MCheck Mcheck Clinical

Deliver AI-Structured Clinical Data for HEDIS, RA, and Care Management Teams

HiLabs’ AI-powered clinical data platform automates ingestion, mapping, validation, and transformation of supplemental files—cutting turnaround time from days to hours and powering a closed-loop system with provider-level data quality scoring

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Delivering contract intelligence every day across health plan operations

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Clinical Records Processed

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Industry Standard Check

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Match Rate to Risk, Quality & Ops File Specs

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From Raw Clinical Files to Clean, Configurable Outputs—in Minutes

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Legacy Process Challenges vs. HiLabs' AI-Powered Solution Advantage

Traditional IT systems can’t keep up with the scale, complexity, or speed variability  required for modern clinical data operations 

Traditional ETL-Based Approach

Rely on static templates and manual rules to interpret files, often breaking when column names or formats change.

Column Mapping & Intake

Validation Logic & Configuration

Operational Visibility

Output Flexibility

Workflow Efficiency

HiLabs

AI Auto-Mapping intelligently assigns clinical concepts—even when files vary between providers or submissions

Column Mapping & Intake

Validation Logic & Configuration

Operational Visibility

Output Flexibility

Workflow Efficiency

Legacy Network Solution Vendors

HiLabs

Rely on static templates and manual rules to interpret files, often breaking when column names or formats change.

AI Auto-Mapping intelligently assigns clinical concepts—even when files vary between providers or submissions

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Why Leading Plans Rely on HiLabs for Clinical Data Ingestion

A configurable AI platform that transforms messy clinical files into clean, validated outputs for Risk, HEDIS, and Care Management—cutting manual effort, improving data quality, and speeding time-to-action for payers.

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How a National Blue Plan Scaled Clinical Supplemental Data Ingestion

From static files, deterministic rules, and continuous data fall outs to an intelligent, closed-loop ingestion engine—streamlining downstream operations and improving submission quality

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$3M+ in Annual Operational Cost Savings

Replaced traditional rules-based workflows with AI-powered ingestion and validation—cutting internal processing costs by over $3M per year.

Turnaround Time Cut from 7 Days to <2 Hours

Reduced average file processing time from a full week to under two hours, accelerating downstream access to structured clinical data.

900+ Data Sources Ingested

From provider-submitted files to EHR extracts, the platform standardized and mapped incoming data from 900+ unique sources—automatically.

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