DEXIS / Envista — Implementation Playbook (DSO)

DEXIS / Envista AI Diagnostic Imaging Implementation Playbook

For Dental Service Organizations (15–50 Locations)

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1. Executive Summary

What DEXIS AI Does

DEXIS AI, part of Envista's diagnostic imaging ecosystem, uses artificial intelligence to analyze dental radiographs and automatically detect potential pathology including caries, periapical lesions, calculus, and bone loss. The system overlays findings directly on images within the clinical workflow, providing real-time diagnostic support that enhances clinical accuracy and patient communication.

Why DSOs Specifically Benefit from AI Diagnostic Imaging

Scale Advantages:

• Standardizes diagnostic protocols across all providers and locations, reducing clinical variability that creates compliance and quality risks
• Aggregates imaging data to identify trends, outliers, and training needs at the portfolio level
• Amortizes implementation costs and vendor relationship management across dozens of locations

Operational Benefits:

• Accelerates case acceptance through visual patient education—patients who see AI-highlighted pathology are more likely to accept treatment
• Reduces missed diagnoses and associated liability exposure across your entire footprint
• Creates defensible documentation that protects against malpractice claims and payer audits
• Enables centralized quality assurance and clinical oversight by CDOs

Strategic Value:

• Positions your DSO as technology-forward for recruitment, retention, and potential exit/acquisition
• Generates portfolio-wide clinical intelligence for capacity planning and service mix optimization

Expected Timeline: Decision to Full Deployment

DSO Size	Pilot Phase	Wave Rollout	Full Deployment
15–25 locations	Weeks 1–6	Weeks 7–16	4–5 months
26–40 locations	Weeks 1–6	Weeks 7–20	5–6 months
41–50 locations	Weeks 1–8	Weeks 9–24	6–7 months

Timeline assumes 2–3 pilot locations, followed by waves of 5–8 locations, with 2-week buffers between waves.

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2. Pre-Implementation Checklist (Weeks 1–2)

Technical Requirements

Hardware Requirements

☐ Verify all imaging sensors are DEXIS-compatible or confirm cross-compatibility with existing sensors (Gendex, KaVo, Schick, etc.) ☐ Workstations meet minimum specs: Windows 10/11 Pro, 16GB RAM, dedicated GPU recommended for AI processing ☐ Monitors support adequate resolution (1920x1080 minimum; 4K recommended for diagnostic imaging) ☐ Confirm server capacity if deploying on-premise image storage vs. cloud

Network Requirements

☐ Minimum 100 Mbps upload/download per location for cloud-based AI processing ⚠️ Common failure point: underestimating bandwidth needs ☐ Network latency under 50ms to cloud endpoints ☐ VLAN segmentation for HIPAA compliance if required by your security posture ☐ Static IP addresses if vendor requires whitelisting

Software Requirements

☐ Current PMS version compatibility confirmed (see Section 5 for specifics) ☐ Existing DEXIS Imaging Suite version documented per location ☐ Browser requirements for any web-based dashboards (Chrome/Edge latest versions) ☐ .NET Framework and other dependencies documented

Vendor Onboarding Steps

☐ 🔵 Execute enterprise Master Services Agreement (MSA) covering all locations ☐ 🔵 Establish primary vendor contacts:

• Enterprise Account Manager: _______________
• Technical Implementation Lead: _______________
• Support Escalation Contact: _______________
• Customer Success Manager: _______________ ☐ 🔵 Confirm enterprise pricing and per-location licensing structure ☐ 🔵 Schedule enterprise kickoff call with vendor implementation team ☐ 🔵 Obtain access to vendor's enterprise admin portal ☐ 🔵 Document SLA commitments (uptime guarantees, support response times) ☐ 🔵 Confirm training resources available (live sessions, on-demand library, certification programs)

Data/Access Prerequisites

☐ Compile location roster with site IDs, addresses, and primary contacts ☐ 🔵 Obtain enterprise-level API credentials from vendor ☐ Establish service account credentials for PMS integrations at each location ☐ Document imaging archive access method per location (local storage, cloud PACS, etc.) ☐ Confirm historical image migration scope—how many years of images to ingest, if any ☐ Inventory current imaging file formats (DICOM, proprietary, etc.)

