Workflow GuideMEDITECH

MEDITECH Chronic Care Risk Stratification Workflow

Optimize chronic care risk stratification in MEDITECH Expanse. Learn to automate APCM outreach and improve community hospital population health outcomes.

For community and critical access hospitals using MEDITECH, effective risk stratification is the foundation of a successful Advanced Primary Care Management (APCM) program. This workflow outlines how to leverage MEDITECH Expanse data alongside AI-powered automation to identify, categorize, and engage high-risk chronic patients who require intensive longitudinal support.

The Challenge

Manual risk stratification in MEDITECH often fails due to fragmented data between acute and ambulatory modules, leading to missed APCM revenue and poor outcomes for rural populations with high chronic disease burdens.

Step-by-Step Workflow

1

Data Extraction via MEDITECH BCA

Utilize MEDITECH Business and Clinical Analytics (BCA) to pull longitudinal data across the enterprise. Focus on identifying patients with two or more chronic conditions listed in the Problem List that have been active for at least 12 months.

Best Practices
  • Cross-reference Inpatient and Ambulatory problem lists
  • Filter by primary care provider assignment
Common Pitfalls
  • Ignoring inactive status codes that may still require APCM intervention
2

ICD-10 Condition Mapping

Map extracted diagnosis codes to CMS-approved APCM categories. Ensure that older codes from legacy MEDITECH 6.x or Magic systems are correctly cross-walked to current Expanse ambulatory standards for accurate reporting.

Best Practices
  • Automate the mapping of HCC scores to patient records
  • Update the Ambulatory Chronic Care Management (CCM) module
Common Pitfalls
  • Failing to update problem lists during annual wellness visits
3

Utilization and SDOH Analysis

Analyze ED visit frequency and inpatient admissions within the MEDITECH Patient Care System (PCS). Integrate Social Determinants of Health (SDOH) data to identify rural patients with transportation or access barriers.

Best Practices
  • Use the MEDITECH SDOH assessment tool for risk weighting
  • Weight ED frequent flyers higher in the stratification tier
Common Pitfalls
  • Overlooking patients with high medication non-adherence flags
4

AI-Powered Eligibility Outreach

Deploy AI call handling to contact the high-risk cohort identified in Step 3. The AI handles initial outreach, explains APCM benefits, and confirms patient consent, updating the MEDITECH record automatically without nurse intervention.

Best Practices
  • Configure the AI to handle common rural health questions
  • Ensure the AI logs the call duration for documentation
Common Pitfalls
  • Using manual calling for large rural patient populations
5

APCM Enrollment and Flagging

Mark eligible and consenting patients in the MEDITECH Ambulatory module using a specific 'APCM Enrolled' status flag. This trigger ensures that all subsequent clinical documentation contributes to the required monthly care management minutes.

Best Practices
  • Set up automated alerts for the care coordination team
  • Link the flag to the billing workqueue
Common Pitfalls
  • Failing to update the 'Consent Obtained' field in MEDITECH
6

Billing Configuration (BAR)

Configure the MEDITECH Billing and Accounts Receivable (BAR) module to separate professional APCM fees from hospital facility charges. This is critical for Critical Access Hospitals (CAH) to ensure proper cost-based reimbursement.

Best Practices
  • Test the G-code triggers in a sandbox environment
  • Verify the NPI associated with the ambulatory provider
Common Pitfalls
  • Double-billing facility and professional fees for the same encounter

Expected Outcomes

1

Increased APCM enrollment rates through automated AI outreach

2

Improved HCC coding accuracy within MEDITECH Expanse

3

Reduction in ED readmissions for the high-risk chronic cohort

4

Streamlined billing workflows for community hospital professional fees

Frequently Asked Questions

Yes, though data extraction requires custom NPR or RD reports rather than the standard Expanse BCA tools. AI call handling can bridge the gap by collecting data externally and feeding it back via HL7 interfaces.

The AI can check the MEDITECH Ambulatory schedule in real-time to book follow-up chronic care visits for patients who show high-risk indicators during the stratification call.

Expanse offers basic population health reporting, but it often requires manual configuration to align with specific APCM requirements and rural health SDOH factors.

The workflow uses MEDITECH BAR configuration to ensure APCM codes are tied to the professional fee schedule, preventing conflicts with inpatient DRG or facility billing.

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MEDITECH Chronic Care Risk Stratification Workflow | Tile Health