CranioCatch
Step-by-step implementation guide — pre-implementation checklist, onboarding, staff training, go-live runbook, and ROI tracking.
CranioCatch — Implementation Playbook (DSO)
CranioCatch Implementation Playbook
AI-Powered Diagnostic Imaging for Dental Service Organizations
Prepared for DSO Operations Leadership Tool Category: Diagnostic Imaging AI Version 1.0
1. Executive Summary
What CranioCatch Does
CranioCatch is an AI-powered diagnostic imaging platform that automatically analyzes dental radiographs (panoramic, periapical, bitewing, and CBCT images) to detect pathologies, anatomical structures, and treatment needs with FDA-cleared accuracy. The system integrates with existing imaging workflows to provide real-time annotations, numbered tooth detection, and pathology identification—reducing diagnostic variability and supporting clinical decision-making at the point of care.
Why DSOs Specifically Benefit from Diagnostic Imaging AI
Scale Advantages:
- Standardized diagnostic protocols across 15–50+ locations eliminate provider-dependent variability in radiograph interpretation
- Centralized quality assurance enables comparison of diagnostic patterns across regions, identifying outliers and training opportunities
- Bulk licensing and enterprise agreements typically reduce per-location costs by 25–40% compared to individual practice deployments
Operational Standardization:
- Uniform AI-assisted findings documentation strengthens medical-legal positioning across the enterprise
- Consistent pathology detection supports standardized treatment planning protocols and case acceptance frameworks
- Reduced diagnostic time per patient (typically 2–4 minutes saved per radiograph review) compounds into significant chair time recovery at scale
Data Aggregation Value:
- Enterprise-wide diagnostic data creates insights unavailable to single practices: prevalence patterns, treatment outcome correlation, provider performance benchmarking
- Aggregated anonymized data positions the DSO for future value-based care contracts and population health initiatives
- Cross-location analytics enable evidence-based resource allocation and specialty referral optimization
Expected Timeline: Decision to Full Deployment
| Phase | Timeline | Scope |
|---|---|---|
| Pre-Implementation & Planning | Weeks 1–2 | Vendor contracts, technical assessment, baseline metrics |
| Wave 1 Pilot (2–3 locations) | Weeks 3–6 | Configuration, training, go-live, stabilization |
| Wave 2 Expansion (5–8 locations) | Weeks 7–12 | Scaled deployment with refined playbook |
| Wave 3 Full Rollout (remaining locations) | Weeks 13–20 | Enterprise-wide deployment |
| Optimization & Steady State | Weeks 21–24 | Performance tuning, ROI validation |
Total Timeline: 20–24 weeks for a 30-location DSO (adjust ±4 weeks based on location count and IT infrastructure variability)
2. Pre-Implementation Checklist (Weeks 1–2)
Technical Requirements
Hardware Requirements
☐ Workstation specifications per operatory/reading station:
- Minimum: Intel i5 (8th gen+) or AMD Ryzen 5, 16GB RAM, 256GB SSD
- Recommended: Intel i7/AMD Ryzen 7, 32GB RAM, 512GB SSD
- Display: Minimum 1920x1080 resolution; diagnostic-grade monitors recommended for primary reading stations
☐ Network infrastructure:
- Minimum 50 Mbps download/10 Mbps upload per location (100/20 Mbps recommended)
- Latency <100ms to CranioCatch cloud endpoints
- ⚠️ Locations with satellite internet or cellular failover may experience degraded performance
☐ Imaging sensor compatibility verification:
- Document all imaging hardware models at each location
- 🔵 Submit imaging system inventory to CranioCatch for compatibility confirmation
Software Requirements
☐ Operating system: Windows 10/11 Pro (64-bit) or macOS 12+ ☐ Browser: Chrome 90+ or Edge 90+ (Chrome recommended for optimal performance) ☐ Practice Management System: Current supported version (see Integration section) ☐ Imaging software: Compatible versions of imaging acquisition software
Enterprise-Level Requirements
☐ 🟣 Network standards decision: Confirm minimum bandwidth requirements will be added to DSO IT standards documentation
☐ 🟣 Hosting model decision:
| Model | Pros | Cons | Recommendation |
|---|---|---|---|
| Cloud-hosted (CranioCatch standard) | No local infrastructure, automatic updates, lower IT burden | Dependent on internet connectivity | Recommended for most DSOs |
| Hybrid (local cache + cloud) | Faster image processing, offline fallback | Higher complexity, additional hardware | Consider for rural/low-connectivity locations |
☐ Single Sign-On (SSO) configuration:
- 🔵 Provide Identity Provider (IdP) details to CranioCatch (Okta, Azure AD, Google Workspace)
- Estimated SSO setup time: 3–5 business days
- ⚠️ SSO delays are a common timeline risk—initiate early
☐ Centralized credentialing setup:
- Establish enterprise admin hierarchy: Super Admin → Regional Admin → Location Admin
- Define role-based access control (RBAC) matrix
- Document provider credentialing workflow for AI tool access
Vendor Onboarding Steps
| Step | Owner | Timeline | Deliverable |
|---|---|---|---|
| 🔵 Execute enterprise agreement | Legal/Procurement + CranioCatch | Days 1–5 | Signed MSA and BAA |
| 🔵 Assign dedicated Customer Success Manager | CranioCatch | Day 3 | Named CSM with contact info |
| 🔵 Schedule technical kickoff call | IT Director + CranioCatch | Day 5 | Integration requirements confirmed |
| 🔵 Receive enterprise admin credentials | CranioCatch | Day 7 | Admin portal access |
| 🔵 Complete security questionnaire | IT Security + CranioCatch | Days 5–10 | Approved security assessment |
Key Vendor Contacts to Establish
☐ Customer Success Manager (primary relationship owner) ☐ Technical Implementation Specialist (integration support) ☐ Enterprise Support Escalation (Tier 2+) ☐ Account Executive (contract/commercial issues) ☐ 🔵 Request 24/7 support contact for go-live periods
Data/Access Prerequisites
☐ Administrative access requirements:
- Practice Management System admin credentials (or IT admin availability during integration)
- Imaging software admin credentials
- Network firewall access to whitelist CranioCatch endpoints
☐ API and integration prerequisites:
- 🔵 Request API documentation from CranioCatch
- Generate/obtain API keys from PMS vendor if required
- Document imaging software integration method (TWAIN, DICOM, direct API)
☐ Imaging archive access:
- Confirm storage location of historical radiographs (local server vs. cloud)
- ⚠️ If historical analysis is desired, assess archive format compatibility
- Estimate volume of historical images for ingestion planning
☐ Firewall and security whitelist:
Required endpoints (confirm current list with CranioCatch):
- api.craniocatch.com (443)
- images.craniocatch.com (443)
- auth.craniocatch.com (443)
Internal Stakeholder Alignment
Stakeholder Alignment Map
| Stakeholder | Role in Implementation | Communication Need | Approval Required |
|---|---|---|---|
| 🟣 Board/Investors | Strategic oversight | Quarterly AI investment update | Budget approval |
| 🟣 CEO/COO | Executive sponsorship | Bi-weekly rollout status | Go/no-go decisions |
| 🟣 Chief Dental Officer | Clinical validation | Weekly clinical outcomes review | Clinical protocol approval |
| VP of Operations | Implementation ownership | Daily during rollout | Operational decisions |
| Regional Managers | Cascade execution | Weekly wave status | Location sequencing input |
| IT Director | Technical execution | Daily during integration | Technical architecture |
| Compliance/Legal | Risk management | As-needed | BAA, policy updates |
| Office Managers | Location execution | Pre-wave briefing, daily during go-live | Local scheduling |
| Lead Providers (per location) | Clinical adoption | Training, daily during first week | None (RACI: Informed) |
Communication Cadence (Pre-Implementation)
☐ 🟣 Executive briefing: Present business case and rollout plan for approval (Week 1, Day 2) ☐ 🟣 CDO alignment: Review clinical protocols and AI override guidelines (Week 1, Day 3) ☐ Regional manager briefing: Cascade rollout plan and location selection criteria (Week 1, Day 5) ☐ IT team kickoff: Detailed technical requirements and integration planning (Week 1, Day 3) ☐ Compliance review: HIPAA implications, BAA execution, policy updates (Week 1–2)
Baseline Metrics Capture
⚠️ Critical: Baseline metrics must be captured BEFORE any AI tool exposure to enable accurate ROI measurement.