Internal Stakeholder Alignment

🟣 Board/Investor Level

☐ Brief on strategic rationale for AI investment ☐ Confirm budget allocation and approval threshold ☐ Align on success metrics and reporting cadence

C-Suite Level

☐ 🟣 CEO/COO: Approve project charter and timeline ☐ 🟣 CDO: Own clinical protocol standardization and quality oversight ☐ 🟣 CFO: Approve budget, confirm ROI measurement approach ☐ CTO/IT Director: Own technical implementation and security review

Regional Manager Level

☐ Brief on rollout timeline and their role in location readiness assessment ☐ Establish communication cadence (weekly during implementation) ☐ Identify regional-level blockers or concerns

Location Level

☐ Inform office managers of upcoming implementation (general awareness) ☐ Identify potential local champions (formal assessment in Section 3) ☐ Communicate that workflow changes are coming—manage expectations early

Enterprise-Level Requirements

Network Standards Across Locations

☐ Document existing network infrastructure variance across portfolio ☐ 🟣 Decide: remediate network gaps before rollout or exclude under-equipped locations from early waves ☐ Establish minimum network performance standards as go/no-go criteria

Hosting Decision

☐ 🟣 Confirm cloud-hosted (Envista cloud) vs. hybrid vs. on-premise deployment model ☐ If cloud: confirm data residency requirements are met ☐ If on-premise: document server requirements per location or centralized data center needs

Identity and Access Management

☐ 🔵 Confirm SSO compatibility (SAML 2.0, Azure AD, Okta) ☐ 🟣 Decide: implement SSO for enterprise deployment or use local credentials ☐ Design role-based access control (RBAC) structure:

• Enterprise Admin (HQ)
• Regional Admin
• Location Admin
• Provider
• Staff

Centralized Credentialing

☐ Establish process for adding/removing locations from enterprise license ☐ Document provider onboarding workflow for AI tool access ☐ Create offboarding checklist for departing providers

Baseline Metrics to Capture BEFORE Go-Live

⚠️ Critical: Capture these metrics identically across all locations BEFORE deployment to enable valid cross-location comparison and ROI measurement.

Clinical Metrics

Metric	How to Measure	Capture Period
Case acceptance rate	Accepted treatment $ / Presented treatment $	90 days pre-go-live
Average diagnosis time per patient	Time from image capture to treatment plan completion	Sample 50 patients/location
Caries detection rate	Caries diagnoses per 100 radiographs	90 days pre-go-live
Perio diagnosis rate	Perio diagnoses per 100 adult patients	90 days pre-go-live
Missed pathology rate	Re-treatment or referred cases within 12 months	Historical data

Operational Metrics

Metric	How to Measure	Capture Period
Average patient visit duration	Check-in to checkout	Sample 200 patients/location
Provider productivity	Patients seen per provider per day	90 days pre-go-live
Image retake rate	Retakes per 100 images captured	30 days pre-go-live

Financial Metrics

Metric	How to Measure	Capture Period
Claim denial rate (imaging-related)	Denied claims for imaging procedures	90 days pre-go-live
Revenue per patient	Total revenue / Patient visits	90 days pre-go-live
Treatment conversion by category	Restorative, perio, endo separately	90 days pre-go-live

Standardization Protocol for Baseline Measurement

☐ 🟣 Approve standardized metric definitions (no local interpretation) ☐ Designate single source of truth for each metric (PMS reports, BI tool, manual) ☐ Create centralized data collection template ☐ Assign regional managers to verify data accuracy from their locations ☐ Complete baseline data collection for all locations before Wave 1 go-live

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3. Location Readiness Assessment

Scoring Framework

Score each factor 1–5 per location. Composite score determines rollout wave assignment.

