Acuity Provider Implementation Guide

ACUITYhealth - Continuous Care Plan (CCP)

A Three-Layer Architecture for Continuous Care Management

Provider Implementation Guide
10-Step Educational Framework
Transforming Episodic Care to Continuous Health Management

1

Acuity System Foundation

Three-Layer Architecture for Continuous Care Management
STEP 1: Understanding the Core Architecture
System Components Overview:
The Acuity platform operates through three integrated layers that work synchronously to deliver continuous care management, moving beyond episodic "sick care" to proactive health maintenance.
Implementation Actions:
  • Layer 1 - Patient Engagement: Deploy ambient voice assistants, mobile apps, and RPM devices in patient homes for 24/7 data collection
  • Layer 2 - Skilled Care Visits: Equip therapists, nurses, and care managers with ambient AI documentation tools for visit capture
  • Layer 3 - Provider Oversight: Set up provider dashboards with population health views and individual care plan access
  • Central Hub: Establish the 10-chevron Continuous Care Plan as the unified documentation structure across all layers
  • QHIN Integration: Leverage existing QHIN connectivity to automatically pull external health records into the system

Key Technology Stack

• Ambient AI speech recognition tuned for healthcare
• Natural language processing for clinical context
• Real-time data aggregation engines
• TEFCA-compliant health information exchange
• Risk stratification algorithms

Impact Statement

This foundational architecture eliminates data silos and creates a single source of truth for each patient. Providers gain unprecedented visibility into patient health between visits, reducing emergency hospitalizations by enabling early interventions. The three-layer approach ensures scalability while maintaining personalized care delivery.

2

Patient Engagement Layer Implementation

24/7 Ambient Monitoring & Data Collection Infrastructure
STEP 2: Deploy Patient-Facing Technology
Core Objective:
Create a continuous data collection ecosystem in the patient's daily environment using ambient voice AI, RPM devices, and mobile interfaces to capture both subjective and objective health data.
Deployment Sequence:
  • Voice Assistant Activation: Install smart speakers or enable phone apps with always-on ambient listening for symptom reporting ("I have a headache and my blood pressure feels high")
  • RPM Device Distribution: Deploy digital BP cuffs, glucometers, pulse oximeters, smart scales, and wearables with automatic data transmission to Acuity
  • Mobile App Onboarding: Train patients on daily symptom surveys, medication logging, and goal tracking through the existing UX interface
  • SDOH Data Collection: Implement conversational queries about transportation, housing, nutrition, and social support barriers
  • Medication Adherence System: Set up automated reminders with voice confirmation ("Did you take your morning medications?")
  • Personal Goal Setting: Collaborate with patients to establish measurable health goals (e.g., "Walk 15 minutes daily") with progress tracking

Asynchronous Communication Protocols

• Secure portal messages count toward CCM time
• App-based check-ins are billable interactions
• Device alerts trigger async provider responses
• All communications auto-documented in care plan
• No requirement for immediate response under CCM guidelines

Impact Statement

This layer transforms patient engagement from periodic encounters to continuous connection. Studies show AI virtual assistants increase medication adherence and daily health data collection rates. The ambient nature removes friction - patients simply speak naturally rather than navigating complex interfaces. This leads to richer data capture, earlier problem detection, and improved patient activation in their own care.

3

Skilled Care Visit Optimization

Ambient AI Documentation & Care Plan Synchronization
STEP 3: Enable Ambient Documentation for Field Clinicians
Implementation Focus:
Deploy ambient AI scribes for PT, OT, speech therapy, nursing, and care management visits to eliminate documentation burden while ensuring real-time care plan updates.
Workflow Implementation:
  • Pre-Visit Review: Clinicians access the shared care plan with color-coded chevrons (Red/Yellow/Green) to identify care gaps before entering the home
  • Ambient Capture Activation: Start the AI scribe at visit beginning - it listens to natural conversation and structures data into care plan sections
  • Guided Assessment Protocol: Use red/yellow flags as a checklist - if "Social/SDOH" is red, probe food insecurity; if "Goals" is yellow, discuss progress
  • Real-Time Documentation: As patient mentions "more knee pain on stairs," AI logs to Symptom section and tags to musculoskeletal problem list
  • Functional Testing Capture: Speak observations aloud ("Patient scored 26/30 on mini-mental exam") for automatic recording in Cognitive/Functional Status
  • Intervention Documentation: New exercises, education provided, or referrals made are captured and placed in appropriate chevron sections
  • Auto-Generated Notes: Complete SOAP notes and progress documentation created without post-visit "pajama time"
1
Review care plan gaps (red/yellow sections)
2
Activate ambient AI documentation
3
Conduct natural patient conversation
4
AI structures data into care plan sections