Required Baseline Metrics
| Metric | Definition | Measurement Method | Capture Window |
|---|---|---|---|
| Case acceptance rate | % of diagnosed conditions accepted for treatment | PMS treatment acceptance reports | Last 90 days |
| Average diagnosis time | Time from image capture to diagnosis documentation | Time study (sample 50 cases/location) | 1-week study |
| Pathology detection rate | Conditions diagnosed per 100 radiographs | Chart audit (sample 100 radiographs/location) | Last 90 days |
| Claim denial rate (diagnostic) | % of diagnostic-related claims denied | Billing system reports | Last 90 days |
| Radiograph retake rate | % of radiographs requiring retake due to quality | Imaging system logs or manual audit | Last 90 days |
| Patient throughput | Patients seen per provider per day | Scheduling/PMS reports | Last 90 days |
| Provider diagnostic variability | Standard deviation in pathology detection across providers | Chart audit comparison | Last 90 days |
Standardization Requirements for Cross-Location Comparison
☐ Create standardized metric definitions document (ensure all locations measure identically) ☐ Designate single data extraction method per metric (avoid location-specific interpretation) ☐ Establish central data repository for baseline storage (Excel template or BI tool) ☐ Assign regional managers to validate data quality before submission ☐ ⚠️ Flag locations with incomplete historical data—may need extended baseline capture or exclusion from Wave 1
Baseline Data Collection Timeline
| Task | Owner | Days |
|---|---|---|
| Distribute metric collection template | VP Operations | Day 1 |
| Office managers extract PMS/billing data | Office Managers | Days 2–5 |
| Regional managers validate submissions | Regional Managers | Days 6–7 |
| IT compiles time study protocol | IT Director | Day 3 |
| Locations execute time study | Office Champions | Days 5–10 |
| Central team aggregates baselines | Analytics/Operations | Days 11–14 |
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 | Fiber internet (100+ Mbps), workstations <2 years old, current PMS version, no known IT issues |
| 4 | Cable internet (50+ Mbps), workstations 2–3 years old, PMS within 1 version of current |
| 3 | Cable internet (25–50 Mbps), workstations 3–4 years old, PMS within 2 versions of current |
| 2 | DSL or inconsistent connectivity, workstations 4–5 years old, PMS requires upgrade |
| 1 | Satellite/cellular internet, workstations 5+ years old, PMS significantly outdated, frequent IT issues |
Factor 2: Staff Tenure and Adaptability (Weight: 20%)
| Score | Criteria |
|---|---|
| 5 | <10% annual turnover, previous successful tech rollout, documented tech-forward culture |
| 4 | 10–20% turnover, positive response to past tech changes, stable core team |
| 3 | 20–30% turnover, mixed response to past tech changes, some resistance history |
| 2 | 30–40% turnover, significant past tech adoption challenges, leadership changes recent |
| 1 | >40% turnover, failed past tech implementations, unstable management |
Factor 3: Patient Volume (Weight: 20%)
| Score | Criteria | Strategic Note |
|---|---|---|
| 5 | High volume (150+ patients/week) | High impact, prioritize if other factors strong |
| 4 | Above average (120–149 patients/week) | Good impact with manageable scale |
| 3 | Average (90–119 patients/week) | Balanced risk/reward |
| 2 | Below average (60–89 patients/week) | Lower immediate impact but may be good pilot |
| 1 | Low volume (<60 patients/week) | Defer unless strategic reason |
Factor 4: Existing Tech Stack Compatibility (Weight: 20%)
| Score | Criteria |
|---|---|
| 5 | PMS and imaging system on CranioCatch "certified compatible" list, previous API integrations successful |
| 4 | PMS on compatible list, imaging system compatible with minor configuration |
| 3 | PMS compatible, imaging system requires workaround or manual workflow |
| 2 | PMS requires upgrade or custom integration, imaging compatibility uncertain |
| 1 | PMS not on compatible list, imaging system incompatible, major technical barriers |
Factor 5: Local Champion Availability (Weight: 15%)
| Score | Criteria |
|---|---|
| 5 | Identified tech-forward provider AND office manager, both enthusiastic, proven track record |
| 4 | One strong champion (provider or office manager) with executive presence |
| 3 | Potential champion identified but not confirmed, moderate enthusiasm |
| 2 | No obvious champion, would need to develop from scratch |
| 1 | Key staff resistant, leadership skeptical, no internal advocate |
Composite Score Calculation
Composite Score = (IT Score × 0.25) + (Staff Score × 0.20) + (Volume Score × 0.20)
+ (Tech Stack Score × 0.20) + (Champion Score × 0.15)
Score Interpretation and Wave Assignment
| Composite Score | Readiness Tier | Wave Recommendation |
|---|---|---|
| 4.5–5.0 | Tier 1: Highly Ready | Wave 1 (Pilot) candidates |
| 3.5–4.4 | Tier 2: Ready | Wave 2 candidates |
| 2.5–3.4 | Tier 3: Conditionally Ready | Wave 3 (address barriers first) |
| 1.5–2.4 | Tier 4: Not Ready | Defer until barriers resolved |
| <1.5 | Tier 5: Significant Barriers | Exclude from initial rollout |
Sample Location Assessment Matrix
| Location | IT (25%) | Staff (20%) | Volume (20%) | Tech (20%) | Champion (15%) | Composite | Wave |
|---|---|---|---|---|---|---|---|
| Austin Central | 5 | 4 | 5 | 4 | 5 | 4.60 | 1 |
| Dallas North | 4 | 5 | 4 | 5 | 4 | 4.40 | 1 |
