DEXIS / Envista
Implementation PlaybookDSO · Group Practice

DEXIS / Envista

Step-by-step implementation guide — pre-implementation checklist, onboarding, staff training, go-live runbook, and ROI tracking.

DEXIS / Envista — Implementation Playbook (DSO)

DEXIS Diagnostic Imaging AI Implementation Playbook

Enterprise Deployment Guide for Dental Support Organizations

1. Executive Summary

What DEXIS Delivers

DEXIS, part of the Envista Holdings portfolio, provides AI-powered diagnostic imaging solutions that automatically analyze dental radiographs to detect pathologies including caries, periapical lesions, calculus, and bone loss. The system integrates with existing imaging workflows to provide real-time diagnostic assistance, generating visual overlays and confidence scores that support—but do not replace—clinical decision-making.

Why DSOs Gain Disproportionate Value from Diagnostic Imaging AI

Scale Advantages:

  • Standardized diagnostic protocols across 15–50+ locations eliminate provider-to-provider variability that plagues multi-site operations
  • Centralized data aggregation enables portfolio-wide clinical insights impossible to achieve with siloed imaging systems
  • Bulk licensing negotiations and shared infrastructure reduce per-location implementation costs by 30–40%

Operational Leverage:

  • Consistent AI-assisted diagnostics support associate dentists who may lack decades of radiographic interpretation experience
  • Real-time detection reduces missed pathology—a liability risk that compounds across locations
  • Standardized imaging workflows accelerate new provider onboarding from weeks to days
  • Aggregated diagnostic data creates defensible clinical quality metrics for payor negotiations and M&A due diligence

Financial Impact at Scale:

  • Case acceptance improvements of 10–25% compound meaningfully across 15–50 locations
  • Reduced re-treatment rates from missed diagnoses protect margins
  • Documentation enhancement supports higher-value coding and reduces claim denials

Expected Timeline: Decision to Full Deployment

Phase Timeline Milestone
Decision to Wave 1 Go-Live Weeks 1–6 2–3 pilot locations fully operational
Wave 1 Stabilization Weeks 7–10 Pilot learnings documented, go/no-go for Wave 2
Wave 2 Deployment Weeks 11–16 Next 5–8 locations live
Wave 3+ Full Rollout Weeks 17–24 Remaining locations deployed
Total Portfolio Deployment 5–6 months All locations live and optimized

Note: Timeline assumes 25-location DSO. Scale appropriately for portfolio size.

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

Technical Requirements

Hardware Requirements (Per Location)

☐ Workstations: Minimum Intel i5 (8th gen+) or AMD Ryzen 5, 16GB RAM, SSD storage ☐ Display: Medical-grade monitors recommended; minimum 1920x1080 resolution ☐ Existing sensors: Verify DEXIS sensor compatibility or identify upgrade requirements ☐ Server (if on-premise component): Confirm specifications with Envista technical team 🔵

Software Requirements

☐ Operating system: Windows 10/11 Professional (64-bit) across all clinical workstations ☐ Practice Management System: Confirm version compatibility (see Section 5) ☐ Imaging software: Current DEXIS Imaging Suite or migration path identified ☐ Browser requirements: Chrome/Edge latest version for any web-based components

Network Requirements ⚠️

☐ Bandwidth: Minimum 100 Mbps symmetric per location; 250+ Mbps recommended for high-volume sites ☐ Latency: <50ms to cloud endpoints for real-time AI analysis ☐ Firewall: Whitelist DEXIS/Envista cloud endpoints (request list from vendor) 🔵 ☐ VPN/SD-WAN: Confirm AI traffic routing through existing network architecture

Estimated time: 4–6 hours for technical audit per location

Enterprise-Level Requirements

Network Standards Across Locations 🟣

☐ Document current network topology across all locations—identify inconsistencies ☐ Establish minimum network performance standards for AI-ready certification ☐ Determine centralized vs. location-level hosting model:

  • Centralized cloud: Single tenant, simplified management, requires consistent connectivity
  • Distributed cloud: Per-location instances, more resilient, higher management overhead
  • Hybrid: Central analytics with local processing—evaluate with Envista 🔵

Identity and Access Management 🟣

☐ SSO integration: Confirm SAML 2.0 or OAuth compatibility with existing identity provider (Okta, Azure AD, etc.) ☐ Role-based access control: Map DEXIS permission levels to DSO role hierarchy ☐ Centralized credentialing: Establish process for provider credential verification prior to AI access ☐ Automated provisioning/deprovisioning: Integrate with HR systems for staff changes

Estimated time: 8–12 hours for enterprise architecture decisions

Vendor Onboarding Steps

Step Owner Timeline Deliverable
🔵 Execute enterprise license agreement Legal/Procurement + Envista Week 1 Signed MSA and order form
🔵 Assign dedicated Envista implementation manager Vendor Week 1 Named contact with direct line
🔵 Conduct technical discovery call IT + Envista Week 1 Infrastructure gap assessment
🔵 Obtain enterprise admin credentials IT + Envista Week 1 Admin portal access confirmed
🔵 Establish support escalation matrix Operations + Envista Week 1 Documented support tiers and SLAs
🔵 Schedule kickoff with clinical leadership CDO + Envista Week 2 Clinical workflow walkthrough

Key Contacts to Establish

☐ Envista Implementation Manager: Primary point of contact for deployment coordination ☐ Envista Technical Support Lead: Escalation contact for integration issues ☐ Envista Clinical Specialist: Provider training and workflow optimization ☐ Envista Enterprise Account Executive: Commercial issues, licensing questions

Estimated time: 3–4 hours of calls in Week 1

Data/Access Prerequisites

Per Location

☐ Local admin credentials for all clinical workstations ☐ PMS admin credentials with API access (if applicable) ☐ Imaging archive access—confirm storage location and format (DICOM, proprietary) ☐ Sample image export for test validation (10–20 representative images)

Enterprise Level

☐ Centralized asset inventory: Hardware/software versions at each location ☐ API keys for PMS integration (enterprise agreement if applicable) ☐ Historical imaging data migration scope: Define date range and volume 🟣 ☐ Data governance: Confirm image storage, retention, and cross-location access policies

