Workflow GuideAtrial Fibrillation

AFib Chronic Care Risk Stratification Workflow

Standardized workflow for Atrial Fibrillation risk stratification, CHA2DS2-VASc assessment, and anticoagulation management for chronic care patients.

Managing chronic Atrial Fibrillation requires precise risk stratification to prevent strokes and optimize rate vs. rhythm control. This workflow leverages AI automation to ensure consistent CHA2DS2-VASc assessments and anticoagulation adherence monitoring across your entire AFib patient panel, improving clinical outcomes and practice efficiency.

The Challenge

Manual risk stratification is often inconsistent, leading to missed anticoagulation adjustments and delayed follow-ups for high-risk AFib patients, increasing the likelihood of stroke or heart failure exacerbations while overwhelming clinical staff.

Step-by-Step Workflow

1

Patient Identification & APCM Enrollment

AI identifies patients with AFib diagnoses in the EHR and initiates automated calls to explain the Chronic Care Management (CCM) or Advanced Primary Care Management (APCM) benefits, securing consent and establishing a baseline clinical status.

Best Practices
  • Use automated triggers for new AFib diagnoses
  • Verify insurance coverage for APCM early
Common Pitfalls
  • Failing to update the problem list after hospital discharge
2

Automated CHA2DS2-VASc Reassessment

The AI agent prompts patients for updates on comorbid conditions such as new hypertension or diabetes diagnoses to recalculate stroke risk scores dynamically, ensuring the clinical record reflects the most current risk profile.

Best Practices
  • Integrate score calculation into the intake flow
  • Ask specifically about recent TIA or stroke events
Common Pitfalls
  • Relying on outdated age-based risk factors alone
3

Anticoagulation Adherence Monitoring

Automated outreach verifies DOAC or Warfarin adherence, screening for missed doses, side effects like unusual bruising, or financial barriers to filling prescriptions that could lead to non-compliance.

Best Practices
  • Schedule calls one week before refills are due
  • Flag patients reporting high out-of-pocket costs
Common Pitfalls
  • Assuming pharmacy data is always 100% accurate
4

Symptom & Rate Control Assessment

Patients are screened for palpitations, shortness of breath, and resting heart rates. AI collects this data to determine if current rate or rhythm control strategies are effective or if medication adjustments are required.

Best Practices
  • Ask patients to check their heart rate via wearable if available
  • Screen for nocturnal symptoms specifically
Common Pitfalls
  • Ignoring subtle fatigue as a sign of poorly controlled AFib
5

Post-Ablation Recurrence Tracking

Specialized follow-up for post-ablation patients to detect early recurrence and ensure proper transition of anticoagulation therapy during the critical blanking period and beyond.

Best Practices
  • Focus on the first 90 days post-procedure
  • Ensure patients know the difference between the blanking period and recurrence
Common Pitfalls
  • Discontinuing anticoagulation too early without a repeat score
6

Risk-Based Clinical Triage

The system categorizes patients into high, medium, or low risk based on recent data, routing high-risk alerts directly to the electrophysiology team while scheduling routine follow-ups for stable patients.

Best Practices
  • Define clear thresholds for clinical escalation
  • Use color-coded dashboards for rapid review
Common Pitfalls
  • Overwhelming clinicians with alerts for stable, low-risk patients

Expected Outcomes

1

Reduction in AFib-related stroke incidents

2

Improved MIPS quality measure scores for anticoagulation

3

Increased APCM enrollment and reimbursement revenue

4

Higher patient adherence to DOAC and Warfarin regimens

5

Reduced clinician burnout through automated data collection

Frequently Asked Questions

AI call agents systematically query patients for new health events like hypertension diagnosis or vascular disease, updating the score in real-time for clinician review.

Yes, the system tailors questions based on whether the patient is on a DOAC (adherence focus) or Warfarin (INR monitoring and diet focus).

Tile’s AI platform captures patient responses and risk scores, formatting them into structured notes that can be imported directly into patient charts for APCM documentation.

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AFib Chronic Care Risk Stratification Workflow | Tile Health