| Houston West | 4 | 3 | 5 | 4 | 3 | 3.85 | 2 |
| San Antonio Main | 3 | 4 | 3 | 4 | 4 | 3.55 | 2 |
| El Paso | 2 | 3 | 2 | 3 | 2 | 2.40 | Defer |
Recommended Rollout Sequence Process
☐ 🟣 Complete readiness assessment for all locations (VP Operations + Regional Managers) ☐ Rank locations by composite score ☐ Select Wave 1 pilots: 2–3 highest-scoring locations that also represent portfolio diversity (geography, size, payer mix) ☐ ⚠️ Avoid selecting only "easy" locations—include at least one that represents common challenges ☐ 🟣 Present recommended sequence to CDO and CEO for approval ☐ Communicate wave assignments to regional managers and office managers
4. Rollout Strategy
Wave Structure Overview
| Wave | Locations | Timeline | Purpose |
|---|---|---|---|
| Wave 1: Pilot | 2–3 locations | Weeks 3–6 | Validate integration, refine training, identify issues |
| Wave 2: Expansion | 5–8 locations | Weeks 7–12 | Scale with refined playbook, stress-test support capacity |
| Wave 3: Full Rollout | Remaining locations | Weeks 13–20 | Enterprise deployment using proven process |
Wave 1: Pilot Locations (Weeks 3–6)
Selection Criteria for Wave 1
🟣 Select 2–3 locations meeting ALL of the following:
☐ Composite readiness score ≥4.5 ☐ Confirmed champion (provider or office manager actively engaged) ☐ Geographic accessibility for in-person support if needed ☐ Representative of broader portfolio (include at least one suburban and one urban, varied PMS if applicable) ☐ ⚠️ Avoid: locations with upcoming leadership changes, renovation, or major operational disruptions
Wave 1 Timeline
| Week | Activities |
|---|---|
| Week 3 | Configuration and integration at pilot locations, champion training |
| Week 4 | Staff training completion, parallel run begins (AI active but advisory only) |
| Week 5 | Go-live: AI fully integrated into workflow, daily check-ins |
| Week 6 | Stabilization, issue resolution, lessons learned capture |
Parallel Run Period (Wave 1)
Duration: 5 business days (Week 4)
Protocol:
- CranioCatch analyzes all radiographs and displays findings
- Providers document their independent diagnosis BEFORE viewing AI results
- Compare provider diagnosis vs. AI detection
- Track agreement rate, missed findings, false positives
- ⚠️ Do not modify treatment plans based solely on AI during parallel run
Daily/Weekly Check-In Cadence (Wave 1)
| Frequency | Participants | Duration | Focus |
|---|---|---|---|
| Daily (Week 5) | Location champion + VP Operations | 15 min | Issues, blockers, immediate fixes |
| Daily (Week 5) | Champion + Staff huddle | 5 min | Quick wins, questions, encouragement |
| Weekly (Weeks 5–6) | All Wave 1 champions + Central team | 30 min | Cross-location learning, pattern identification |
| End of Week 6 | Full pilot debrief | 60 min | Lessons learned, playbook refinements |
Escalation Path
| Tier | Issue Type | Response Time | Contact |
|---|---|---|---|
| Tier 0 | User error, quick fix | Immediate | Location champion |
| Tier 1 | Configuration, workflow | <2 hours | DSO IT / VP Operations |
| Tier 2 | Integration failure, data sync | <4 hours | DSO IT + CranioCatch CSM |
| Tier 3 🔵 | System outage, critical bug | <1 hour | CranioCatch emergency support |
Wave 2: Expansion (Weeks 7–12)
Go/No-Go Criteria for Wave 2
🟣 Wave 2 proceeds only when Wave 1 meets ALL criteria:
☐ System uptime ≥99% during pilot period ☐ ≥80% of staff rate training as "effective" or "very effective" ☐ No unresolved critical or high-severity bugs ☐ Provider acceptance: ≥75% report AI "helpful" or "very helpful" ☐ Integration stable: no data sync failures in final 5 days of pilot ☐ Lessons learned documented and playbook updated
⚠️ Wave 2 pause triggers (any one is sufficient):
- System uptime <95%
- Critical bug unresolved >48 hours
- Provider NPS <0 (net detractors exceed promoters)
- Champion turnover at pilot location
Wave 2 Timeline
| Week | Scope |
|---|---|
| Week 7 | Wave 2 location confirmation, pre-deployment prep |
| Week 8 | Configuration and integration (2–3 locations) |
| Week 9 | Training and parallel run (2–3 locations) |
| Week 10 | Go-live first cohort + remaining configuration (3–5 locations) |
| Week 11 | Go-live second cohort, stabilization |
| Week 12 | Full Wave 2 stabilization, lessons learned |
Buffer Between Waves
☐ Minimum 5 business days between Wave 1 completion and Wave 2 go-live ☐ Use buffer to: update training materials, refine configuration templates, address infrastructure gaps ☐ 🟣 Conduct formal Wave 1 retrospective before Wave 2 kickoff
Wave 3: Full Rollout (Weeks 13–20)
Wave 3 Acceleration Principles
By Wave 3, the following should be proven and repeatable:
- Configuration template deploys in <2 hours per location
- Training completion achievable in single day per role
- Champions can lead local implementation with minimal central support
- Known issues have documented resolutions
Wave 3 Timeline
| Week | Locations | Notes |
|---|---|---|
| Week 13–14 | 5–7 locations | First Wave 3 cohort |
| Week 15–16 | 5–7 locations | Second cohort |
| Week 17–18 | 5–7 locations | Third cohort |
| Week 19–20 | Remaining locations | Final cohort + stragglers |
Go/No-Go Criteria for Each Wave 3 Cohort
☐ Previous cohort stabilized (no critical issues in last 3 days) ☐ Support capacity available (<5 open tickets per support staff member) ☐ Champion confirmed and trained for each incoming location
Rollback Plan
⚠️ Rollback is a last resort but must be planned in advance.