Estimated time: 2–3 hours per location for data/access assembly

Internal Stakeholder Alignment

Stakeholder Alignment Map

Stakeholder Group Role in Implementation Required Action Timeline
🟣 Board/Investors Approve capital expenditure; understand AI strategy Investment memo review, quarterly update commitment Week 1
🟣 C-Suite (CEO/CFO/CDO) Champion initiative; allocate resources; approve rollout sequence Steering committee formation, bi-weekly briefing commitment Week 1
Regional Managers Cascade communication; monitor location readiness; resolve local blockers Briefing session, location assessment ownership Week 2
Location Office Managers Coordinate local logistics; champion adoption with staff Readiness assessment participation, champion nomination Week 2
Providers (Dentists/Hygienists) Clinical adoption; workflow integration; patient communication Awareness communication; training commitment Week 2–3
IT/Operations Technical deployment; integration; support Technical requirements sign-off, testing participation Weeks 1–2
Billing/RCM Understand documentation impact; adjust coding as needed Briefing on AI documentation capabilities Week 3

Approval Gates 🟣

☐ Budget approval: Enterprise license, implementation services, hardware upgrades ☐ IT security review: HIPAA compliance, data handling, vendor security posture ☐ Clinical leadership endorsement: CDO confirmation of clinical value ☐ Rollout sequence approval: Wave structure and location selection

Estimated time: 10–15 hours for stakeholder alignment activities

Baseline Metrics Capture ⚠️

Critical: Capture these metrics BEFORE any go-live to enable ROI measurement

Standardized Baseline Metrics (Identical Measurement Across All Locations)

Metric How to Measure Source System Measurement Period
Case acceptance rate Treatment presented ÷ Treatment accepted PMS reporting Prior 90 days
Radiographic findings per patient Average pathologies documented per exam PMS clinical notes Prior 90 days
Time from imaging to treatment presentation Image capture timestamp to treatment plan creation PMS workflow audit Sample 50 patients
Diagnostic re-treatment rate Retreatments due to missed pathology Clinical audit Prior 12 months
Claim denial rate (diagnostic codes) Denied claims for D0120-D0999 RCM system Prior 90 days
Provider radiograph interpretation time Minutes per FMX review Time study Sample 10 exams/provider
Patient volume (imaging) Radiographic exams per week Imaging system logs Prior 90 days

Baseline Capture Process

☐ Designate baseline data owner (recommend: VP of Operations or Analytics lead) ☐ Create standardized data collection template for all locations ☐ Train office managers on consistent metric capture methodology ⚠️ ☐ Set data submission deadline: End of Week 2 ☐ Validate data quality before aggregation—flag outliers for investigation ☐ Store baseline data in accessible format for post-launch comparison

Estimated time: 4–6 hours per location for baseline data collection

3. Location Readiness Assessment

Scoring Framework

Rate each location on the following factors using a 1–5 scale:

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

Score Criteria
5 Enterprise-grade network (250+ Mbps), workstations <2 years old, current PMS version
4 Strong network (100+ Mbps), workstations <3 years old, PMS version within 1 release
3 Adequate network (50+ Mbps), mixed workstation age, PMS version within 2 releases
2 Inconsistent network, aging workstations, PMS version outdated by 2+ releases
1 Poor network, workstations >5 years old, PMS significantly outdated

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

Score Criteria
5 Low turnover (<15%/yr), previous successful tech adoption, high training completion rates
4 Moderate turnover (15–25%/yr), recent tech adoption with minor issues, good training compliance
3 Average turnover (25–35%/yr), mixed tech adoption history, training compliance adequate
2 High turnover (35–50%/yr), previous tech adoption challenges, training compliance spotty
1 Very high turnover (>50%/yr), tech adoption failures, training compliance poor

Factor 3: Patient Volume (Weight: 20%)

Score Criteria
5 High volume (200+ patients/week): Maximum impact potential, experienced staff
4 Above average (150–200 patients/week): Strong impact potential
3 Average (100–150 patients/week): Moderate impact potential
2 Below average (50–100 patients/week): Lower impact, good for learning
1 Low volume (<50 patients/week): Limited ROI, save for later waves

Note: For pilot locations, consider scoring 3 (moderate volume) as ideal—high enough impact to matter, low enough risk to manage issues.

Factor 4: Tech Stack Compatibility (Weight: 20%)

Score Criteria
5 DEXIS imaging already in use, compatible PMS with proven API, no integration conflicts
4 Compatible imaging system, PMS integration documented, minimal conflicts
3 Compatible systems with some integration work required
2 Incompatible imaging system (upgrade required) OR significant PMS integration challenges
1 Major system upgrades required before deployment feasible

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

Score Criteria
5 Tech-forward provider AND engaged office manager willing to lead adoption
4 Strong champion in one role (provider or office manager)
3 Willing participants but no clear champion identified
2 Staff resistance identified; no champion emerged
1 Active opposition from key staff members

Composite Readiness Score Calculation

Formula:

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

Score Interpretation

Composite Score Readiness Tier Deployment Recommendation
4.0 – 5.0 Tier 1: Pilot Ready Wave 1 candidate
3.0 – 3.9 Tier 2: Standard Ready Wave 2 candidate
2.0 – 2.9 Tier 3: Needs Preparation Wave 3 after remediation
1.0 – 1.9 Tier 4: Not Ready Defer deployment; address blockers

Sample Location Assessment Matrix

Location IT (1-5) Staff (1-5) Volume (1-5) Tech Stack (1-5) Champion (1-5) Composite Tier
Location A 5 4 3 5 5 4.35 Tier 1
Location B 4 4 4 4 4 4.00 Tier 1
Location C 3 3 5 4 3 3.55 Tier 2
Location D 4 2 3 3 2 2.90 Tier 3
Location E 2 2 2 2 2 2.00 Tier 4

Rollout Sequence Recommendation

Wave 1 Selection Criteria (2–3 Locations)

☐ Composite score ≥4.0 ☐ Geographic proximity for efficient on-site support ⚠️ ☐ Representative of broader portfolio (mix of provider types, patient demographics) ☐ NOT your highest-revenue locations (limit downside risk) ☐ NOT locations with major competing initiatives (renovations, provider transitions)

Wave 2 Selection (Next 5–8 Locations)

☐ Composite score 3.5–4.5 ☐ Address geographic coverage (reduce travel burden for rollout team) ☐ Include at least one higher-volume location to stress-test workflows ☐ Include at least one specialty-focused location if applicable

