Workflow GuideTile Health vs ChartSpan

APCM EHR Documentation: Tile Health vs ChartSpan Guide

Compare APCM EHR documentation workflows between Tile Health's AI automation and ChartSpan's human care coordinators to optimize your practice's CCM billing.

Navigating Advanced Primary Care Management (APCM) requires meticulous documentation to ensure reimbursement and compliance. While ChartSpan relies on human care coordinators to manually enter notes into your EHR, Tile Health utilizes AI-driven automation to capture patient interactions and clinical data in real-time. This guide breaks down the workflow differences and how AI impacts documentat...

The Challenge

Practices often struggle with the latency and inconsistency of human-driven documentation provided by traditional vendors like ChartSpan. Manual entry leads to billing gaps, increased overhead for care coordinators, and difficulty scaling APCM services without sacrificing data integrity or patien...

Step-by-Step Workflow

1

Patient Eligibility and Enrollment Identification

Tile Health uses AI to scan EHR records for APCM eligibility, flagging patients automatically. ChartSpan typically requires manual review of patient lists by human care coordinators, which can delay enrollment cycles.

Best Practices
  • Use automated filters to identify high-risk patients first
  • Verify BAA compliance before AI data scanning
Common Pitfalls
  • Relying on outdated manual spreadsheets for enrollment
  • Missing eligible patients due to human oversight in list reviews
2

Initial Care Plan Generation

Tile Health's AI generates a structured care plan draft based on clinical data for provider approval. In the ChartSpan model, a human coordinator must interview the patient and manually draft the plan, often taking 30-45 minutes.

Best Practices
  • Standardize care plan templates for consistent AI output
  • Ensure providers review and sign off on AI-generated drafts
Common Pitfalls
  • Allowing human coordinators to finalize plans without clinical oversight
  • Failing to update care plans monthly
3

Real-Time Interaction Logging

As the AI handles patient calls for Tile Health, it transcribes and categorizes clinical notes instantly. ChartSpan's coordinators must take notes during or after calls, which can lead to 'note bloat' or missing critical details.

Best Practices
  • Enable real-time transcription for better accuracy
  • Use NLP to highlight medication changes automatically
Common Pitfalls
  • Waiting until the end of the day to document patient calls
  • Using non-standardized shorthand in EHR notes
4

Automated Time Tracking for Billing

Tile Health logs every second of AI-patient interaction with millisecond precision for APCM billing. ChartSpan relies on coordinators manually starting and stopping timers, which often results in under-reporting billable time.

Best Practices
  • Audit time logs weekly to ensure billing thresholds are met
  • Ensure the system distinguishes between clinical and non-clinical time
Common Pitfalls
  • Rounding up time manually, which risks audit failure
  • Forgetting to log time spent on care coordination outside of calls
5

Bi-Directional EHR Synchronization

Tile Health utilizes native APIs to push documentation directly into the patient chart. ChartSpan often uses a portal or batch uploads, requiring practice staff to manually move data into the primary EHR system.

Best Practices
  • Test API connectivity for all EHR modules
  • Schedule syncs to occur immediately after patient interaction
Common Pitfalls
  • Maintaining a separate siloed database for CCM data
  • Delayed data entry leading to clinical data fragmentation
6

Compliance Audit Trail Preparation

AI systems provide an immutable log of all actions taken, making audits seamless. Human-led models require manual reconciliation of call logs, notes, and billing codes to prove APCM compliance.

Best Practices
  • Keep a digital paper trail for every automated interaction
  • Review documentation for HIPAA and APCM regulatory compliance
Common Pitfalls
  • Lacking a clear link between documentation and the billed code
  • Failing to store call recordings or transcripts

Expected Outcomes

1

90% reduction in documentation lag time compared to human models

2

100% accuracy in billable time tracking for APCM codes

3

Seamless bi-directional EHR data flow without manual entry

4

Significant reduction in cost-per-patient through AI automation

5

Improved audit readiness with immutable digital logs

Frequently Asked Questions

Tile Health uses advanced Natural Language Processing (NLP) to categorize data instantly into structured fields. ChartSpan relies on human interpretation, which can lead to variability in how different coordinators document the same clinical issue.

Tile Health is significantly more cost-effective. By replacing human labor with AI automation, practices avoid the high overhead costs associated with ChartSpan's large staff of care coordinators.

Yes, Tile Health typically offers deeper API-level integration for real-time updates, whereas ChartSpan often relies on manual workarounds or external portals that require extra steps for your clinical team.

AI provides instant responses and 24/7 availability, eliminating the hold times and scheduling delays common with ChartSpan's human-staffed call centers.

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APCM EHR Documentation: Tile Health vs ChartSpan Guide | Tile Health