Rollback Triggers (Any One Sufficient)
- System outage >4 hours during business hours
- Data integrity issue (incorrect patient/image matching)
- HIPAA/compliance incident
- Provider unanimously rejects tool after good-faith trial (requires CDO review)
Rollback Procedure
| Step | Action | Owner | Timeline |
|---|---|---|---|
| 1 | 🟣 Decision to roll back (requires VP Ops + CDO approval) | Executives | <2 hours from trigger |
| 2 | Notify affected location champions | VP Operations | Immediately |
| 3 | 🔵 Contact CranioCatch to disable integration | IT + CranioCatch | <1 hour |
| 4 | Revert to pre-CranioCatch workflow documentation | Location champions | <2 hours |
| 5 | Communicate to staff: temporary pause, not failure | Office managers | Same day |
| 6 | Root cause analysis with CranioCatch | IT + CranioCatch | Within 48 hours |
| 7 | Remediation plan and re-deployment timeline | Central team | Within 1 week |
Rollback Isolation
- Rollback can be location-specific; does not require enterprise-wide pause
- Locations in other waves continue unless issue is systemic (platform-level)
- 🟣 Systemic rollback requires CEO notification
5. Configuration & Integration (Weeks 2–3)
Practice Management System Integration
Dentrix Enterprise Integration
| Step | Action | Owner | Time |
|---|---|---|---|
| 1 | 🔵 Request Dentrix API credentials from Henry Schein | IT + Vendor | 3–5 days |
| 2 | 🔵 Provide API credentials to CranioCatch | IT | 1 day |
| 3 | 🔵 CranioCatch configures Dentrix connector | CranioCatch | 2–3 days |
| 4 | Enable CranioCatch integration module in Dentrix | IT (per location) | 30 min/location |
| 5 | Configure patient matching rules (name, DOB, chart number) | IT + CranioCatch | 1 hour |
| 6 | Test patient record retrieval in sandbox | IT | 1 hour |
| 7 | Test diagnostic code writeback | IT + Clinical | 1 hour |
| ⚠️ | Verify Dentrix version compatibility—G7+ required | IT | Pre-step |
Eaglesoft Integration
| Step | Action | Owner | Time |
|---|---|---|---|
| 1 | Confirm Eaglesoft version 21+ at all locations | IT | 1 day |
| 2 | 🔵 Enable Eaglesoft FHIR API (requires Patterson support) | IT + Patterson | 3–5 days |
| 3 | 🔵 Provide FHIR endpoint details to CranioCatch | IT | 1 day |
| 4 | 🔵 CranioCatch configures Eaglesoft connector | CranioCatch | 2–3 days |
| 5 | Test bidirectional data flow | IT | 2 hours |
| ⚠️ | Eaglesoft on-premise vs. cloud deployment affects integration method | IT | Pre-step |
Open Dental Integration
| Step | Action | Owner | Time |
|---|---|---|---|
| 1 | Enable Open Dental API in Program Properties | IT (per location) | 15 min/location |
| 2 | Generate API key per location | IT | 15 min/location |
| 3 | 🔵 Provide API keys to CranioCatch (centrally or per location) | IT | 1 hour |
| 4 | 🔵 CranioCatch configures Open Dental connector | CranioCatch | 1–2 days |
| 5 | Test integration in single location | IT | 1 hour |
| 6 | Replicate configuration across locations | IT | 15 min/location |
Imaging System Integration
Standard DICOM Integration
| Step | Action | Owner | Time |
|---|---|---|---|
| 1 | Identify DICOM server/PACS details at each location | IT | 2 hours |
| 2 | 🔵 Provide DICOM AE Title, IP, Port to CranioCatch | IT | 1 hour |
| 3 | Configure firewall rules to allow CranioCatch DICOM connection | IT | 1 hour |
| 4 | 🔵 CranioCatch configures DICOM receiver | CranioCatch | 1–2 days |
| 5 | Test image transmission: capture → CranioCatch → analysis | IT + Clinical | 1 hour |
| ⚠️ | Verify DICOM compliance of all imaging sensors—some older sensors require bridge software | IT | Pre-step |
Direct Sensor Integration (Common Brands)
| Imaging Brand | Integration Method | Notes |
|---|---|---|
| Dexis | TWAIN or DICOM | Verify Dexis Imaging Suite version |
| Schick | DICOM | Requires CDR DICOM software |
| Carestream | Direct API | 🔵 Requires CranioCatch-Carestream partnership activation |
| Planmeca | DICOM | Romexis DICOM module required |
| CBCT Systems | DICOM only | Volume data requires specific handling |
Test Environment Setup
Recommended Approach: Centralized Test Environment
☐ 🔵 Request CranioCatch sandbox/test tenant ☐ Connect sandbox to representative PMS and imaging system (use non-production data) ☐ Create test patient profiles with variety of pathology presentations ☐ Execute test cases:
| Test Case | Expected Result | Pass/Fail |
|---|---|---|
| New image capture → AI analysis | Analysis completes <30 seconds | ☐ |
| AI findings populate in PMS | Correct patient, correct tooth numbers | ☐ |
| Provider overrides AI finding | Override logged, audit trail created | ☐ |
| Historical image import | Images processed, findings available | ☐ |
| SSO authentication | User logs in via enterprise IdP | ☐ |
| Offline/degraded network | Graceful failure, no data loss | ☐ |
☐ Document test results and sign-off before production deployment
Data Migration / Historical Image Ingestion
Assessment Questions
☐ Do you want CranioCatch to analyze historical radiographs? (Common: last 12–24 months) ☐ Where are historical images stored? (Local server, cloud, PMS-embedded) ☐ What volume of historical images exists per location? ☐ What is the priority: speed (batch import) vs. on-demand (analyze when patient returns)?