Wave 3+ Selection (Remaining Locations)

☐ All Tier 2 and remediated Tier 3 locations ☐ Sequence by regional cluster for support efficiency ☐ Save Tier 4 locations for final waves after full remediation

Estimated time: 8–10 hours total for full portfolio assessment

4. Rollout Strategy

Wave Structure

Wave Locations Timeline Purpose
Wave 1 (Pilot) 2–3 locations Weeks 4–6 Validate workflows, identify issues, build internal expertise
Buffer/Learning — Weeks 7–10 Document learnings, refine training, adjust configuration
Wave 2 (Expansion) 5–8 locations Weeks 11–16 Scale deployment model, stress-test support structure
Buffer/Optimization — Weeks 17–18 Process refinements, prepare for final push
Wave 3 (Completion) Remaining 14–18 locations Weeks 19–24 Full portfolio deployment

Wave 1 Pilot Location Selection Criteria 🟣

Select locations that maximize learning while minimizing risk:

☐ High Readiness (Tier 1): Composite score ≥4.0 ensures smooth deployment ☐ Engaged Local Champion: Tech-forward provider actively supportive ☐ Manageable Volume: Medium patient volume (100–150/week) limits exposure ☐ Geographic Accessibility: Within 2-hour travel for on-site support ☐ Operational Stability: No major staff changes, renovations, or competing projects ☐ Representative Portfolio Mix: Include at least one GP-focused and one specialty-influenced location ☐ NOT Flagship Locations: Protect highest-revenue sites from pilot issues

Timeline Per Wave

Wave 1 Detail (Weeks 4–6)

Week Activities Deliverables
Week 4 Configuration, integration, test environment validation Locations technically ready
Week 5 Staff training, parallel workflows, soft launch Teams trained, running alongside legacy
Week 6 Go-live, daily monitoring, issue resolution Full production operation

Wave 2+ Detail (5–8 Locations Per Wave)

Week Activities Deliverables
Week 1 of Wave Technical prep for all wave locations simultaneously All locations technically ready
Week 2 of Wave Champion training, train-the-trainer deployment Champions certified
Week 3 of Wave Staff training, soft launch (staggered by 1–2 days) Teams trained
Week 4 of Wave Go-live (staggered by 1–2 days), stabilization All wave locations live
Weeks 5–6 of Wave Monitoring, optimization, learning documentation Wave complete, ready for next

Go/No-Go Criteria 🟣

Criteria to Advance from Wave 1 to Wave 2

Criterion Threshold Measurement
Technical Stability <5 critical issues in final week Issue tracking log
User Adoption >80% of providers using AI consistently Usage analytics
Workflow Integration <10% increase in patient cycle time Time study comparison
Staff Satisfaction Average ≥3.5/5 on pulse survey Post-go-live survey
Patient Impact No patient complaints attributable to AI Complaint tracking
Support Capacity Vendor + internal support adequately handled volume Support ticket review

Go Decision: All criteria met, or mitigation plan approved for any gaps No-Go Decision: Any criterion critically failed with no viable mitigation

Rollback Plan ⚠️

If a Wave Fails:

Immediate Actions (Within 24 Hours) ☐ Halt deployment of any remaining locations in current wave ☐ Notify all stakeholders per communication plan ☐ Convene emergency steering committee 🟣 ☐ Document failure mode in detail

Affected Location Options ☐ Pause: Disable AI features, continue with legacy workflow, schedule remediation ☐ Revert: Full removal of AI components, return to pre-deployment state ☐ Isolate: Continue in limited capacity with enhanced monitoring

Unaffected Location Protection ☐ Previously deployed locations continue unchanged (unless systemic issue identified) ☐ Upcoming wave locations postponed until root cause addressed ☐ Timeline adjusted; communicate revised schedule to all stakeholders

Recovery Process ☐ Root cause analysis (involve vendor) 🔵 ☐ Remediation plan development and approval 🟣 ☐ Controlled re-deployment with additional monitoring ☐ Extended buffer period before resuming wave structure

5. Configuration & Integration (Weeks 2–3)

Practice Management System Integration

Dentrix Enterprise Integration

Step Action Owner Time Est.
1 Verify Dentrix version compatibility (G7.2+ recommended) IT 30 min
2 🔵 Request DEXIS-Dentrix integration module from Envista IT + Vendor 1 day
3 Install integration module on Dentrix server IT 2 hours
4 ⚠️ Configure patient linking: Match patient IDs between systems IT 2 hours
5 Enable bidirectional image transfer IT 1 hour
6 Configure AI findings export to clinical notes IT + Clinical 2 hours
7 Test patient lookup, image transfer, findings documentation IT 2 hours
8 Validate across 10 sample patients IT + Provider 1 hour

Total estimated time: 1–2 days per location

Eaglesoft Integration

Step Action Owner Time Est.
1 Verify Eaglesoft version (21.0+ recommended) IT 30 min
2 🔵 Obtain Patterson-approved DEXIS connector IT + Vendor 1 day
3 Install connector on server and workstations IT 3 hours
4 ⚠️ Configure image file path mapping IT 1 hour
5 Enable treatment plan integration (if applicable) IT + Clinical 2 hours
6 Test end-to-end workflow IT + Provider 2 hours

Total estimated time: 1–2 days per location

Open Dental Integration

Step Action Owner Time Est.
1 Verify Open Dental version (current stable release) IT 30 min
2 Enable Open Dental bridge for DEXIS IT 1 hour
3 ⚠️ Configure image module integration (Open Dental imaging vs. external) IT 2 hours
4 🔵 Implement API-based data exchange if required IT + Vendor 4 hours
5 Test bidirectional workflow IT + Provider 2 hours

Total estimated time: 1 day per location

Imaging System Integration

DEXIS Sensor Integration (Native)

Step Action Owner Time Est.
1 Update DEXIS Imaging Suite to current version IT 1 hour
2 🔵 Activate AI module license key IT + Vendor 30 min
3 Configure AI analysis preferences (sensitivity, pathology types) Clinical + IT 1 hour
4 Validate sensor connectivity with AI analysis IT 30 min
5 Test overlay display and confidence score presentation Provider 30 min