Factor 1: IT Infrastructure Maturity (Weight: 25%)

Score	Criteria
5	Fiber internet, <3-year-old workstations, current PMS version, DEXIS sensors already installed
4	Reliable broadband (100+ Mbps), 3–5-year-old workstations, PMS within one version of current
3	Adequate internet (50+ Mbps), some workstations need upgrades, PMS is compatible but dated
2	Inconsistent internet, majority of workstations need replacement, PMS upgrade required
1	Poor connectivity, significant hardware gaps, PMS incompatible—major remediation needed

Factor 2: Staff Tenure and Adaptability (Weight: 20%)

Score	Criteria
5	<15% annual turnover, history of successful tech adoptions, staff tenure averages 3+ years
4	15–25% turnover, generally positive tech adoption, average tenure 2–3 years
3	25–35% turnover, mixed tech adoption history, adequate stability for implementation
2	35–50% turnover, resistance to past changes, concerns about training retention
1	>50% turnover, active staffing crisis, recent failed implementations

Factor 3: Patient Volume (Weight: 15%)

Score	Criteria
5	High volume (80+ patients/day) with operational stability—high impact, manageable risk
4	Moderate-high volume (60–79 patients/day), operationally sound
3	Moderate volume (40–59 patients/day), representative of portfolio average
2	Lower volume (20–39 patients/day), limited impact but also limited risk
1	Very low volume or highly variable, operational instability

Note: Highest volume is not automatically best for Wave 1. Balance impact against risk—a high-volume location with operational instability should score lower.

Factor 4: Existing Tech Stack Compatibility (Weight: 25%)

Score	Criteria
5	Already using DEXIS imaging suite, compatible PMS with documented integration, no conflicts
4	Compatible imaging system (Gendex, KaVo), PMS integration available, minor configuration needed
3	Third-party imaging requiring integration work, PMS compatible with effort
2	Significant integration complexity, may require middleware or workarounds
1	Incompatible core systems, requires platform migration before AI deployment

Factor 5: Local Champion Availability (Weight: 15%)

Score	Criteria
5	Identified tech-forward provider AND office manager, both willing to lead implementation
4	Strong champion in either provider or OM role, other is supportive
3	Potential champion identified but needs development, general staff support
2	No obvious champion, but no active resistance
1	Key staff resistant or actively opposed, leadership vacuum at location

Composite Score Calculation

Composite Score = (IT × 0.25) + (Staff × 0.20) + (Volume × 0.15) + (Tech Stack × 0.25) + (Champion × 0.15)

Rollout Wave Assignment

Composite Score	Wave Assignment	Notes
4.0–5.0	Wave 1 (Pilot)	Select 2–3 from this group that are also geographically/regionally representative
3.0–3.9	Wave 2	Core rollout locations—bulk of portfolio
2.0–2.9	Wave 3	Require remediation or additional support
Below 2.0	Deferred	Address infrastructure/staffing issues before scheduling

Recommended Rollout Sequence Criteria

Wave 1 Pilot Selection (2–3 locations): ☐ Composite score 4.0+ required ☐ At least one location should be representative of portfolio majority (not outlier) ☐ At least one location should be geographically accessible to HQ for on-site support ☐ Avoid selecting only "easy" locations—include at least one that will surface real-world challenges ☐ 🟣 Final pilot location selection requires CDO and COO approval

Wave 2 Expansion (5–8 locations per wave cycle): ☐ All composite scores 3.0+ or remediation completed ☐ Group by region to enable regional manager oversight efficiency ☐ Balance workload across IT support resources

Wave 3 Completion: ☐ Remaining locations with any score ☐ Apply lessons learned from Waves 1–2 ☐ Allocate additional support resources for lower-readiness locations

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4. Rollout Strategy

Wave Structure Recommendation

For a 25-location DSO example:

Wave	Locations	Duration	Cumulative Timeline
Wave 1 (Pilot)	3 locations	4 weeks	Weeks 1–4
Buffer & Learning Capture	—	2 weeks	Weeks 5–6
Wave 2a	6 locations	3 weeks	Weeks 7–9
Buffer	—	1 week	Week 10
Wave 2b	6 locations	3 weeks	Weeks 11–13
Buffer	—	1 week	Week 14
Wave 3	10 locations	4 weeks	Weeks 15–18
Stabilization	All	2 weeks	Weeks 19–20

Adjust location counts proportionally for larger portfolios. Consider parallel wave tracks for 40+ locations with dedicated support teams.