Historical Ingestion Process (If Applicable)
| Step | Action | Owner | Time |
|---|---|---|---|
| 1 | Export historical images in DICOM format | IT (per location) | 2–4 hours/location |
| 2 | 🔵 Upload to CranioCatch secure transfer | IT | Variable by volume |
| 3 | 🔵 CranioCatch batch processes images | CranioCatch | 1–3 days per location |
| 4 | Verify processed images linked to correct patient | Clinical + IT | 2 hours |
| ⚠️ | Historical ingestion can be deferred to post-go-live for speed | — | — |
Security and HIPAA Compliance Verification
Enterprise-Level HIPAA Checklist
| Requirement | Verification | Status |
|---|---|---|
| 🔵 Business Associate Agreement (BAA) | Executed with CranioCatch covering all locations | ☐ |
| Data encryption in transit | TLS 1.2+ confirmed | ☐ |
| Data encryption at rest | AES-256 encryption of stored images | ☐ |
| Access controls | RBAC implemented, minimum necessary access | ☐ |
| Audit logging | All access logged with user ID, timestamp, action | ☐ |
| Data retention policy | Aligned with DSO retention requirements | ☐ |
| Breach notification | CranioCatch breach notification SLA documented | ☐ |
| Subcontractor agreements | CranioCatch subprocessors covered by BAAs | ☐ |
| Employee training | CranioCatch staff HIPAA trained | ☐ |
| Data location | Confirm data residency (US-based servers) | ☐ |
☐ 🟣 Legal/Compliance team sign-off on HIPAA compliance (required before production go-live)
Standardized vs. Location-Specific Configuration
Standardized Configuration Template (All Locations)
| Setting | Standard Value | Rationale |
|---|---|---|
| Pathology sensitivity | Medium | Balance accuracy and false positive rate |
| Tooth numbering system | Universal (1–32) | DSO standard |
| Auto-annotation display | Enabled | Consistent provider experience |
| Findings categories enabled | All | Comprehensive screening |
| Audit log retention | 7 years | Compliance requirement |
| SSO enforcement | Required | Security standard |
| Provider override required | Optional (logged) | Clinical autonomy with accountability |
Location-Specific Configuration (Can Vary)
| Setting | Variable By | Example |
|---|---|---|
| Imaging sensor profiles | Hardware at location | Schick vs. Dexis settings |
| Specialty-specific modules | Provider mix | Pedo locations enable deciduous detection |
| Language/localization | Patient demographics | Spanish-language patient reports |
| Working hours for support | Time zone | PST vs. EST business hours |
☐ Create configuration template document capturing all standard settings ☐ Define approval process for location-specific exceptions ☐ Track exceptions in central configuration registry
6. Team Training Plan
Train-the-Trainer Model
Structure
Central Training Team (CranioCatch + DSO)
↓
Location Champions (1 per location)
↓
All Location Staff (role-specific)
Champion Selection Criteria
☐ Role: Provider (dentist or hygienist with diagnostic scope) OR experienced office manager ☐ Tenure: Minimum 1 year at location, not planning departure ☐ Tech comfort: Above-average proficiency with existing digital tools ☐ Influence: Respected by peers, can overcome resistance ☐ Availability: Can dedicate 4–6 hours to champion training, then 2–4 hours to train team
Champion Responsibilities
- Complete champion certification (2-hour training + assessment)
- Deliver role-specific training to all location staff
- Serve as first point of contact for questions
- Escalate unresolved issues to regional manager
- Submit weekly adoption metrics during first month
- Participate in cross-location champion calls
Champion Certification Process
| Step | Activity | Duration | Owner |
|---|---|---|---|
| 1 | 🔵 Complete CranioCatch online certification | 90 min | Champion |
| 2 | 🔵 Attend live Q&A with CranioCatch trainer | 30 min | Champion + CranioCatch |
| 3 | Pass certification assessment (≥85%) | 15 min | Champion |
| 4 | Receive training delivery kit | — | Central team |
| 5 | Shadow training delivery at pilot location (Wave 1 only) | 2 hours | Champion |
Role-Specific Training Outlines
Dentists/Providers
Training Time: 45–60 minutes Format: Live demo (in-person or video call) + hands-on practice Delivered By: Location champion
Content Outline:
What CranioCatch does (5 min)
- AI analysis of radiographs for pathology and anatomical detection
- Decision support, not decision replacement
How it integrates into workflow (10 min)
- Image capture → automatic analysis → findings display
- Where findings appear (sidebar, overlay, or integrated view)
- Timing: analysis typically completes during image review
Interpreting AI output (15 min)
- Pathology categories detected (caries, periapical lesions, bone loss, calculus, etc.)
- Confidence scores: what high/medium/low means
- Annotations: bounding boxes, tooth numbers, severity indicators
- ⚠️ AI is trained on population data; edge cases require clinical judgment
When and how to override (10 min)
- You are always the final decision-maker
- Override logging: why it exists (audit trail, AI improvement, medicolegal)
- When to override: clinical context AI cannot see, patient history, findings outside AI training
- How to override: demonstrate the click/documentation process
Hands-on practice (15 min)
- Review 3–5 sample cases with AI findings
- Practice accepting findings, overriding findings, and documenting
Common Resistance Points:
| Resistance | Response |
|---|---|
| "I don't need AI to do my job" | "AI is a second set of eyes—studies show it catches findings providers miss and vice versa. You make the call." |
| "What about liability?" | "You remain the clinician of record. AI is a tool like a microscope—it enhances but doesn't replace judgment." |
| "This will slow me down" | "Initial slowdown is normal. After 1–2 weeks, most providers report no change or time savings." |
Day 1 Cheat Sheet: Providers
CRANIOCATCH QUICK REFERENCE - PROVIDERS
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1. Capture image as normal
2. AI analysis runs automatically (wait for ✓)
3. Review highlighted findings in sidebar
4. Click any finding to see detail
5. ACCEPT finding: Click checkmark (auto-documents)
6. OVERRIDE finding: Click X → Select reason → Add note
7. If AI shows nothing: Review image normally; document if you find something AI missed
8. Questions? Contact: [Champion name/number]
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Hygienists
Training Time: 30 minutes Format: Live demo + shadow session Delivered By: Location champion
Content Outline:
Overview (5 min)
- What CranioCatch is and why we're using it
- Hygienist role: capture quality images, understand AI output, do not make diagnostic determinations
Image capture best practices (10 min)
- AI accuracy depends on image quality
- Positioning, exposure, and angulation tips
- Common capture errors that reduce AI accuracy
Understanding AI findings in your workflow (10 min)
- What you'll see on screen after image capture
- How to communicate findings to provider (without diagnosing)
- Example language: "CranioCatch highlighted something on tooth #14 for Dr. [Name] to review"
What NOT to do (5 min)
- Do not tell patients they "have a cavity" based on AI
- Do not dismiss provider findings because AI didn't detect
- When in doubt, involve the provider
Common Resistance Points:
| Resistance | Response |
|---|---|
| "This isn't my job" | "Your role is awareness, not diagnosis. This helps you support providers and prepare patients." |
| "Patients will ask me about the screen" | "Great—we'll give you language to use that informs without diagnosing." |
Day 1 Cheat Sheet: Hygienists
CRANIOCATCH QUICK REFERENCE - HYGIENISTS
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1. Capture image using standard protocol
2. Confirm image quality before saving
3. AI analysis runs automatically
4. If AI highlights something: "Dr. [Name] will review the AI findings on tooth [#]"
5. DO NOT say: "The AI found a cavity"
6. DO say: "The system highlighted an area for the doctor to examine"
7. Questions? Contact: [Champion name/number]
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Front Desk / Office Manager
Training Time: 30 minutes Format: Live demo + administrative walkthrough Delivered By: Location champion
Content Outline:
Overview (5 min)
- What CranioCatch is and why we're adopting it
- Your role: administrative support, not clinical
Administrative functions (10 min)
- User management (if applicable)
- Reporting dashboard overview
- How to access usage statistics
Patient communication changes (10 min)
- If patients ask about "the AI": standard response language
- No change to scheduling, check-in, or checkout workflows
- If technical issues arise: escalation process
Supporting go-live (5 min)
- First-week responsibilities
- Tracking staff questions and issues
- Communicating with regional manager
Day 1 Cheat Sheet: Front Desk
CRANIOCATCH QUICK REFERENCE - FRONT DESK
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1. No change to scheduling/check-in/checkout