Third-Party Sensor Migration (If Applicable) ⚠️

Step Action Owner Time Est.
1 Assess current sensor brand and compatibility IT + Vendor 1 hour
2 🔵 Obtain compatibility certification from Envista Vendor 1–5 days
3 If incompatible: Budget and schedule sensor upgrade 🟣 Finance + IT Variable
4 Install DEXIS integration layer for compatible sensors IT 2 hours
5 Validate image quality and AI analysis with non-native sensors IT + Provider 1 hour

Test Environment Setup

☐ 🔵 Request dedicated test tenant from Envista with DSO-wide access ☐ Configure test tenant to mirror production settings ☐ Populate with anonymized sample images from multiple locations ☐ Grant access to IT, clinical leadership, and designated testers ☐ Establish test data refresh cadence (weekly recommended)

Validation Checklist (Per Location)

Test Pass Criteria Tested By Date
Patient data sync: PMS ↔ DEXIS Patient record appears in both systems within 30 seconds IT
Image capture: AI analysis trigger AI overlay appears within 5 seconds of image capture Provider
AI findings: Accuracy spot-check AI findings align with provider assessment on 5 sample images Provider
AI findings: Documentation export Findings appear in PMS clinical notes accurately IT + Provider
Reporting: Usage metrics capture Dashboard reflects test activity IT
Performance: System response time No degradation vs. pre-AI baseline IT

Data Migration / Historical Image Ingestion

Scope Decision 🟣

Option Pros Cons Recommendation
No historical import Fastest deployment, lowest risk AI only analyzes new images Recommended for initial deployment
Recent history (90 days) Catch recent pathology, manageable volume Requires batch processing time Consider for Wave 2+
Full history Complete patient picture Large volume, time-consuming, potential data quality issues Rarely justified; defer to optimization phase

Historical Import Process (If Elected)

☐ 🔵 Coordinate batch import timeline with Envista ☐ Export images in DICOM format from existing archive ☐ ⚠️ Validate patient ID mapping between systems before import ☐ Schedule import during off-hours to minimize performance impact ☐ Monitor import progress; validate sample of imported images ☐ Document any import failures for manual remediation

Security and HIPAA Compliance

Enterprise-Level HIPAA Checklist 🟣

Requirement Status Owner Evidence
☐ BAA executed with Envista Legal Signed BAA document
☐ Envista SOC 2 Type II report reviewed IT Security Audit report on file
☐ Data encryption in transit (TLS 1.2+) IT Configuration verification
☐ Data encryption at rest (AES-256) IT/Vendor Vendor attestation
☐ Access controls configured per role IT RBAC documentation
☐ Audit logging enabled IT Log sample review
☐ Data residency confirmed (US-only if required) IT/Vendor Vendor attestation
☐ Incident response plan updated to include AI system IT Security Updated IRP document
☐ Patient consent reviewed (if applicable) Compliance/Legal Consent form review
☐ Provider training on AI disclosure (if required by state) Compliance Training completion records

Standardized vs. Location-Specific Configuration 🟣

Standardize Centrally

Setting Recommended Standard Rationale
AI sensitivity level "Balanced" (default) Consistency in diagnostic presentation
Pathology categories enabled All standard categories Complete diagnostic picture
Overlay display format Color-coded highlighting Uniform patient communication
Documentation template Standard AI findings format Consistent clinical notes
User permission levels Enterprise RBAC Security consistency

Allow Local Discretion

Setting Permitted Variation Approval Required
Confidence score display Show/hide based on provider preference Office manager
AI assistant audio cues Enable/disable Office manager
Secondary review workflow Optional peer review trigger Regional manager
Patient-facing display Show/hide AI overlay during case presentation Provider

6. Team Training Plan

Train-the-Trainer Model

Champion Selection Criteria

☐ Role: Provider (preferred) or Office Manager with strong clinical credibility ☐ Tech Comfort: History of successful technology adoption ☐ Influence: Respected by peers; opinion shapes team behavior ☐ Availability: Willing to commit 4–6 hours to certification and ongoing support ☐ Communication: Can explain technical concepts simply ☐ Attitude: Genuinely supportive of AI adoption (not grudging compliance)

Champion Responsibilities

Responsibility Time Commitment Frequency
Complete certification training 4 hours One-time
Deliver role-specific training to location staff 4–6 hours Pre-go-live
Provide day-one support Full day Go-live
Conduct daily check-ins with central team 15 min First 2 weeks
Collect and escalate staff feedback 30 min Weekly ongoing
Train new hires 1 hour As needed
Lead quarterly refresher sessions 30 min Quarterly

Champion Certification Process 🔵

Step Method Duration Deliverable
1 Complete Envista online learning modules 2 hours Module completion certificate
2 Attend live train-the-trainer session (virtual or in-person) 2 hours Session attendance
3 Pass competency assessment (80% threshold) 30 min Assessment score
4 Deliver practice training session (observed) 30 min Sign-off from clinical leader
5 Receive champion toolkit and materials — Materials in hand

Role-Specific Training Outlines

Dentists/Providers

Training Duration: 90 minutes Format: Live demo (45 min) + hands-on practice (30 min) + Q&A (15 min) Delivered By: Location champion + Envista clinical specialist (Wave 1 only) 🔵

Content Modules:

  1. Understanding AI Diagnostic Assistance (15 min)

    • What the AI does and doesn't do
    • Confidence scores explained
    • AI as assistant, not replacement for clinical judgment
    • Liability and documentation implications

  2. Workflow Integration (20 min)

    • Where AI appears in the imaging workflow
    • How to access AI findings
    • How to accept, modify, or dismiss AI suggestions
    • Documenting clinical decision when differing from AI

  3. Clinical Interpretation (30 min)

    • Reading AI overlays and pathology indicators
    • Understanding sensitivity/specificity tradeoffs
    • When AI typically excels vs. requires more scrutiny
    • Case studies: AI-assisted diagnosis examples

  4. Patient Communication (15 min)

    • How to explain AI to patients
    • Using AI visuals in case presentation
    • Addressing patient questions/concerns about AI

  5. Hands-On Practice (30 min)

    • Process 5 sample cases with AI assistance
    • Practice workflow from image capture to documentation
    • Practice patient communication script

Common Resistance Points & Responses:

Resistance Response
"I don't need AI to read X-rays" "This is a second set of eyes to catch what any human might miss on a busy day. It supports your expertise, not replaces it."
"What if the AI is wrong?" "You remain the diagnostician. The AI is a tool—you can and should override when your clinical judgment differs."
"This will slow me down" "Initial learning curve is 1–2 weeks. After that, most providers report faster, more confident diagnoses."
"My patients won't trust a computer" "Patients respond well to visual proof. The AI visuals actually increase case acceptance in most practices."