Wave 1 Pilot Location Selection Criteria

Required Criteria (must meet all): ☐ Composite readiness score ≥ 4.0 ☐ Office manager committed to daily implementation log for 4 weeks ☐ At least one provider willing to actively provide feedback ☐ No major planned disruptions (renovation, key staff departures, PMS migration)

Preferred Criteria (meet at least 2 of 4): ☐ Represents dominant practice type in portfolio (GP vs. specialty mix) ☐ Within 2-hour travel of HQ or regional support hub ☐ Has experienced past technology implementations successfully ☐ Patient demographic representative of portfolio majority

Strategic Criteria: ☐ 🟣 Include at least one location that leadership is "watching"—early success here builds momentum ☐ Include geographic diversity if portfolio spans multiple states (regulatory learning)

Timeline Per Wave with Learning Capture

Wave 1 (Pilot) — 4 Weeks

Week 1: Configuration & Training

• Days 1–2: Technical setup and integration validation
• Days 3–4: Champion training (on-site or intensive remote)
• Day 5: Staff training delivered by champion

Week 2: Soft Launch

• System live in "shadow mode" — AI runs but findings optional
• Daily 15-minute check-in calls with central team
• Document all issues in standardized log

Week 3: Full Go-Live

• AI findings integrated into standard workflow
• Daily check-ins continue
• Begin collecting user feedback

Week 4: Stabilization

• Address outstanding issues
• Check-ins move to every-other-day
• Begin drafting lessons learned

Buffer Period — 2 Weeks

☐ Compile lessons learned document from pilot ☐ Identify configuration changes to standardize for future waves ☐ Update training materials based on pilot feedback ☐ 🟣 Present pilot results to leadership, confirm go/no-go for Wave 2 ☐ Remediate any systematic issues discovered ☐ Recognize and celebrate pilot location champions

Go/No-Go Criteria to Advance Waves

Must Pass (All Required):

Criterion	Threshold
System uptime	≥99% during pilot period
Critical bugs	Zero open critical severity issues
Staff adoption	≥90% of staff completed training
Provider adoption	≥80% of providers actively using AI findings
Data integrity	No PHI exposure incidents, no data loss
Patient experience	No significant patient complaints attributed to system

Should Pass (Pass ≥3 of 5):

Criterion	Threshold
User satisfaction	Net Promoter Score ≥6 (1–10 scale)
Workflow disruption	Average visit time increased <5 minutes
Support ticket volume	Declining trend week-over-week
Image processing time	<10 seconds for AI analysis
Champion confidence	Champions report readiness to scale

🟣 Decision Authority

• Wave 1 → Wave 2: CDO and COO joint approval
• Wave 2a → Wave 2b: Regional Manager + Central Project Lead
• Wave 2 → Wave 3: COO approval (CDO advisory)

Rollback Plan

Triggers for Wave Pause

• System uptime <95% for 48+ hours
• 2+ critical severity bugs affecting patient care
• Significant patient safety concern identified
• Widespread provider refusal to use system
• Major data breach or HIPAA incident

Rollback Procedure

Immediate (0–4 hours): ☐ Notify vendor support of issue and potential rollback ☐ Central IT lead assesses scope (single location vs. wave-wide) ☐ Regional manager notified ☐ If patient safety issue: immediately disable AI overlay, revert to standard imaging workflow

Short-term (4–24 hours): ☐ 🟣 COO/CDO briefed on situation ☐ Location champions informed of temporary pause ☐ Patient-facing communication prepared if needed ☐ Root cause analysis initiated with vendor