2. If patient asks about AI: "We use advanced technology to help our doctors provide thorough care."
3. If technical issue reported:
- First: Contact [Champion name]
- If urgent: Contact [Regional manager]
4. To access reports: [URL] > Reports > Usage
5. Questions? Contact: [Champion name/number]
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Billing/Insurance Staff
Training Time: 20 minutes Format: Video training + documentation review Delivered By: Location champion (or central billing team)
Content Outline:
Overview (5 min)
- CranioCatch supports diagnosis; minimal direct billing impact
- No new CDT codes specific to AI usage (as of current guidelines)
Documentation changes (10 min)
- AI-assisted findings auto-document in patient record
- How to locate AI findings in clinical notes
- Verify provider sign-off before claim submission
Claim denial considerations (5 min)
- If denial references "insufficient documentation," check AI findings capture
- No payor-specific AI restrictions identified (confirm with individual payors)
- ⚠️ Monitor for payor policy changes regarding AI-assisted diagnosis
Day 1 Cheat Sheet: Billing
CRANIOCATCH QUICK REFERENCE - BILLING
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1. No new CDT codes for AI (bill diagnosis as normal)
2. AI findings auto-populate in clinical notes
3. Verify provider signature before claim submission
4. If denial mentions documentation: Check AI findings section
5. Questions? Contact: [Champion name/number]
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Training Completion Tracking
Tracking Mechanism
☐ Create training roster per location (all staff by role) ☐ Champion marks completion with date ☐ Regional manager verifies completion before go-live ☐ 🟣 No location goes live without 100% role-required training completion
Training Tracker Template
| Location | Staff Name | Role | Training Required | Completed | Date | Champion Sign-off |
|---|---|---|---|---|---|---|
| Austin Central | Jane Doe | Provider | Provider module | ☐ | — | — |
| Austin Central | John Smith | Hygienist | Hygienist module | ☐ | — | — |
| ... | ... | ... | ... | ... | ... | ... |
Ongoing Training Cadence
New Hire Training
☐ Add CranioCatch training to new hire onboarding checklist ☐ Champion responsible for delivering within first 5 business days ☐ Training completion documented in HR system
Refresher Training
| Interval | Trigger | Format | Duration |
|---|---|---|---|
| 90 days | Scheduled | Champion-led huddle review | 15 min |
| Ad hoc | New feature release | 🔵 CranioCatch webinar or video | 20–30 min |
| Ad hoc | Identified knowledge gap | Champion-led micro-training | 10–15 min |
7. Change Management
Executive Sponsor Communication Plan
Board/Investor Updates
🟣 Frequency: Quarterly (aligned with board meetings) Owner: CEO with VP Operations input
Content Framework:
Strategic rationale (first update only): Why AI diagnostic imaging, why CranioCatch, alignment with DSO growth strategy
Progress metrics:
- Locations deployed (current wave, cumulative)
- On-track vs. delayed (explain variances)
- Staff adoption rates
Early outcomes:
- Diagnostic accuracy improvements (if measurable)
- Case acceptance trends
- Patient volume/throughput changes
Investment summary:
- Spend to date vs. budget
- Projected ROI timeline
Next quarter priorities:
- Wave progression plan
- Risks and mitigations
Sample Board Update Email
Subject: Q[X] AI Implementation Update: CranioCatch Diagnostic Imaging
Executive Summary:
- [X] of [Y] locations deployed (Wave [X] complete)
- On track for full deployment by [date]
- Early indicators positive: [key metric]
Detailed Report: [Link to 2-page PDF]
Key Decisions Requested: [None / Describe if any]
Regional Manager Briefing Guide
Purpose
Equip regional managers to communicate rollout plan to office managers and address questions confidently.
Briefing Cadence
| Timing | Format | Content |
|---|---|---|
| Pre-Wave 1 | 60-min video call | Full plan overview, their role, Q&A |
| Pre-each subsequent wave | 30-min video call | Wave-specific details, lessons from prior wave |
| Weekly during active wave | 15-min check-in | Status, escalations, support needs |
Key Messages for Regional Managers to Cascade
"This is a strategic investment in clinical quality and efficiency"
- Frame as supporting providers, not replacing or surveilling them
"Every location will be deployed, but in a sequence based on readiness"
- No location is being punished or prioritized unfairly
"Your office manager and champion will lead locally—you're the connector"
- Regional manager role: resource allocation, escalation, cross-location learning
"We expect questions and concerns—escalate them, don't suppress them"
- Resistance is normal; early surfacing prevents late-stage problems
"We're measuring results and will adjust based on data"
- This is a learning deployment, not a mandate
FAQ for Regional Managers
| Question | Response |
|---|---|
| "What if a provider refuses to use it?" | "Understand their concern. Engage them 1:1. Involve CDO if needed. Mandating rarely works—engagement does." |
| "What if the AI makes a mistake?" | "The provider is always the final decision-maker. AI is a tool, not an authority. Document and escalate accuracy issues." |
| "Why is my location in Wave 3?" | "Wave sequencing is based on readiness factors, not quality judgments. Earlier waves help us learn so later waves go smoother." |
Staff Resistance Framework for Multi-Location Dynamics
Common Resistance Archetypes
| Archetype | Belief | Engagement Strategy |
|---|---|---|
| The Skeptic | "This is just another overhyped tech fad" | Share peer-reviewed evidence; connect with adopters from Wave 1 |
| The Threatened | "They're trying to replace me" | Emphasize AI as assistant, not replacement; highlight job security |
| The Overwhelmed | "I don't have time to learn something new" | Simplify training; show time-saving potential post-adoption |
| The Perfectionist | "What if AI makes mistakes?" | Explain human oversight; validate their quality commitment |
| The Wait-and-See | "I'll see how others do first" | Provide early success stories; peer influence works |
Location-Level Resistance Triage
| Signal | Severity | Action |
|---|---|---|
| Questions during training | Normal | Champion addresses |
| Grumbling in huddles | Monitor | Champion engages, notifies regional manager |
| Passive non-use | Concerning | Regional manager conversation; identify root cause |
| Active vocal opposition | Serious | Regional manager + CDO intervention |
| Provider threatens resignation | Escalate | 🟣 CDO + HR involvement |
Internal Marketing
Initiative Naming
Give the implementation a name that conveys positive intent and creates identity.