Day 1 Cheat Sheet for Providers: (Single page, tape to monitor)

┌────────────────────────────────────────────────────┐
│           DEXIS AI QUICK REFERENCE                 │
├────────────────────────────────────────────────────┤
│ 1. CAPTURE: Image as normal—AI runs automatically │
│                                                    │
│ 2. REVIEW: Look for colored overlays               │
│    🔴 Red = High confidence finding                │
│    🟡 Yellow = Moderate confidence                 │
│    🔵 Blue = Low confidence/suggested review       │
│                                                    │
│ 3. INTERPRET: Click any finding for details        │
│    - Pathology type                                │
│    - Confidence %                                  │
│    - Reference points                              │
│                                                    │
│ 4. DECIDE: Accept, modify, or dismiss              │
│    YOUR clinical judgment is final                 │
│                                                    │
│ 5. DOCUMENT: Click "Export to Notes"               │
│    Findings auto-populate in PMS                   │
│    Add your clinical commentary                    │
│                                                    │
│ 6. PRESENT: Use AI visuals with patient            │
│    "I'm using advanced imaging technology that     │
│     helps identify areas of concern..."            │
│                                                    │
│ ⚠️ ISSUE? Contact: [Champion name] or ext. [XXX]   │
└────────────────────────────────────────────────────┘

Hygienists

Training Duration: 45 minutes Format: Live demo (20 min) + hands-on practice (15 min) + Q&A (10 min) Delivered By: Location champion

Content Modules:

  1. Role in AI Workflow (10 min)

    • How AI analyzes images taken during prophylaxis
    • What hygienists will see on screen
    • Calculus detection feature specific to hygiene

  2. Using AI for Patient Education (15 min)

    • Showing AI findings to patients during cleaning
    • Supporting provider case presentations
    • Reinforcing treatment recommendations

  3. Escalation Workflow (10 min)

    • When to flag AI findings for provider review
    • How to document hygiene-observed findings

  4. Hands-On Practice (15 min)

    • Process 3 sample hygiene cases
    • Practice patient education dialogue

Common Resistance Points & Responses:

Resistance Response
"This isn't part of my job" "AI enhances your ability to educate patients and support comprehensive care. It's not additional work—it's better tools for what you already do."
"I can see calculus without AI" "Of course. AI helps visualize it for patients and ensures nothing is missed subgingivally."

Day 1 Cheat Sheet for Hygienists:

┌────────────────────────────────────────────────────┐
│        DEXIS AI FOR HYGIENE - QUICK REFERENCE      │
├────────────────────────────────────────────────────┤
│ WHAT YOU'LL SEE:                                   │
│ - AI overlays appear after imaging                 │
│ - Calculus deposits highlighted in [green]        │
│ - Other findings highlighted for provider          │
│                                                    │
│ YOUR ROLE:                                         │
│ ☐ Note AI findings visible during prophy          │
│ ☐ Show findings to patient: "You can see here..." │
│ ☐ Flag concerns for doctor review                  │
│                                                    │
│ DO NOT: Make diagnostic statements to patients     │
│ ("You have decay" — leave that to provider)        │
│                                                    │
│ ⚠️ ISSUE? Contact: [Champion name] or ext. [XXX]   │
└────────────────────────────────────────────────────┘

Front Desk / Office Manager

Training Duration: 30 minutes Format: Live demo (15 min) + system walkthrough (10 min) + Q&A (5 min) Delivered By: Location champion

Content Modules:

  1. Patient Communication (10 min)

    • Answering patient questions about AI
    • Explaining AI benefits in simple terms
    • Sample scripts for phone and in-person inquiries

  2. Scheduling Considerations (5 min)

    • Any appointment length adjustments during rollout
    • Flagging patients for AI-assisted exams (if applicable)

  3. Administrative Functions (10 min)

    • Accessing usage reports
    • Basic troubleshooting (restart workflow)
    • When to contact champion vs. escalate

  4. Reporting Basics (5 min)

    • Locating AI activity dashboards
    • Metrics to monitor weekly

Day 1 Cheat Sheet for Front Desk:

┌────────────────────────────────────────────────────┐
│       DEXIS AI FOR FRONT DESK - QUICK REFERENCE    │
├────────────────────────────────────────────────────┤
│ PATIENT QUESTIONS:                                 │
│                                                    │
│ Q: "What is this AI thing?"                        │
│ A: "We've added advanced imaging technology that   │
│     helps Dr. [Name] identify dental issues more   │
│     accurately. It's another tool to give you the  │
│     best possible care."                           │
│                                                    │
│ Q: "Is a computer diagnosing me?"                  │
│ A: "No—Dr. [Name] makes all diagnoses. The AI     │
│     is a helper that highlights areas to review.   │
│     Your dentist is always in charge."             │
│                                                    │
│ Q: "Is this safe?"                                 │
│ A: "Absolutely. It analyzes the same X-rays we've │
│     always taken. No additional radiation."        │
│                                                    │
│ ⚠️ ISSUE? Contact: [Champion name] or ext. [XXX]   │
└────────────────────────────────────────────────────┘

Billing/Insurance Staff

Training Duration: 30 minutes Format: Live demo (15 min) + coding review (10 min) + Q&A (5 min) Delivered By: Location champion + RCM representative

Content Modules:

  1. Documentation Changes (10 min)

    • How AI findings appear in clinical notes
    • Enhanced documentation detail for claims support
    • Narrative export features

  2. Coding Considerations (15 min)

    • No new codes required for AI-assisted diagnosis
    • AI documentation supports medical necessity
    • Strategies for using AI visuals in appeals

  3. Claim Impact Monitoring (5 min)

    • Metrics to track (denial rates, resubmission rates)
    • Reporting to central RCM team

Day 1 Cheat Sheet for Billing:

┌────────────────────────────────────────────────────┐
│        DEXIS AI FOR BILLING - QUICK REFERENCE      │
├────────────────────────────────────────────────────┤
│ WHAT CHANGES:                                      │
│ - Clinical notes may include AI-assisted findings  │
│ - Diagnoses are MORE thoroughly documented         │
│ - This SUPPORTS claims, not complicates them       │
│                                                    │
│ CODING:                                            │
│ - No new CDT codes for AI                         │
│ - Standard diagnostic codes apply                  │
│ - AI doesn't change what you bill                 │
│                                                    │
│ APPEALS:                                           │
│ - AI images can be included in appeal packets      │
│ - Contact [Champion] for image exports             │
│                                                    │
│ MONITOR:                                           │
│ - Track D0120-D0999 denial rates monthly          │
│ - Report changes to [RCM contact]                  │
│                                                    │
│ ⚠️ ISSUE? Contact: [Champion name] or ext. [XXX]   │
└────────────────────────────────────────────────────┘

Training Completion Tracking

Pre-Go-Live Training Gate ⚠️

No location goes live until training completion verified:

Role Training Required Completion Verification
Champion Certification complete Certificate on file
All providers Role training complete Signed attestation
All hygienists Role training complete Signed attestation
Front desk staff Role training complete Signed attestation
Billing staff Role training complete Signed attestation

Tracking Mechanism

☐ Create centralized training completion spreadsheet (or LMS if available) ☐ Champion reports completions daily during training week ☐ Regional manager validates completion before go-live sign-off ☐ Training records retained for compliance purposes

Ongoing Training Cadence

Training Type Frequency Audience Duration
New hire onboarding As needed New staff 30–90 min (by role)
Quarterly refresher Quarterly All clinical staff 15 min
Feature updates As released Champions → cascade 15–30 min
Annual certification Annually Champions 1 hour

7. Change Management

Executive Sponsor Communication Plan

Board/Investor Updates 🟣

Touchpoint Frequency Content Owner
Pre-launch briefing Once (Week 1) Investment rationale, expected ROI, timeline CEO/CFO
Quarterly update Quarterly Deployment progress, early metrics, risk status CEO
Investment committee As scheduled AI as strategic capability, portfolio value impact CEO/CFO
Exit/M&A materials As needed AI adoption as technology maturity indicator CFO

Board-Ready Talking Points:

  • "We are deploying AI-assisted diagnostic imaging to standardize clinical quality across [X] locations"
  • "This investment reduces diagnostic variability, supports case acceptance, and positions us as a technology-forward operator"
  • "Expected full deployment by [date] with measurable ROI within 6 months"

C-Suite Communication

Touchpoint Frequency Content Attendees
Steering committee Bi-weekly Deployment status, decisions needed, risk escalation CEO, CDO, CFO, VP Ops
CDO clinical review Weekly Clinical adoption, provider feedback, workflow issues CDO, clinical leads
CFO financial review Monthly Budget tracking, ROI progress, investment performance CFO, VP Ops

Regional Manager Briefing Guide

Purpose: Equip regional managers to cascade rollout information effectively

Briefing Deck Structure (30 Minutes)

  1. What We're Doing and Why (5 min)

    • DEXIS AI overview—one paragraph
    • DSO strategic rationale
    • Expected benefits for their region

  2. Their Role in Rollout (10 min)

    • Location readiness assessment support
    • Champion identification and support
    • Go-live attendance (if required)
    • Weekly check-in facilitation

  3. Timeline and Their Locations (5 min)

    • Wave assignments for their locations
    • Key dates and milestones
    • Buffer periods and flexibility

  4. What to Tell Office Managers (5 min)

    • Key messages to cascade
    • Common questions to anticipate
    • How to handle staff concerns

  5. Escalation and Support (5 min)

    • When to escalate to central team
    • Who to contact for what
    • Regular check-in schedule with central team

Regional Manager Toolkit

☐ One-page initiative summary for office managers ☐ FAQ document for staff questions ☐ Location assessment template (if not completed centrally) ☐ Champion nomination form ☐ Weekly status report template

Staff Resistance Framework for Multi-Location Dynamics

Common Resistance Patterns at Scale

Pattern Manifestation Mitigation
"Other locations are doing fine without this" Staff compare to non-deployed locations Deploy in waves to minimize this window; emphasize portfolio-wide commitment
"Corporate is forcing this on us" Perception of top-down mandate Involve local champions; frame as clinical improvement, not mandate
"We're guinea pigs" Wave 1 locations feel tested Position as trusted partners; offer extra support
"Why are we last?" Wave 3 locations feel neglected Communicate that later waves benefit from earlier learnings; thank them for patience
Cross-location grumbling Staff at different locations share frustrations Monitor, address quickly; share success stories broadly

Resistance Response Protocol

  1. Local champion addresses first: Peer-to-peer credibility
  2. Office manager reinforces: Management support
  3. Regional manager intervenes if needed: Authority and broader context
  4. Central team escalates if systemic: Policy or training adjustments

Internal Marketing

Initiative Naming 🟣

Recommended: Give the rollout a memorable internal name that conveys positivity

Examples:

  • "Project ClearView" (emphasizes diagnostic clarity)
  • "AI Advantage Initiative"
  • "SmartScan Rollout"

Avoid: Generic names like "DEXIS Implementation" or names that emphasize change/disruption

Momentum-Building Tactics

Tactic Timing Owner
CEO/CDO video announcement Week 1 CEO/CDO
"Meet the AI" preview session (all-hands or regional) Week 2 Clinical leader
Champion spotlight emails Ongoing Internal comms
Wave 1 success stories Post-Wave 1 Marketing/Comms
"First 100 AI-assisted diagnoses" celebration Post-Wave 1 Regional managers
Monthly leaderboard (optional—use carefully) Monthly VP Ops
Full deployment celebration Final wave CEO

Celebrating Milestones

☐ Wave 1 go-live: Recognize pilot locations and champions ☐ 50% deployment: All-hands update, share early results ☐ Full deployment: Company-wide announcement, champion recognition ☐ ROI milestone: Quantified results communication

8. Go-Live Day Runbook

Standardized Go-Live Checklist (Every Location)

Pre-Go-Live (Day Before)