Impact Statement

Ambient documentation increases face-to-face patient time by 40% while improving documentation accuracy. Therapists maintain eye contact and provide hands-on care without laptop interruptions. The guided gap-closure approach ensures no critical issues are missed. Documentation consistency across disciplines eliminates fragmentation, giving supervising providers a coherent view of all interventions.

4

Continuous Care Plan Architecture

The 10 Chevrons - Comprehensive Patient Documentation Framework
STEP 4: Implement Standardized Care Plan Sections
Medicare Compliance Built-In:
The 10-chevron structure aligns with CMS requirements for CCM, TCM, and AWV services, ensuring complete documentation for billing while improving care quality.
1. Patient Problems/Diagnoses: Current chronic conditions with severity indicators and prognoses
2. Goals & Expected Outcomes: Patient-specific measurable targets aligned with conditions
3. Symptom & Vital Trends: Real-time aggregation of patient-reported symptoms and RPM data
4. Medications & Adherence: Current meds, compliance tracking, side effects, and changes
5. Care Team & Contacts: PCP, specialists, caregivers with contact methods for coordination
6. Interventions & Treatment Plan: Active therapies, education, and treatment protocols
7. Appointments & Follow-ups: Scheduled visits, routine screenings, and callback reminders
8. Social/Environmental Factors: SDOH issues, living situation, community resources
9. Cognitive/Functional Status: Assessment scores, ADL capabilities, mobility status
10. Documentation Log & Reviews: Interaction history, care plan revision dates, time tracking

Auto-Population Sources

• Patient voice inputs → Symptoms, Goals, SDOH
• RPM devices → Vital Trends
• QHIN records → Problems, Medications, Appointments
• Skilled visits → Functional Status, Interventions
• Provider updates → Treatment Plans, Team changes

Impact Statement

This standardized structure ensures nothing falls through the cracks. Every team member contributes to the same sections, eliminating duplication and confusion. The care plan becomes a living document that satisfies regulatory requirements while serving as an actionable clinical tool. Providers spend less time searching for information and more time making care decisions.

5

Provider Oversight Dashboard

Population Health Management & Risk Stratification
STEP 5: Deploy Risk-Based Population Management Tools
Dashboard Architecture:
Providers managing 100+ patients need instant visibility into who needs attention most urgently. The red/yellow/green triage system dynamically updates based on incoming data streams.
Risk Stratification Implementation:
  • Red Flag Triggers: BP readings >180/110 for 3 days, weight gain >5 lbs overnight, missed medications x3, no data x1 week, ER visit detected
  • Yellow Flag Indicators: Trending vitals approaching thresholds, new symptoms reported, upcoming care gaps, partial engagement
  • Green Status Maintenance: All vitals within range, good adherence, recent successful visits, goals on track
  • Dynamic Reallocation: Status updates in real-time as new data flows in - a stable patient can turn red within hours if concerning data arrives
  • Alert Configuration: Customize notification thresholds per patient based on their specific conditions and care plan parameters
  • Panel View Options: Sort by risk level, last contact, specific conditions, or upcoming care management deadlines
1
Morning panel review - identify all red flags
2
Drill into individual care plans for context
3
Initiate interventions (calls, med changes, visits)
4
Document actions in care plan for billing

Impact Statement

Risk stratification ensures providers focus time on patients who need it most. High-risk patients receive immediate attention before complications escalate to hospitalizations. The dashboard eliminates the need to manually review each chart daily - the system surfaces actionable intelligence. This proactive approach aligns with value-based care models and improves both outcomes and efficiency.

