Workflow GuideTile Health vs ChartSpan

Chronic Care Risk Stratification: Tile Health vs ChartSpan

Compare Chronic Care Management risk stratification workflows between Tile Health's AI automation and ChartSpan's human-staffed service model.

Managing a Chronic Care Management (CCM) program requires precise risk stratification to prioritize high-risk patients. While ChartSpan relies on human care coordinators to manually review charts and call patients, Tile Health utilizes AI-driven automation to analyze data in real-time, offering a more scalable and cost-effective approach to patient prioritization and intervention.

The Challenge

Traditional CCM models like ChartSpan struggle with scaling risk stratification due to high costs and human error associated with manual chart reviews. Practices face delays in identifying rising-risk patients, leading to missed intervention opportunities and inconsistent care delivery.

Step-by-Step Workflow

1

EHR Data Ingestion and Synchronization

Connect your CCM platform to the EHR for data harvesting. While ChartSpan often relies on manual exports or batch HL7 feeds, Tile Health uses deep API integration to pull real-time clinical data for immediate AI analysis.

Best Practices
  • Ensure your BAA covers AI data processing
  • Verify EHR compatibility for real-time syncing
Common Pitfalls
  • Relying on monthly batch exports which delay risk identification
2

Automated Patient Identification

Tile Health's AI scans the entire patient roster against CMS eligibility criteria and specific risk factors. Unlike ChartSpan's human-led identification, this happens instantly across thousands of records without increasing administrative overhead.

Best Practices
  • Define specific ICD-10 codes for automated flagging
  • Set custom risk thresholds based on practice demographics
Common Pitfalls
  • Allowing human coordinators to manually cherry-pick patients based on ease rather than clinical risk
3

Dynamic Risk Scoring

Apply algorithms to rank patients based on recent ER visits, medication changes, and social determinants. Tile Health updates scores daily, whereas ChartSpan’s human model often updates scores only during scheduled monthly check-ins.

Best Practices
  • Integrate SDOH data for a holistic risk view
  • Automate alerts for sudden score spikes
Common Pitfalls
  • Using static risk scores that do not account for acute clinical changes between human calls
4

AI-Powered Status Verification

Tile Health initiates AI voice outreach to stratified patients to gather current health status. ChartSpan requires a human coordinator to find time in their schedule, often resulting in lower touch-points for moderate-risk patients.

Best Practices
  • Use AI to handle routine check-ins
  • Reserve human staff for high-complexity clinical escalations
Common Pitfalls
  • Over-relying on human phone tag which delays urgent patient engagement
5

Clinical Intervention Escalation

When Tile Health's AI detects a high-risk symptom during automated outreach, it immediately alerts the clinical team. In the ChartSpan model, this depends entirely on the coordinator's ability to reach the patient and document the finding correctly.

Best Practices
  • Configure instant SMS or dashboard alerts for providers
  • Standardize escalation protocols for specific symptoms
Common Pitfalls
  • Failing to define a clear hand-off from the AI system to the primary care provider
6

Automated Documentation and Compliance

Tile Health automatically logs all interactions and risk updates into the EHR for APCM/CCM billing. ChartSpan coordinators must manually document their calls, which increases the risk of non-compliance or missed billing minutes.

Best Practices
  • Review AI-generated logs for billing accuracy
  • Ensure all time-based activities are captured automatically
Common Pitfalls
  • Inconsistent documentation of non-face-to-face time across different human coordinators

Expected Outcomes

1

90% reduction in manual chart review time for administrative staff

2

Faster identification of high-risk clinical escalations compared to human models

3

Significant decrease in cost-per-patient through AI automation

4

Improved consistency in risk scoring across the entire patient population

5

Higher patient engagement rates through consistent, automated outreach

Frequently Asked Questions

Tile Health's AI analyzes 100% of patient data daily without fatigue, whereas ChartSpan's coordinators are limited by their caseload capacity and manual review speed.

Yes, Tile Health maintains full HIPAA compliance and signs a BAA, ensuring all automated data analysis and patient outreach meet federal security standards.

While human staff handle nuanced emotional support, Tile Health’s AI excels at clinical data processing and consistent monitoring, escalating only the most complex cases to your in-house clinical team.

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Chronic Care Risk Stratification: Tile Health vs ChartSpan | Tile Health