Example options:
- "ClearView Initiative" (clarity in diagnosis)
- "Second Set of Eyes Program" (collegial support)
- "Diagnostic Excellence Initiative" (quality framing)
🟣 Select name with executive sponsor input to ensure alignment with DSO brand voice.
Momentum-Building Tactics
| Tactic | Timing | Owner |
|---|---|---|
| Launch announcement (email + video from CEO) | Pre-Wave 1 | CEO/COO |
| Champion spotlight in internal newsletter | Weekly during rollout | Marketing/HR |
| "Quick win" stories shared across regions | After each wave | Regional managers |
| Live Q&A webinar for all staff | Pre-Wave 1, pre-Wave 3 | VP Operations + CranioCatch |
| Swag for champions (polo, badge, etc.) | Wave 1 training | HR/Operations |
Milestone Celebrations
| Milestone | Celebration |
|---|---|
| Wave 1 complete | Shout-out in company all-hands; pilot location recognition |
| 50% deployment | Email from CEO; metric highlight |
| 100% deployment | Enterprise-wide announcement; "founding team" recognition |
| ROI milestone achieved | Board communication; employee bonus consideration |
8. Go-Live Day Runbook
Standardized Go-Live Checklist (Every Location)
48 Hours Before Go-Live
☐ Verify integration is active (test image flows to CranioCatch, findings return) ☐ Confirm all staff training marked complete ☐ Champion reviews escalation contacts with staff ☐ Test all workstations that will use CranioCatch ☐ Print and post Day 1 cheat sheets in operatories ☐ Regional manager confirms location is ready (formal sign-off)
24 Hours Before Go-Live
☐ Final integration test (capture live image, verify analysis) ☐ Champion sends reminder email to staff with go-live time ☐ Confirm on-call support availability (central IT, CranioCatch) ☐ Pre-stage troubleshooting supplies (backup login credentials, support phone numbers)
Hour-by-Hour Schedule
Go-Live Day: [Insert Date]
| Time | Activity | Who |
|---|---|---|
| 7:00 AM | Champion arrives 30 min before office opens | Champion |
| 7:15 AM | Verify all systems operational | Champion + IT (remote) |
| 7:30 AM | 10-minute staff huddle: confidence check, questions | Champion + All staff |
| 8:00 AM | First patient with CranioCatch-assisted imaging | Provider + Hygienist |
| 8:30 AM | Champion checks in with first provider: any issues? | Champion |
| 9:00 AM | Check-in call with regional manager | Champion + Regional manager |
| 10:00 AM | Mid-morning pulse check: any emerging patterns? | Champion |
| 12:00 PM | Champion lunch with providers: informal debrief | Champion + Providers |
| 1:00 PM | Check-in call with central IT/VP Operations | Champion + Central team |
| 3:00 PM | Afternoon pulse check | Champion |
| 5:00 PM | End-of-day huddle: wins, challenges, questions | Champion + All staff |
| 5:30 PM | Champion submits Day 1 report | Champion → Regional manager |
Who Needs to Be On-Site or On-Call
| Role | Location | Contact Method |
|---|---|---|
| Location Champion | On-site | Direct availability |
| Office Manager | On-site | Direct availability |
| Regional Manager | On-call | Mobile phone, Slack |
| VP Operations | On-call | Mobile phone, Slack |
| DSO IT Support | On-call | Support hotline, Slack |
| 🔵 CranioCatch Support | On-call (Tier 2+) | [Vendor support number] |
Known Gotchas and Troubleshooting
Issue 1: AI Analysis Not Appearing After Image Capture
Symptoms: Image captured but no AI findings display
Troubleshooting:
- Check internet connectivity (run speed test)
- Verify image format is supported (check sensor settings)
- Confirm CranioCatch integration is active in system tray/status
- Log out and log back in
- If persists: Restart workstation
- If still persists: Escalate to IT
Escalation Trigger: Issue affects >1 workstation or >2 patients
Issue 2: Wrong Patient Matched to Images
⚠️ Severity: High
Symptoms: AI analysis displays but patient name/chart number doesn't match
Immediate Action:
- STOP—do not proceed with that analysis
- Document the error (screenshot)
- Notify champion immediately
- Champion escalates to IT + CranioCatch
Root Cause Investigation:
- Check patient matching rules (name, DOB, chart number)
- Verify imaging software patient selection process
- 🔵 CranioCatch technical review required
Issue 3: Analysis Taking Too Long (>60 seconds)
Symptoms: Spinning/loading indicator persists
Troubleshooting:
- Check internet connectivity
- Check CranioCatch system status page: [status.craniocatch.com]
- Try different workstation
- If widespread: Likely server-side issue—escalate to CranioCatch
Workaround: Provider proceeds with manual interpretation; analysis will process eventually
Issue 4: Provider Disagrees Strongly with AI Finding
Symptoms: Provider believes AI finding is clearly wrong
Protocol:
- Provider overrides with documented reason
- Champion notes for end-of-day report
- If pattern emerges (same type of error multiple times): Escalate to CDO + CranioCatch
- ⚠️ Never force provider to accept AI finding
Patient Communication Script
If the tool is patient-facing or visible to patients:
Scenario: Patient asks about the AI annotations they see on screen
Response:
"Great question! We use advanced technology to help ensure we don't miss anything when reviewing your X-rays. Think of it as a second set of eyes for your dentist. Dr. [Name] reviews everything personally and makes all the decisions about your care."
If patient expresses concern:
"Your care is always guided by Dr. [Name], not a computer. The technology just helps us be as thorough as possible."
If patient asks about privacy:
"Your images are protected by the same privacy rules as all your medical information. The system is fully HIPAA compliant."