6

Intelligent Alert System

Care Plan-Driven Monitoring & Automated Interventions
STEP 6: Configure Smart Alert Parameters
Alert Intelligence:
The system continuously compares incoming data against care plan parameters, generating targeted alerts linked to specific chevron sections for immediate action.
Alert Configuration Pipeline:
  • Baseline Establishment: Set patient-specific thresholds in care plan (e.g., "Maintain glucose <150 mg/dL" for diabetic patient)
  • Multi-Source Monitoring: Track RPM devices, patient voice reports, skilled visit findings, and QHIN updates simultaneously
  • Intelligent Correlation: Link alerts to relevant chevron - weight gain flags under "CHF management" in Interventions section
  • Escalation Protocols: Define when to notify RN vs. MD vs. emergency response based on severity and duration
  • Suppression Logic: Prevent alert fatigue by grouping related issues and respecting provider acknowledgment windows
  • Trend Analysis: Flag gradual deterioration even within "normal" ranges if trajectory is concerning
  • Context Awareness: Consider recent interventions - don't alert on expected post-medication BP drop

Alert Response Workflows

• Immediate: Chest pain report → Provider notification + patient callback
• Urgent: BP spike x3 days → Med adjustment consideration
• Routine: Goal not met → Next visit discussion item
• Informational: Lab result received → Review at monthly check
• All alerts documented with timestamp and response

Impact Statement

Intelligent alerts transform reactive care into predictive intervention. The system acts as a 24/7 clinical assistant that never misses concerning patterns. By linking alerts to specific care plan sections, providers instantly understand context and required actions. This reduces cognitive load while ensuring critical issues receive timely attention, preventing approximately 30% of avoidable hospitalizations.

7

Monthly CCM Workflow Optimization

Streamlined Review Process & Billing Compliance
STEP 7: Execute Monthly Care Plan Reviews
CCM Requirements:
Medicare requires ≥20 minutes of non-face-to-face care coordination monthly with comprehensive care plan review and revision for billing codes 99490/99439.
Monthly Review Protocol:
  • Time Accumulation: System auto-logs patient app interactions, async messages, phone calls, and care coordination - often reaching 20 minutes without additional effort
  • Pre-Populated Updates: Open care plan to find all month's data already integrated - new problems, medication changes, goal progress
  • Gap Analysis: Review any remaining yellow/red chevrons that weren't addressed during the month
  • Plan Modifications: Update goals, adjust interventions, modify thresholds based on month's data trends
  • Documentation Verification: Confirm all interactions logged in Documentation chevron with timestamps
  • Billing Code Assignment: System suggests appropriate codes based on time spent and complexity
  • Patient Communication: Generate patient-friendly summary of plan changes for next month
  • Quality Metrics: Track adherence improvements, ER avoidance, goal achievement rates
1
System aggregates month's interactions (usually >20 min)
2
Provider reviews pre-populated care plan updates
3
Make clinical decisions on plan modifications
4
Attest to review and submit for billing

Impact Statement

Automated time tracking and pre-population reduce monthly review time from hours to minutes. Providers focus on clinical decision-making rather than data gathering. The comprehensive documentation ensures 100% billing compliance and audit readiness. This efficiency allows practices to manage larger CCM panels while maintaining quality, increasing revenue by 15-20% through proper capture of care management services.

8

Transitional Care Integration

Hospital Discharge & Care Continuity Management
STEP 8: Implement TCM & Care Transition Protocols
Transition Points:
QHIN connectivity automatically captures hospital discharges, specialist visits, and ER encounters, triggering immediate care plan updates and follow-up workflows.
Transition Management Pipeline:
  • Discharge Detection: QHIN feed alerts system within hours of hospital/ER discharge with full summary
  • Auto-Population: New diagnoses added to Problem List, medication reconciliation initiated, follow-up appointments logged
  • Risk Elevation: Patient automatically moves to "red" status for 30-day TCM period requiring close monitoring
  • 48-Hour Contact: System prompts care team for required patient contact within 2 business days (TCM requirement)
  • Medication Reconciliation: AI compares pre/post discharge meds, flags discrepancies for pharmacist review
  • Home Safety Assessment: Skilled visit scheduled to evaluate functional status post-discharge
  • 14-Day Provider Visit: Auto-scheduled face-to-face required for complex TCM billing (99496)
  • 30-Day Monitoring: Enhanced RPM and daily check-ins during high-risk readmission window

