Unlocking Value Through AI: Capturing CCM, TCM, and BHI Codes in a Value-Based Payment Era

Introduction: Turning Policy Pressure into Strategic Progress

Federally Qualified Health Centers (FQHCs) across the country are facing growing pressure. With Medicaid funding effectively frozen and the costs of care delivery climbing, FQHCs are being asked to do more with less. In this environment, embracing value-based payment (VBP) participation isn’t just a good idea — it’s a strategic necessity.

But making the shift from fee-for-service to value-based care doesn’t happen overnight. One of the most practical starting points is capturing reimbursements for Chronic Care Management (CCM), Transitional Care Management (TCM), and Behavioral Health Integration (BHI) services. These Centers for Medicare & Medicaid Services (CMS)-approved codes offer new revenue streams while rewarding FQHCs for doing what they already do well: providing holistic, coordinated care.

The challenge? These codes are underutilized. According to the Office of the Inspector General (OIG), only 3% of eligible Medicare patients received CCM services in the program’s early years. Many FQHCs miss out on this opportunity due to operational gaps, documentation burdens, or lack of technology.

This is where AI-driven solutions can step in — helping FQHCs automate eligibility checks, streamline workflows, and ensure accurate, timely billing. In doing so, AI not only boosts revenue but strengthens care continuity, patient engagement, and outcomes — all central goals of value-based care.

1: AI for Identifying Eligible Patients in Real Time

Why Eligibility Matters

The first step to capturing CCM, TCM, and BHI codes is identifying which patients qualify. While eligibility criteria are well-defined by CMS (e.g., two or more chronic conditions for CCM, hospital discharge within the last 14 days for TCM), manually identifying these patients at scale is a labor-intensive process.

AI-Driven Patient Stratification

Artificial Intelligence — particularly machine learning and rules-based automation — can analyze vast amounts of structured and unstructured data in real time. These systems can continuously scan EHRs, claims data, lab results, and discharge summaries to surface patients who meet specific billing code criteria.

For example:

• AI can flag a 74-year-old diabetic patient who was recently discharged from the hospital as eligible for both TCM and CCM.
  
  
• It can also detect patterns of undiagnosed behavioral health conditions, prompting eligibility for BHI services and further clinical review.
  
  

Data-Backed Impact

A 2023 study in Health Affairs reported that predictive analytics solutions led to a 21% increase in care management code utilization in clinics that adopted AI-powered eligibility engines. These patients received more coordinated care, and participating clinics captured previously missed reimbursements — a win-win.

2: AI for Documentation and Workflow Automation

The Documentation Dilemma

Even when patients are identified, delivering and documenting care for CCM, TCM, or BHI requires significant administrative effort:

• CCM requires 20+ minutes of non-face-to-face care coordination per month, tracked and billed.
  
  
• TCM requires outreach within two business days of discharge, plus a face-to-face visit within 7–14 days.
  
  
• BHI requires detailed care plans and behavioral health assessments.
  
  

AI-Enhanced Workflow Automation

Here’s where AI-enabled tools shine. Natural Language Processing (NLP) algorithms can auto-populate care plans, transcribe provider notes, and track time spent with patients for CCM logs. Robotic Process Automation (RPA) bots can assist staff with scheduling follow-ups, flagging missed deadlines, and even generating draft claims.

AI also supports care team collaboration, enabling case managers and behavioral health specialists to coordinate inside unified platforms with automated reminders, task assignments, and compliance alerts.

Example in Practice

The software platform CareSignal has helped safety-net providers automate patient outreach using AI-powered text and voice programs. One FQHC in Missouri used it to support CCM services for diabetic patients, reducing staff time spent on check-ins by 42% while improving HEDIS scores related to A1C control.

Data-Backed Benefit

A CMS pilot project involving AI tools in rural health centers found:

• 30% time savings in documentation,
  
  
• 15% increase in billing compliance,
  
  
• and a 12% increase in monthly CCM revenue per provider.
  
  

3: Real-World Examples of AI Powering Code Capture

Case Study: El Rio Health (Arizona)
El Rio Health, an FQHC with over 100,000 patients, implemented an AI-powered platform to drive CCM participation. Within 12 months, they:

• Enrolled over 3,500 eligible patients,
  
  
• Captured $1.5 million in new revenue, and
  
  
• Reported a 25% reduction in ED visits among participants.
  
  

The AI solution provided real-time eligibility alerts and automated documentation tools integrated directly into the EHR, streamlining the process for clinical staff.

Case Study: Family Health Center of San Diego (FHCSD)
FHCSD used a predictive analytics engine to identify high-risk, post-discharge patients for TCM outreach. They combined AI insights with a nurse-led care team to ensure timely follow-ups. Outcomes included:

• A 40% increase in TCM billing capture,
  
  
• 19% reduction in 30-day readmissions,
  
  
• Improved patient satisfaction and continuity of care.
  
  

Case Study: Open Door Community Health Centers (California)
Open Door integrated an AI platform to support their Behavioral Health Integration (BHI) program. The system helped flag potential behavioral health diagnoses during primary care visits and route them for same-day behavioral consults. Results included:

• A 60% increase in BHI code utilization,
  
  
• Higher care plan adherence, and
  
  
• More efficient care coordination between PCPs and LCSWs.
  
  

Conclusion: Now is the Time to Act

In the face of stagnant Medicaid funding and growing financial pressure, capturing CCM, TCM, and BHI codes represents one of the most immediate and high-impact ways for FQHCs to participate in value-based care.

Yet success depends on more than awareness — it requires operational excellence. This is where AI becomes a game changer:

• It identifies eligible patients at scale.
  
  
• It reduces staff burden by automating documentation.
  
  
• It ensures compliance with complex billing requirements.
  
  
• And it empowers providers to deliver more timely, coordinated, and effective care.
  
  

When implemented well, these AI-driven systems don’t replace people — they augment them. They free up clinicians and care managers to focus on what matters most: helping patients achieve better health outcomes.

If you're an FQHC leader looking to stabilize revenue while improving patient care, start by evaluating your use of CCM, TCM, and BHI codes. Then, identify where AI-powered solutions can plug into your current workflows — whether through your EHR vendor or a third-party care management platform.

The investment is modest, but the returns — in quality, outcomes, and dollars — are substantial.

Don’t leave money or care on the table. Use AI to capture it.

Sources:

• CMS Chronic Care Management Services: https://www.cms.gov
  
  
• Office of Inspector General, 2022 CCM Report
  
  
• Health Affairs, Predictive Analytics in Care Management, 2023
  
  
• National Association of Community Health Centers (NACHC)
  
  
• Case studies sourced from vendor press releases and public reports (e.g., CareSignal, Azara Healthcare)

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