Recovery: ☐ Document issue and resolution in risk register ☐ Vendor provides remediation plan with timeline ☐ 🟣 Leadership approves remediation before wave resumes ☐ Affected locations receive additional support during re-deployment ☐ Adjust future wave timelines as needed

Isolation Protocol

• Rollback issues at one location should NOT automatically halt all locations in a wave
• Assess whether issue is location-specific (local config, integration, staff) vs. systemic
• If systemic: pause all locations in current wave
• If location-specific: pause that location, continue others with monitoring

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5. Configuration & Integration (Weeks 2–3)

Practice Management System Integration

Dentrix Enterprise Integration

Prerequisites: ☐ Dentrix Enterprise version 8.0 or higher confirmed ☐ Multi-site license active and accessible from central IT ☐ Integration module license obtained from Henry Schein (if required) ☐ Service account created with appropriate permissions per location

Integration Steps:

1. 🔵 Obtain DEXIS integration package from vendor (estimated: 1 hour)
2. Deploy integration service to Dentrix Enterprise server or designated integration server (estimated: 2 hours)
3. Configure HL7/API connection strings for each location database (estimated: 30 min/location)
4. Map patient identifier fields (ensure PatientID consistency across systems)
5. Configure image routing rules — DEXIS images automatically associated with correct patient chart
6. ⚠️ Test bi-directional data flow: patient demographics → DEXIS, imaging data → Dentrix (estimated: 1 hour/location)
7. Verify image thumbnails appear in patient chart within Dentrix
8. Configure AI findings documentation flow — confirm AI detections are captured in clinical notes

Eaglesoft Integration

Prerequisites: ☐ Eaglesoft version 21 or higher per location ☐ eClinicalWorks or Patterson bridge license (if applicable) ☐ Local database access credentials available

Integration Steps:

1. 🔵 Request Eaglesoft integration documentation from DEXIS support
2. Install DEXIS-Eaglesoft bridge application on each workstation capturing images (estimated: 30 min/workstation)
3. Configure image storage paths — ensure network paths accessible from all clinical workstations
4. Map patient demographic fields between systems
5. ⚠️ Test patient lookup functionality from DEXIS imaging workflow
6. Verify captured images appear in correct patient charts within Eaglesoft
7. Configure AI overlay preferences per provider (settings sync)

Open Dental Integration

Prerequisites: ☐ Open Dental version 22.1 or higher ☐ Open Dental API access enabled ☐ Bridge configured for imaging integration

Integration Steps:

1. Navigate to Setup > Program Bridges in Open Dental
2. Enable DEXIS bridge (pre-configured in Open Dental)
3. Configure file path to DEXIS Imaging executable
4. Set communication method (CLI arguments or API depending on version)
5. Map patient identifier fields
6. Test end-to-end: select patient in Open Dental → launch DEXIS → capture image → verify appears in patient record
7. 🔵 Request AI overlay configuration assistance from DEXIS support if not auto-configured

Imaging System Integration

DEXIS-Native Imaging

If locations already use DEXIS sensors and DEXIS Imaging Suite:

☐ Verify DEXIS Imaging Suite version (10.0+ required for AI features) ☐ 🔵 Request AI module activation from Envista (license key or cloud activation) ☐ Install AI module update if software version requires it ☐ Configure cloud connectivity for AI processing (verify firewall rules) ☐ Enable AI overlay display settings per provider preferences ☐ Confirm image quality thresholds for AI processing (low-quality images may not process)

Third-Party Sensor Integration (Gendex, Schick, Carestream, etc.)