Time Task Owner Status
T-24h Confirm all training complete (attestations collected) Champion ☐
T-24h Verify system configuration matches standard template IT ☐
T-24h Confirm PMS integration validated IT ☐
T-24h Verify imaging system connectivity IT ☐
T-24h Test AI analysis on 3 sample images Provider ☐
T-24h Print and distribute Day 1 cheat sheets Champion ☐
T-24h Brief all staff on go-live plan Champion ☐
T-24h Confirm vendor support contact and availability IT ☐
T-24h 🔵 Notify Envista of go-live (if heightened support requested) IT ☐

Go-Live Day: Hour-by-Hour Schedule

Time Activity Owner Support
7:00 AM Champion arrives, system check Champion IT (remote)
7:15 AM Final huddle with clinical team (10 min) Champion
7:30 AM First patient with AI-assisted imaging Provider Champion observes
8:00 AM Check-in: First patient processed, any issues? Champion Regional (remote)
9:00 AM Check-in: First 2–3 patients processed Champion Regional (remote)
10:00 AM Morning progress report to central team Champion
12:00 PM Midday huddle: Issues, questions, adjustments Champion Provider
2:00 PM Afternoon check-in Champion Regional (remote)
4:00 PM End of day debrief Champion Provider
4:30 PM Day 1 report submitted to central team Champion

Who Needs to Be Available

Role Requirement Contact Method
Location Champion On-site all day In-person
Regional Manager On-call; on-site for Wave 1 only Phone/video
Central IT On-call all day Slack/Teams + phone
Central Operations On-call all day Phone/video
🔵 Envista Support On-call; elevated support for Wave 1 Support hotline

Known Gotchas and First-Day Troubleshooting ⚠️

Issue Likely Cause Fix Time to Fix
AI analysis not triggering DEXIS service not running Restart DEXIS application; verify service status 5 min
Analysis extremely slow Network bandwidth issue Check network speed; prioritize imaging traffic 15–30 min
Overlay not displaying Display settings incorrect Adjust view settings; check monitor resolution 5 min
Findings not exporting to PMS Integration configuration Verify API connection; re-authenticate 15 min
"License not found" error Licensing not activated Contact Envista support 🔵 15–60 min
Inconsistent patient matching Patient ID mismatch Manual patient link; escalate for permanent fix 5 min per patient
Provider override not saving Documentation setting Adjust note export settings 10 min
Staff forgot workflow Normal learning curve Reference cheat sheet; champion provides guidance 2 min

Escalation Tiers

Tier Who When to Engage Expected Response
Tier 1 Location Champion Any question or minor issue Immediate
Tier 2 Regional Manager Issue not resolved in 15 min; staff escalation Within 15 min
Tier 3 Central IT Technical issue not resolved at Tier 2 Within 30 min
Tier 4 🔵 Envista Support System-level issue; central IT cannot resolve Per SLA (target: 1 hour)

Patient Communication Script

For Patient-Facing AI Visuals

Introducing AI to Patients (Provider Script):

"Today I'm using some advanced imaging technology that helps me identify potential areas of concern in your X-rays. You might notice colored highlights on the images—those are areas the system has flagged for me to review closely. I want to be clear: I'm the one making all the diagnostic decisions, but this technology helps ensure I don't miss anything. Do you have any questions about that?"

If Patient Asks Questions:

Patient Question Recommended Response
"Is a robot diagnosing me?" "Not at all—I'm making all the diagnoses. This is a tool that helps me catch things that might be easy to miss. Think of it like spell-check for X-rays."
"Is this safe?" "Absolutely. It analyzes the same X-rays we've always taken. There's no additional radiation or procedures."
"How accurate is it?" "It's very good at highlighting areas that need attention, but I always apply my clinical judgment. It's one of many tools I use."
"Do I have a choice?" "The AI is simply analyzing images we're already taking. If you'd prefer not to see the AI overlay, I can discuss your X-rays without it."

First-Week Daily Check-In Protocol

Location Champion → Central Team

Daily Report (Submit by 5 PM local time)

Question Response
Patients imaged with AI today: [Number]
Issues encountered: [List or "None"]
Issues resolved: [List]
Issues escalated: [List]
Staff feedback themes: [Summary]
Provider feedback themes: [Summary]
Patient feedback: [Summary]
Confidence level (1–10): [Score]
Support needed tomorrow: [Specific requests]

Central Team → Champion

Daily Check-In Call (15 min, scheduled time)

  • Review submitted report
  • Address outstanding issues
  • Provide encouragement and guidance
  • Update on any system-wide learnings
  • Confirm next day's plan

9. Post-Launch Optimization (Weeks 4–8)

Weekly Metrics Review Cadence

Metrics to Track (Per Location)

Metric Source Target Red Flag
AI utilization rate DEXIS dashboard >90% of exams <70%
Provider adoption rate DEXIS dashboard 100% of providers using Any provider at 0%
Average analysis time DEXIS dashboard <5 seconds >15 seconds
System uptime IT monitoring >99% <95%
Support tickets Helpdesk Decreasing trend Increasing after Week 2
Case acceptance rate PMS Improving vs. baseline Declining vs. baseline
Patient complaints Complaint log Zero AI-related Any AI-related complaints

Weekly Review Meeting (30 Minutes)

Attendees: Central operations lead, clinical lead, IT lead Frequency: Weekly (Weeks 1–8); bi-weekly thereafter

Agenda:

  1. Metrics review: Red/yellow/green by location (5 min)
  2. Issue triage: Outstanding issues and resolution status (10 min)
  3. Feedback synthesis: Themes from champions (5 min)
  4. Process adjustments: Any workflow refinements (5 min)
  5. Next week focus: Priorities and action items (5 min)

30-Day Checkpoint

What "Good" Looks Like

Indicator Target at 30 Days
AI utilization >95% of eligible exams
Provider adoption 100% of providers actively using
Support tickets <5 open tickets across all deployed locations
Staff satisfaction Average ≥3.5/5 on pulse survey
Workflow integration No significant patient flow delays
Case acceptance Stable or improving vs. baseline
Patient feedback Net positive; no recurring complaints

Red Flags at 30 Days ⚠️

Red Flag Action Required
Utilization <70% Champion intervention; identify barriers
Any provider not using Direct outreach from CDO
Open tickets increasing Root cause analysis; additional training
Staff satisfaction <3/5 Focus groups; specific concern addressing
Case acceptance declining Clinical workflow review; provider coaching
Patient complaints Immediate review; communication adjustments

