How Our Platform Solves Healthcare Reporting Challenges

Revolutionary methodology using FHIR-native data validation, local monitoring tools, and open standards to eliminate manual processes and prevent multi-million dollar losses.

How Healthcare Reporting Works Today

Manual processes, proprietary formats, and delayed feedback create massive inefficiencies

Legacy Workflow Problems

1

Manual Chart Abstraction

Staff spends 200+ hours/month manually reviewing charts for HEDIS measures

2

Quarterly Batch Processing

6-month delay before seeing HEDIS performance—too late to intervene

3

Proprietary Vendor Formats

Locked into vendor-specific formats, high switching costs, no data portability

4

Validation at Submission

Data errors discovered AFTER submission deadline—too late to fix

Result: $375M losses like Elevance, $1-3B impacts like Humana

Our Revolutionary Approach

1

Automated FHIR Integration

HL7 FHIR R4/R5 pulls chart data automatically—zero manual abstraction

2

Real-Time Processing

Sub-200ms calculations after every patient encounter—instant visibility

3

Open Standards (FHIR/HL7)

Zero vendor lock-in, portable data, works with any FHIR-compliant EHR

4

Validation at Rest

FHIR queries validate data quality BEFORE calculation—early error detection

Result: Prevent losses, save $2.5M annually, 40+ hours/month saved

Our 5-Step Technical Validation Workflow

How we ensure data quality and prevent submission errors

FHIR Data Flow Pipeline

EHR System

Epic, Cerner, Meditech

FHIR API

R4/R5

HAPI Server

146 Resources

42-Point Validation

Real-time data quality checks

Citus Database

3 Regional Workers

HEDIS Engine

<100ms

Provider Dashboard

Real-time alerts

Open Standard

FHIR R4/R5 - works with any EHR

Real-time Validation

42 checks before calculations

Sub-100ms Speed

Instant HEDIS results

Step 1: FHIR Integration

Connect to your EHR via HL7 FHIR R4/R5 standard. Supports Epic, Cerner, Meditech, and 200+ healthcare systems. Real-time bidirectional sync pulls patient data automatically.

GET /fhir/Patient?_lastUpdated=gt2024-01-01&_count=1000

Step 2: Data Validation at Rest

FHIR queries validate data quality BEFORE calculations. Check for missing demographics, invalid codes, incorrect date ranges, and provider credentials.

GET /Observation?code=4548-4&date=ge2024-01-01&_include=Patient

Validates HbA1c tests with patient demographics

Step 3: Real-Time HEDIS Calculation

PostgreSQL functions execute HEDIS measure logic in <200ms. Results update instantly after each patient encounter—no batch processing delays.

SELECT calculate_hedis_measure('CDC', 'HbA1c_Test', '2024', organization_id);

Step 4: Local Monitoring Validation

Run validation scripts on-premise to verify platform integrity. You control the quality assurance—no vendor dependency.

./scripts/validate-production.sh # 42 checks, 100% pass rate

Step 5: NCQA Submission Ready

One-click export generates NCQA-formatted files with zero errors. Automated validation guarantees submission acceptance.

export_ncqa_submission('2024', 'all_measures') → hedis_2024_validated.xml

Why Our Methodology Works

Data Quality Assurance

FHIR queries validate data at rest—catch errors BEFORE the submission deadline, not after it fails.

Learn About FHIR Validation

Local Control

Run validation scripts on-premise. You verify platform accuracy—not dependent on vendor claims.

See Monitoring Tools

Zero Vendor Lock-in

Open FHIR/HL7 standards mean your data is portable. Switch vendors anytime—no proprietary formats.

Compare to Legacy Systems

Ready to Transform Your Healthcare Reporting?

See how FHIR-native validation and local monitoring tools prevent multi-million dollar losses

Request Technical DemoView Architecture