☐ 🔵 Confirm DEXIS compatibility with existing sensors (vendor support ticket) ☐ If compatible: configure DEXIS Imaging to accept images from third-party sensors ☐ ⚠️ Test image quality — some sensors may require calibration for optimal AI analysis ☐ Configure image import workflow if using separate imaging software currently ☐ 🔵 Plan for migration if third-party integration not supported (discuss with vendor)

Panoramic and CBCT Integration

☐ Confirm DEXIS AI supports modalities beyond intraoral (pano, CBCT vary by product tier) ☐ 🔵 Verify licensing includes 2D pan and 3D analysis if applicable ☐ Configure DICOM image routing from panoramic units to DEXIS ☐ Test AI analysis on panoramic images — different pathology detection models apply

Test Environment Setup

Recommended Approach for DSOs

☐ 🟣 Establish centralized test environment (not per-location) for cost efficiency ☐ Mirror production configuration in test ☐ Use anonymized patient data or synthetic test data (HIPAA compliance) ☐ Include integration touchpoints with PMS test environments if available

Validation Checklist

Pre-Go-Live Validation (required for each location):

Test Case	Pass Criteria	Tested By	Date
Patient lookup from DEXIS	Correct patient loads within 3 seconds
Image capture (sensor)	Image captured and displayed correctly
AI analysis execution	AI overlay appears within 15 seconds
AI findings accuracy spot-check	Findings appear reasonable (provider validates)
Image saved to patient chart	Image visible in PMS patient record
AI findings documented	AI detections captured in clinical notes
Multi-provider access	Different providers see their own settings
Report generation	Can generate AI-assisted report for patient
Cloud connectivity failover	System functions (without AI) if cloud unavailable
Audit trail	Actions logged for HIPAA compliance

Data Migration / Historical Image Ingestion

☐ 🟣 Decide: ingest historical images for AI analysis or start fresh with new images only

• Recommendation: start fresh for most locations; historical ingestion adds cost and complexity with diminishing returns ☐ If ingesting historical images:
  • Inventory total image volume per location
  • 🔵 Request bulk processing quote from Envista
  • Estimate timeline (typically 1,000–5,000 images/hour depending on infrastructure)
  • ⚠️ Plan for AI false-positive review — historical images may surface unexpected "findings" ☐ Archive access permissions confirmed for legacy imaging servers

Security and HIPAA Compliance Verification

Enterprise-Level HIPAA Checklist

Business Associate Agreement: ☐ 🔵 🟣 Execute BAA with Envista at enterprise level (not per-location) ☐ Confirm BAA covers all locations in portfolio ☐ Review BAA terms with legal counsel ☐ Document BAA execution date and review schedule (annual renewal)

Data Governance: ☐ 🟣 Define data ownership and retention policies for AI-processed images ☐ Confirm data residency (where data is stored geographically) ☐ Document data processing workflow: where images go, what's stored where ☐ Verify right to data export/portability if vendor relationship ends ☐ ⚠️ Confirm vendor's data breach notification procedures and timelines

Access Controls: ☐ Role-based access control (RBAC) implemented per enterprise design ☐ User access provisioning workflow documented ☐ User access de-provisioning workflow documented (critical for terminations) ☐ Minimum necessary access principle applied ☐ Administrative access limited and logged

Technical Safeguards: ☐ Encryption in transit (TLS 1.2+) confirmed ☐ Encryption at rest confirmed for stored images ☐ Multi-factor authentication for admin access (recommended for all users) ☐ Audit logging enabled and retained per policy (minimum 6 years recommended) ☐ Session timeout configured appropriately

Compliance Documentation: ☐ 🔵 Obtain vendor's SOC 2 Type II report ☐ 🔵 Obtain vendor's HIPAA compliance attestation ☐ Document configuration settings that support compliance ☐ Include AI system in annual HIPAA risk assessment ☐ Create incident response procedure addendum for AI system

Standardized Configuration Template

Settings to Standardize Centrally (identical across all locations):

