Workflow GuideFQHCs (Federally Qualified Health Centers)

FQHC Chronic Care Risk Stratification Workflow Guide

Optimize FQHC chronic care with our risk stratification workflow. Align PPS reimbursement, HRSA quality measures, and AI-driven patient outreach.

Effective risk stratification is the backbone of high-performing FQHCs. By categorizing patients based on clinical complexity and social determinants of health (SDOH), centers can optimize PPS reimbursement, meet HRSA quality measures, and deploy AI-driven outreach to manage high-risk chronic populations efficiently without increasing administrative overhead.

The Challenge

FQHCs face overwhelming patient volumes and high chronic disease burdens with limited staff. Manual risk scoring often ignores social determinants, leading to missed APCM revenue and poor HRSA compliance while stretching care coordination teams to their breaking point.

Step-by-Step Workflow

1

Data Aggregation & EHR Integration

Consolidate patient data from EHRs, including ICD-10 codes for chronic conditions and UDS reporting metrics. Ensure that all historical PPS visit data is accessible to identify long-term care patterns.

Best Practices
  • Use automated scripts to pull UDS data monthly
  • Verify that ICD-10 codes are specific enough for HCC scoring
Common Pitfalls
  • Ignoring historical claims data from outside the current EHR
2

SDOH Assessment Integration

Incorporate PRAPARE or similar tools to capture social determinants like housing instability and food insecurity into the risk score. These factors are critical for FQHC populations and impact clinical outcomes.

Best Practices
  • Standardize SDOH data collection across all intake points
  • Map SDOH factors to specific community resource referrals
Common Pitfalls
  • Treating SDOH as secondary to clinical data in risk models
3

Automated Clinical Scoring

Utilize AI to analyze longitudinal data, identifying patients eligible for APCM based on multiple chronic conditions and PPS visit history. The AI should flag patients who meet the two or more chronic condition criteria.

Best Practices
  • Weight behavioral health conditions heavily in the score
  • Automate the identification of rising-risk patients
Common Pitfalls
  • Relying on manual clinician review for all risk assignments
4

Multilingual AI Outreach Initiation

Deploy AI voice agents to conduct initial outreach in the patient's preferred language. The AI verifies patient status, assesses immediate needs, and schedules necessary follow-up visits to maintain care continuity.

Best Practices
  • Configure AI for Spanish, Mandarin, and other local dialects
  • Ensure AI outreach occurs during hours convenient for working patients
Common Pitfalls
  • Using English-only automation for diverse FQHC populations
5

Care Coordinator Triage

Route high-risk patients identified by the AI to human care coordinators. This ensures that the most complex cases receive personalized attention while the AI handles routine monitoring for lower-risk tiers.

Best Practices
  • Create clear escalation protocols for the AI
  • Provide coordinators with a dashboard of AI-captured patient insights
Common Pitfalls
  • Overloading coordinators with low-risk patient follow-ups
6

Continuous Monitoring & Re-stratification

Update risk scores monthly based on AI-monitored patient interactions and new clinical data. This maintains APCM documentation compliance and ensures the FQHC captures all available per-patient-per-month revenue.

Best Practices
  • Review risk tiers quarterly for population health trends
  • Align re-stratification with HRSA UDS reporting cycles
Common Pitfalls
  • Static risk scoring that doesn't account for acute events

Expected Outcomes

1

Increased APCM per-patient-per-month revenue on top of PPS

2

Improved HRSA UDS quality measure reporting accuracy

3

Enhanced management of SDOH for underserved populations

4

Reduced administrative burden on clinical staff through automation

5

Higher patient engagement through culturally competent AI outreach

Frequently Asked Questions

APCM provides additional monthly revenue per patient for non-face-to-face care coordination, which is billed separately and does not interfere with the cost-based PPS reimbursement for office visits.

Yes, our AI outreach tools support multiple languages to ensure equitable access and accurate data collection from diverse populations, which is essential for FQHC compliance.

Yes, the documentation generated during risk stratification and AI outreach directly aligns with HRSA quality reporting and clinical oversight standards required for Section 330 grantees.

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FQHC Chronic Care Risk Stratification Workflow Guide | Tile Health