Workflow GuideValue-Based Care

Chronic Care Monthly Check-In: VBC Optimization Guide

Optimize your Value-Based Care strategy with a standardized chronic care monthly check-in workflow to improve quality metrics and shared savings.

Transforming chronic care management from a billing task into a value-based care engine requires a standardized monthly check-in workflow. This guide outlines how to leverage AI-powered outreach to close care gaps, improve HEDIS scores, and drive shared savings through proactive APCM engagement and population health oversight.

The Challenge

Manual outreach for chronic care check-ins is labor-intensive, leads to inconsistent documentation, and often misses critical care gaps, resulting in lost shared savings and poor performance on VBC quality metrics due to fragmented patient communication.

Step-by-Step Workflow

1

Data-Driven Patient Identification

Utilize AI to scan EHR records and population health tools to identify patients with chronic conditions requiring a monthly check-in based on their risk score, last contact date, and outstanding care gaps.

Best Practices
  • Integrate with population health software for real-time risk stratification
  • Prioritize patients with rising risk scores to prevent acute episodes
Common Pitfalls
  • Relying on manual spreadsheets that become outdated quickly
  • Ignoring patients who are historically non-compliant with office visits
2

Automated Engagement and Screening

Deploy AI-powered call agents to initiate the monthly check-in, using natural language to verify medication adherence and screen for new symptoms or changes in social determinants of health (SDOH).

Best Practices
  • Use natural language processing to ensure an empathetic patient experience
  • Schedule calls during hours when patients are most likely to answer
Common Pitfalls
  • Using overly clinical or robotic scripts that discourage patient engagement
  • Failing to ask open-ended questions about symptom progression
3

Real-Time Care Gap Identification

During the automated call, the AI cross-references the patient's record to identify missing HEDIS measures or overdue screenings, prompting the patient to schedule necessary preventative services immediately.

Best Practices
  • Focus on high-impact HEDIS gaps like A1c checks or colonoscopies
  • Provide immediate scheduling options during the call
Common Pitfalls
  • Ignoring SDOH barriers such as transportation that prevent gap closure
  • Missing the opportunity to address multiple gaps in a single touchpoint
4

Clinical Escalation and Triage

If the patient reports clinical instability, medication side effects, or specific red flags, the AI immediately routes the call to a nurse or schedules a priority telehealth visit to prevent ER utilization.

Best Practices
  • Establish clear clinical triggers for immediate nurse intervention
  • Ensure the AI can distinguish between routine updates and urgent needs
Common Pitfalls
  • Delayed response to acute symptoms reported during the check-in
  • Failing to document the reason for escalation in the clinical note
5

Structured Risk Adjustment Documentation

The workflow captures structured data on chronic condition status and severity, ensuring accurate HCC coding and risk adjustment for VBC contracts to reflect the true complexity of the patient panel.

Best Practices
  • Train AI to prompt for status updates on all active chronic conditions
  • Ensure documentation supports M.E.A.T. criteria for coding
Common Pitfalls
  • Vague documentation that fails to meet audit requirements
  • Focusing only on the primary diagnosis while ignoring comorbidities
6

Automated EHR Integration and Billing

The interaction is summarized and pushed to the EHR, capturing the non-face-to-face time spent for APCM/CCM billing and quality reporting requirements without requiring manual data entry from staff.

Best Practices
  • Automate the calculation of time spent to ensure billing compliance
  • Use standardized templates for easy retrieval during VBC audits
Common Pitfalls
  • Failing to log the specific minutes spent on care coordination
  • Manually transcribing call notes, which introduces errors and burnout

Expected Outcomes

1

Increased HEDIS measure compliance and care gap closure rates across the population.

2

Improved HCC coding accuracy and higher Risk Adjustment Factor (RAF) scores.

3

Reduced total cost of care through proactive monitoring and ER diversion.

4

Higher shared savings through optimized MSSP and ACO quality performance.

5

Enhanced patient satisfaction and engagement with the primary care home.

Frequently Asked Questions

Advanced Primary Care Management (APCM) provides a recurring revenue stream while establishing the proactive monitoring necessary to reduce hospitalizations and meet VBC quality targets.

Yes, AI agents are trained on clinical protocols to identify red flags, assess medication adherence, and ensure all VBC-required data points are collected consistently across the patient panel.

Standardized monthly check-ins ensure that preventative screenings and chronic management metrics are documented in real-time, directly boosting MIPS and ACO quality scores for shared savings.

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Chronic Care Monthly Check-In: VBC Optimization Guide | Tile Health