Setting Category	Specific Setting	Standard Value
AI Detection	Pathology categories displayed	Caries, periapical lesions, calculus, bone loss (all enabled)
AI Detection	Confidence threshold for display	≥70% (adjust based on pilot feedback)
Display	Overlay color scheme	Red: high confidence, Yellow: moderate
Display	Default overlay visibility	On (providers can toggle off)
Documentation	AI findings auto-populate notes	Enabled
Documentation	Disclaimer language	[Standard corporate language]
Security	Session timeout	15 minutes
Security	Failed login lockout	5 attempts
Integration	PMS sync frequency	Real-time
Reporting	Report template	Corporate standard template

Settings to Allow Local Discretion:

Setting Category	Specific Setting	Local Decision By
Display	Provider-specific overlay preferences	Individual provider
Workflow	Image capture workflow order	Office manager + lead provider
Workflow	AI review checkpoint (before/after exam)	Provider
Communication	Patient education display style	Office manager
Scheduling	AI processing during appointment vs. batch	Office manager based on workflow

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6. Team Training Plan

Train-the-Trainer Model

Champion Selection Criteria

Required Qualifications: ☐ Employed at location ≥ 12 months (stability) ☐ Will remain at location through implementation and 90 days post ☐ Demonstrates comfort with technology (uses existing systems proficiently) ☐ Respected by peers (clinical credibility if provider, operational credibility if OM) ☐ Available for 8 hours initial training + 2 hours ongoing support weekly

Preferred Qualifications: ☐ Previous experience training others ☐ Positive attitude toward change and innovation ☐ Strong communication skills ☐ Track record of completing assigned projects

Ideal Champion Profile:

• Primary Champion: Office Manager (operational focus) OR Lead Hygienist (clinical focus)
• Secondary Champion: Provider (clinical authority and adoption modeling)
• Having both an OM champion and provider champion is ideal but not required

Champion Responsibilities

Pre-Go-Live:

• Complete certification training (4–6 hours)
• Customize standard training materials for location-specific workflows
• Schedule and deliver role-specific training to all staff
• Verify training completion and competency
• Coordinate go-live logistics with central team

Go-Live and Post:

• Serve as first point of contact for location staff issues
• Conduct daily check-ins with central team during first week
• Escalate technical issues appropriately
• Reinforce adoption and address resistance
• Train new hires on system

Ongoing:

• Monthly 30-minute check-in with central team
• Quarterly refresher communication to location staff
• Report adoption metrics and user feedback

Champion Certification Training (6 hours)

Module	Duration	Format	Content
System Overview	1 hour	Live + Demo	What DEXIS AI does, how it works, key benefits
Technical Operations	1 hour	Hands-on	Login, navigation, basic troubleshooting, escalation paths
Clinical Workflow	1.5 hours	Hands-on	Image capture workflow, AI findings interpretation, patient communication
Training Delivery	1.5 hours	Workshop	How to train others, role-specific modules, common questions
Administrative Functions	0.5 hour	Demo	Reporting, user management, settings
Certification Assessment	0.5 hour	Quiz + Simulation	Demonstrate competency to train others

Standardized Training Materials (Created Centrally)

☐ Champion Facilitator Guide (step-by-step training delivery instructions) ☐ Role-specific slide decks (Provider, Hygienist, Front Desk, Billing) ☐ Hands-on exercise worksheets for each role ☐ Day 1 Cheat Sheets (one-pagers, laminated, for each role) ☐ FAQ document (common questions and answers) ☐ Video library access (for self-paced learning and new hire training) ☐ Training completion sign-off forms ☐ Competency assessment quizzes per role

Materials Champions Customize Locally

☐ Training schedule (times that fit location operations) ☐ Location-specific workflow nuances (room setup, patient flow) ☐ Local examples and case studies ☐ Location-specific escalation contacts

Role-Specific Training Outlines

Dentists/Providers Training (90 minutes)

Learning Objectives:

• Interpret AI findings on radiographs accurately
• Integrate AI insights into clinical decision-making
• Communicate AI-supported diagnoses to patients effectively
• Know when and how to override AI suggestions

Module Content:

Section	Duration	Content
Introduction	10 min	Why AI imaging, what it does, what it doesn't do
Clinical Workflow	25 min	How AI findings appear,