60-Day Checkpoint

ROI Assessment Framework

Compare to Baseline Metrics Captured Pre-Launch

Metric Baseline 60-Day Delta ROI Implication
Case acceptance rate [%] [%] [+/- %] Revenue impact
Radiographic findings per patient [#] [#] [+/- #] Diagnostic thoroughness
Time to treatment presentation [min] [min] [+/- min] Efficiency impact
Diagnostic re-treatment rate [%] [%] [+/- %] Quality impact
Claim denial rate (dx codes) [%] [%] [+/- %] Revenue cycle impact
Provider interpretation time [min] [min] [+/- min] Provider efficiency

ROI Calculation Framework

Monthly Revenue Impact = 
  (Case Acceptance Improvement % × Average Case Value × Monthly Patient Volume)
  + (Denied Claims Reduction × Average Claim Value)
  - (Additional Operating Costs, if any)

Annual ROI = (12 × Monthly Revenue Impact) / Total Implementation Investment

Staff Feedback Collection

5-Question Pulse Survey (Monthly)

Deploy to all staff at deployed locations

  1. How confident do you feel using DEXIS AI in your daily work? (1 = Not confident → 5 = Very confident)

  2. How has DEXIS AI impacted your workflow? (1 = Made it worse → 5 = Improved significantly)

  3. How well does DEXIS AI integrate with your other systems? (1 = Poorly → 5 = Seamlessly)

  4. How likely are you to recommend DEXIS AI to a colleague? (1 = Not likely → 5 = Highly likely)

  5. What one thing would most improve your experience with DEXIS AI? (Open text)

Survey Administration

  • Deploy via email on the first Monday of each month
  • Close survey after 5 business days
  • Analyze results and share summary with regional managers within 1 week
  • Track trends over time; investigate any location with declining scores

Workflow Refinements: Common Post-Launch Adjustments

Adjustment When to Consider Implementation
Adjust AI sensitivity Providers report excessive false positives/negatives Configuration change (test before production)
Modify overlay display Providers want more/less visual detail Per-provider customization (within permitted range)
Streamline documentation Export to notes is clunky Template adjustment; work with vendor 🔵
Add peer review workflow CDO wants quality oversight Configure secondary review trigger
Adjust patient communication Patients confused by AI mention Update scripts; additional staff training
Reallocate champion time Champion overloaded with support requests Add secondary champion or reduce other duties

Centralized Dashboard Structure

Location-Level Dashboard (Accessible to Champions, Office Managers, Regional Managers)

Metric Display Update Frequency
AI utilization rate Percentage, trend chart Real-time
Exams analyzed today Count Real-time
Average analysis time Seconds Daily
Open support tickets Count, list Real-time
Training completion Percentage Real-time
Staff survey average Score Monthly

Portfolio-Level Dashboard (Accessible to C-Suite, VP Ops)

Metric Display Update Frequency
Deployment progress Locations live / Total locations Real-time
Portfolio utilization rate Percentage, by-location breakdown Daily
Portfolio case acceptance delta Percentage change vs. baseline Weekly
Open tickets (all locations) Count, by severity Real-time
Red/yellow/green status Heatmap Weekly
ROI tracking Dollar estimate Monthly

Quarterly Business Review Framework

QBR Agenda (90 Minutes)

Attendees: C-suite, regional managers, clinical leadership, IT

  1. Executive Summary (10 min)

    • Deployment status: Locations live, wave progress
    • Key wins and challenges
    • ROI snapshot

  2. Performance Review (20 min)

    • Portfolio-wide metrics vs. targets
    • Location-level performance: Top performers and laggards
    • Trend analysis: Improving, stable, declining

  3. Clinical Impact Assessment (15 min)

    • CDO presentation: Clinical quality observations
    • Provider adoption and feedback themes
    • Patient impact summary

  4. Operational Review (15 min)

    • IT: System stability, integration performance
    • Operations: Workflow impact, efficiency gains/losses
    • Support: Ticket volume, common issues

  5. Financial Review (15 min)

    • Budget vs. actual: Implementation costs
    • ROI progress: Revenue impact tracking
    • Forecast: Expected full-year impact

  6. Roadmap and Optimization (10 min)

    • Upcoming enhancements from vendor 🔵
    • Planned process improvements
    • Next quarter priorities

  7. Decisions Needed (5 min) 🟣

    • Open items requiring executive decision
    • Resource requests

10. Centralized vs. Localized Decision Framework

Decision Area Standardize Centrally Allow Local Discretion Notes
AI sensitivity settings ✓ Consistency in diagnostic presentation
Pathology categories enabled ✓ Complete diagnostic picture portfolio-wide
Documentation template ✓ Consistent clinical notes and compliance
User permission levels/RBAC ✓ Security consistency
Training content ✓ Quality assurance
Reporting structure ✓ Comparable metrics across locations
Confidence score display ✓ Provider preference
Audio/visual cues ✓ Workflow preference
Patient-facing overlay display ✓ Provider judgment
Secondary review triggers ✓ Regional/specialty variation
Champion selection ✓ Local knowledge required
Training scheduling ✓ Local logistics
Go-live day of week ✓ Patient volume management

11. Risk Register

Risk Likelihood (1-5) Impact (1-5) Risk Score Mitigation Strategy Owner
⚠️ Provider resistance stalls adoption 3 4 12 Champion-led training; CDO engagement; address concerns directly CDO
Network issues disrupt AI analysis 2 4 8 Pre-deployment network assessment; bandwidth upgrades; offline fallback workflow IT
Integration failures delay go-live 3 3 9 Thorough test environment validation; buffer time in schedule; vendor escalation path IT
Patient pushback on AI 2 3 6 Staff communication training; patient-friendly scripts; transparency Champions
Champion turnover mid-rollout 2 4 8 Identify backup champions; champion succession plan Regional Manager
Vendor support capacity exceeded 2 3 6 Establish dedicated enterprise support contact; SLA enforcement VP Ops
⚠️ Wave 1 failure delays entire rollout 2 5 10 Thorough pilot selection; extended stabilization period; clear rollback plan VP Ops
Budget overrun from unexpected costs 2 3 6 Contingency budget (10%);

AI-generated implementation guide based on public vendor information. Verify specifics directly with DEXIS / Envista.