Readmission Prevention Protocol

• Daily vital monitoring with tighter thresholds
• Medication adherence verification via voice AI
• Symptom escalation pathways defined
• Social support activation (meals, transportation)
• Specialist follow-ups tracked and confirmed

Impact Statement

Seamless transition management reduces 30-day readmissions by up to 25%. The automatic capture of discharge data eliminates dangerous information gaps. Immediate risk elevation ensures vulnerable post-acute patients receive intensive monitoring when they need it most. The structured TCM workflow ensures billing compliance while delivering evidence-based transition care that significantly improves outcomes.

9

Annual Wellness Visit Optimization

Comprehensive Yearly Assessment & Preventive Planning
STEP 9: Leverage Continuous Data for AWV Efficiency
AWV Advantage:
With a year of continuous monitoring data, the Annual Wellness Visit becomes a comprehensive review rather than a data collection exercise.
AWV Preparation & Execution:
  • Pre-Visit Analysis: System generates 12-month trend reports for all vital signs, symptoms, and goal achievement
  • Risk Assessment Update: Health Risk Assessment (HRA) pre-populated with year's SDOH data, functional changes, behavioral patterns
  • Screening Schedule: Automatically identifies due/overdue preventive screenings based on age, gender, risk factors
  • Medication Effectiveness Review: Analyze adherence patterns vs. outcome metrics to identify optimization opportunities
  • Goal Recalibration: Review past year's goal achievement, set new targets based on current functional status
  • Care Team Evaluation: Assess if current team composition meets patient's evolving needs
  • Advance Directive Discussion: Document preferences with year of relationship-building as foundation
  • Personalized Prevention Plan: Generate next year's roadmap based on data-driven risk predictions

AWV Documentation Components

• Updated problem list with prognoses
• Current medications with effectiveness data
• Preventive screening schedule
• Cognitive assessment results
• Functional status evaluation
• Personalized health advice
• All auto-populated from continuous monitoring

Impact Statement

The data-rich AWV transforms from a checkbox exercise to a strategic health planning session. Providers can identify subtle year-over-year changes that predict future decline. The comprehensive view enables truly personalized prevention strategies. Visit time is spent on meaningful discussions rather than data gathering, improving both patient satisfaction and preventive care quality scores.

10

Continuous Quality Improvement

Outcome Metrics & System Optimization Protocols
STEP 10: Measure Impact & Refine Workflows
Performance Analytics:
The platform generates comprehensive analytics on clinical outcomes, operational efficiency, and financial performance to drive continuous improvement.
Key Performance Indicators to Track:
  • Clinical Outcomes: Hospital admission rates (target: 25% reduction), ER visits avoided, medication adherence rates (target: >80%), BP/glucose control rates
  • Engagement Metrics: Daily patient interaction rates, RPM data submission consistency, care plan completion percentages, red-flag response times
  • Operational Efficiency: Documentation time saved (target: 2 hrs/day per provider), visit productivity increases, care coordination minutes captured
  • Financial Performance: CCM billing capture rate (target: >90% eligible patients), TCM completion rates, quality bonus achievement
  • Provider Satisfaction: Burnout reduction scores, after-hours work reduction, clinical decision support satisfaction
  • Patient Experience: Activation scores, goal achievement rates, satisfaction surveys, health literacy improvements

Optimization Feedback Loops

• Weekly team huddles on red-flag patterns
• Monthly alert threshold adjustments
• Quarterly workflow refinements
• Semi-annual provider training updates
• Annual patient enrollment optimization
• Continuous AI model training on local patterns

1
Generate monthly outcome reports
2
Identify improvement opportunities
3
Implement targeted interventions
4
Measure impact and iterate

Impact Statement

Continuous measurement and optimization ensure the platform delivers on its promise of better outcomes at lower cost. Regular analysis identifies which interventions drive the greatest impact, allowing resource reallocation to high-value activities. The feedback loop creates a learning health system that improves over time. Organizations typically see 30% reduction in total cost of care within 18 months while improving quality scores and provider satisfaction.