First-Week Daily Check-In Protocol
Champion → Regional Manager
Format: 15-minute call or detailed Slack/email
Daily Report Template:
LOCATION: [Name]
DATE: [Day 1/2/3/4/5]
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PATIENTS IMAGED WITH AI: [#]
ISSUES LOGGED: [#]
CRITICAL ISSUES: [None / Describe]
RESOLVED ISSUES: [Describe]
PENDING ISSUES: [Describe with ETA]
STAFF SENTIMENT: [Green / Yellow / Red]
PROVIDER FEEDBACK THEMES: [Brief summary]
SUPPORT NEEDED: [None / Describe]
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Escalation Tiers
| Tier | Role | Handles | Response Time |
|---|---|---|---|
| 0 | Location Champion | User questions, minor workflow issues | Immediate |
| 1 | Regional Manager | Staffing, local escalations, morale issues | <2 hours |
| 2 | Central IT / VP Operations | Technical issues, integration failures | <4 hours |
| 3 🔵 | CranioCatch Support | Platform issues, outages, accuracy concerns | Per SLA |
9. Post-Launch Optimization (Weeks 4–8)
Weekly Metrics Review Cadence
Review Structure
| Week | Meeting | Participants | Duration |
|---|---|---|---|
| 1 | Daily check-ins (first week) | Champion + Regional | 15 min |
| 2 | 2x weekly | Champion + Regional | 15 min |
| 3–4 | Weekly | Regional + VP Ops | 30 min |
| 5–8 | Weekly | VP Ops + IT + CDO | 30 min |
Core Metrics to Track
| Metric | Target | Red Flag |
|---|---|---|
| System uptime | ≥99% | <95% |
| AI analysis completion rate | ≥98% | <90% |
| Provider override rate | 10–25% | >40% or <5% |
| Average analysis time | <30 seconds | >60 seconds |
| Support ticket volume | Decreasing weekly | Increasing after Week 2 |
| Staff satisfaction (pulse survey) | ≥3.5/5 | <3.0/5 |
30-Day Checkpoint: What "Good" Looks Like vs. Red Flags
What "Good" Looks Like
☐ AI analysis completing on ≥98% of captured images ☐ Providers report AI is "helpful" at ≥75% rate ☐ Override rate between 10–25% (indicates appropriate clinical judgment) ☐ Support tickets declining week-over-week ☐ No unresolved critical issues ☐ Staff pulse survey satisfaction ≥3.5/5
Red Flags (Trigger Investigation)
⚠️ Override rate >40% (Investigate: AI accuracy? Training gap? Provider resistance?) ⚠️ Override rate <5% (Investigate: Rubber-stamping? Over-reliance?) ⚠️ Support tickets increasing in Week 3–4 (Investigate: Emerging issue? Training gap?) ⚠️ Staff satisfaction <3.0/5 (Investigate: Workflow burden? Fear? Technical frustration?) ⚠️ Provider actively avoiding AI (Investigate: Individual concerns? Systemic problem?)
60-Day Checkpoint: ROI Assessment Framework
ROI Measurement Structure
Compare 60-day post-launch data to baseline metrics captured in Week 1–2.
| Metric | Baseline | 60-Day | Change | ROI Implication |
|---|---|---|---|---|
| Case acceptance rate | [%] | [%] | [+/- %] | Higher = more treatment revenue |
| Average diagnosis time | [min] | [min] | [+/- min] | Lower = more patients seen |
| Pathology detection rate | [per 100] | [per 100] | [+/- #] | Higher = better clinical outcomes |
| Claim denial rate | [%] | [%] | [+/- %] | Lower = fewer write-offs |
| Patient throughput | [pts/day] | [pts/day] | [+/- #] | Higher = revenue capacity |
| Provider diagnostic variability | [std dev] | [std dev] | [+/- σ] | Lower = standardization benefit |
ROI Calculation (Simplified)
Revenue Impact = (Δ Case Acceptance × Average Case Value × Patient Volume)
+ (Δ Throughput × Average Revenue per Patient)
- (CranioCatch subscription cost)
60-Day Report Template
🟣 Deliver to executive leadership
CRANIOCATCH 60-DAY ROI ASSESSMENT
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Locations Assessed: [#]
Period: [Date range]
KEY FINDINGS:
• Case acceptance: [Baseline] → [60-Day] ([+/-X%])
• Diagnosis time: [Baseline] → [60-Day] ([+/-X min])
• Detection rate: [Baseline] → [60-Day] ([+/-X per 100])
ESTIMATED REVENUE IMPACT: $[X] per month across assessed locations
EXTRAPOLATED ENTERPRISE IMPACT (full deployment): $[X] per month
RECOMMENDATION: [Continue rollout / Pause for adjustments / Expand scope]
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Staff Feedback Collection: 5-Question Pulse Survey
Frequency: Weekly for first 4 weeks, then monthly Method: Anonymous, 2-minute survey (Google Forms, SurveyMonkey, or internal tool)
Survey Questions
How helpful is CranioCatch in your daily work?
- 1 (Not helpful) – 5 (Very helpful)
How confident are you using CranioCatch?
- 1 (Not confident) – 5 (Very confident)
Has CranioCatch changed the amount of time you spend on diagnosis/imaging?
- Saves significant time / Saves some time / No change / Takes more time / Takes significantly more time
What is your biggest challenge with CranioCatch?
- [Open text]
What is working well?
- [Open text]
Survey Analysis Protocol
☐ Champion reviews results weekly ☐ Aggregate by role (provider vs. hygienist vs. admin) ☐ Identify themes in open-text responses ☐ Flag scores <3.0 for follow-up ☐ Include in weekly metrics report to regional manager
Workflow Refinements: Common Adjustments After Month 1
Common Adjustment 1: Display Settings
Issue: Providers find annotations distracting Adjustment: Configure annotation display to "on hover" vs. always visible Who: Champion requests via IT; 🔵 CranioCatch confirms capability
Common Adjustment 2: Sensitivity Tuning
Issue: Too many low-confidence findings (provider fatigue) Adjustment: Increase confidence threshold for display (e.g., show only high/medium confidence) Who: 🟣 CDO approval required; IT implements
Common Adjustment 3: Integration Timing
Issue: AI analysis arrives after provider has already reviewed Adjustment: Workflow change—brief pause before provider reviews, or notification when analysis ready Who: Champion trains staff on adjusted workflow
Common Adjustment 4: Override Documentation
Issue: Providers find override documentation burdensome Adjustment: Simplify override reason dropdown; allow batch overrides for similar findings Who: 🔵 CranioCatch configuration request
Centralized Dashboard Structure (DSO)
Per-Location Metrics (Viewable by Regional Manager + VP Ops)
| Metric | Display | Drill-Down |
|---|---|---|
| Daily images analyzed | Line chart (7-day trend) | By provider |
| AI uptime | % and status indicator | Incident log |
| Override rate | % with trend | By pathology type |
| Support ticket count | Count with severity breakdown | Ticket detail |
| Staff satisfaction (latest pulse) | Score with trend | By role |
Aggregate Enterprise Metrics (Viewable by VP Ops, CDO, C-suite)
| Metric | Display | Benchmarking |
|---|---|---|
| Deployment progress | # deployed / # total locations | Wave status |
| Enterprise adoption rate | % of images AI-analyzed | Location ranking |
| Enterprise case acceptance |
AI-generated implementation guide based on public vendor information. Verify specifics directly with CranioCatch.