance protocol: Establish patient consent language, HIPAA audit procedures, and de-identification workflows if Raekis processes images in the cloud (review your Business Associate Agreement).
• Baseline diagnostic metrics: Capture current average time-per-image reviewed, diagnostic miss rate (if tracked), and patient complaint frequency related to imaging delays at 3-5 representative locations.
• Staff skill mapping: Identify clinicians who may resist AI assistance early; plan 1-on-1 onboarding with them before group rollout.
• Imaging equipment standardization check: Verify sensor calibration and settings are consistent across locations; poor image quality degrades AI output and creates user frustration.
• IT resource allocation: Assign dedicated IT resource for 8-12 weeks post-launch to manage logins, integrations, and troubleshooting across the network.

Implementation Timeline

Phase 1: Pilot & Infrastructure (Weeks 1-4)

• Week 1-2: Deploy Raekis at 2 high-volume locations with strong tech adoption; run parallel diagnostics (AI + human review) to build internal validation dataset.
• Week 3-4: Collect clinician feedback on workflow integration, image rejection rates, and accuracy concerns; document any PACS integration bugs and escalate to Raekis support.
• Milestone: 95%+ image acceptance rate (AI successfully processes images without resubmission).

Phase 2: Network Rollout (Weeks 5-10)

• Week 5-6: Deploy to locations 3-6; conduct live training sessions at each site covering AI output interpretation, override protocols, and escalation paths for high-confidence edge cases.
• Week 7-8: Stagger rollout to remaining locations (7-10+); use lessons from earlier sites to customize training (e.g., if pediatric imaging is weak at your network, front-load that training).
• Week 9-10: Monitor adoption dashboards; ensure <5% of clinicians are reverting to non-AI workflows or generating excessive manual overrides.
• Milestone: >80% of diagnostic imaging routed through Raekis across 8+ locations.

Phase 3: Optimization & Governance (Weeks 11-16)

• Establish monthly audit of Raekis flagged cases vs. clinician overrides; identify systematic gaps (e.g., periapical pathology consistently missed at one location = image quality or training issue).
• Create standardized escalation protocol: Raekis high-confidence finding → clinician review → patient notification pathway.
• Roll out advanced features (e.g., multi-scan analysis, batch prioritization) at high-volume locations.

Phase 4: Continuous Improvement (Ongoing, Month 4+)

• Quarterly case review with clinical leadership to validate AI performance against manually graded reference sets.
• Annual HIPAA & data security audit of Raekis integrations.
• Periodic staff retraining as new clinicians join the DSO.

Key Metrics to Track

1. Diagnostic throughput: Average images processed per clinician-hour (target: +35-50% vs. baseline).
2. Image-to-diagnosis cycle time: Days from exposure to finalized report (target: <24 hours; baseline typically 2-5 days in DSOs without AI).
3. AI concordance rate: Percentage of Raekis findings confirmed by clinician review (target: >92% for high-confidence flags; <2% false positive override rate).
4. User adoption velocity: % of clinicians consistently using Raekis by week 12 (target: >85%; track by location and role).
5. Diagnostic confidence improvement: Pre/post survey: clinician confidence in ruling out pathology (target: +25-40% improvement score, measured at 6 and 12 weeks).
6. Revenue impact: Incremental patient case acceptance due to faster diagnostics + reduced re-takes from image quality flagging (target: 2-4% net revenue lift within 6 months).

Common Pitfalls

Pitfall 1: Treating AI as diagnostic replacement, not decision support. Clinicians who expect Raekis to eliminate their review step often become frustrated when edge cases still require manual judgment. Avoid: Frame Raekis in onboarding as a "second reader" that flags priority cases, not a substitute for clinical expertise. Use case studies showing where AI caught early caries or bone loss the clinician might have missed on a busy day.

Pitfall 2: Rolling out to all 10+ locations simultaneously without pilot validation. If your PACS integration fails or staff training is weak, fixing 10 broken workflows at once creates churn and backlash. Avoid: Pilot at 2 locations minimum; don't scale until >95% image acceptance and <10% clinician override rate is stable for 2+ weeks.

Pitfall 3: Ignoring image quality variability across locations. Some practices have inconsistent sensor settings or aging equipment; Raekis output degrades on poor-quality images. Clinicians blame the tool, not their imaging. Avoid: Conduct a pre-implementation imaging audit; standardize sensor calibration and retake protocols; train hygienists on positioning consistency before Raekis launch.

Pitfall 4: Underestimating staff training depth. Clinicians need to understand why Raekis flagged something, not just what was flagged. Shallow training leads to override-happy users who ignore AI findings. Avoid: Require hands-on, case-based training with your clinical champion at each location; provide laminated reference cards; schedule refreshers at 6 weeks and 12 weeks.

Pitfall 5: No escalation protocol for high-confidence AI findings. Raekis flags an aggressive lesion, but no clear path exists for urgent clinician review or patient notification. Avoid: Document a 24-hour review SLA for high-confidence findings; assign ownership (e.g., regional clinical director reviews flagged cases daily); track SLA breach rate monthly.

Cost & ROI Framework

Implementation Cost Range: $80,000–$150,000 (Year 1)

• Raekis software licensing: $40,000–$70,000 (typically $200–$400/location/month for 10+ location DSO; often volume-discounted).
• Integration & IT setup: $15,000–$30,000 (PACS integration, user provisioning, security audit).
• Training & change management: $10,000–$20,000 (clinical champion stipends, in-person sessions, materials).
• Contingency/support: $5,000–$15,000.

Payback Period: 6–10 months

ROI Drivers:

1. Clinician time recovery (~$35–50K annual): Imaging review time drops ~8–12 hours/week across the DSO (10 locations × 1–1.5 hrs/location/week saved × $50–65/hour clinician rate).
2. Reduced diagnostic re-takes & complaints (~$15–25K annual): Fewer image quality issues and missed pathology = fewer callbacks, retakes, and liability risk.
3. Patient throughput acceleration (~$40–80K annual): Faster diagnostics enable same-day or next-day diagnosis, increasing case acceptance and patient satisfaction scores, translating to 2–4% net revenue lift on hygiene/restorative upsell.

Year 2+ ROI: 250–400% (licensing + support ~$50K annually; benefits compound as staff expertise deepens and integration optimizes).

Implementation Owner Accountability: Assign a single DSO operations lead (not IT, not a clinician