Analyze
Financial Intelligence That Connects Claims and Revenue
Remitz Analyze turns complex claim and remittance data into clear, actionable insights. Using AI-driven analytics on 835 and 837 EDI files, the platform detects denial patterns, suspected underpayments, and payer performance trends that impact revenue integrity. Designed for both RCM and clinical teams, Analyze reveals where revenue is lost, how performance can improve, and what actions will drive faster, fairer reimbursement.
Parse EDI Claims Automatically
Upload raw 835 and 837 EDI files and let Remitz do the heavy lifting. The system automatically parses headers, line items, payment details, and denial codes—transforming unstructured data into a clean, structured format for faster, more accurate analysis.
Track Every Encounter Across the Revenue Cycle
Gain full visibility from claim submission to final payment. Monitor encounter flow, resubmissions, and lag times to improve your revenue cycle efficiency.
Measure Claim Timelines and Payment Aging
Identify payment delays, monitor aging claims, and optimize follow-up processes to reduce outstanding receivables.
Forecast Revenue Recovery Opportunities
Predict which claims have the highest reimbursement potential using AI-powered models based on historical 835 and 837 data.
Analyze Financial Impact by CPT, DRG, and Payor
Evaluate allowed vs. paid amounts, adjustments, and zero-pay encounters to detect suspected underpayments and possible revenue leakage.
*DRG Analysis Coming Soon
Scale Insights Across Any Organization
From small practices to multi-facility health systems, Remitz scales to meet your data demands. Process large volumes of claim and remittance data with consistent speed, precision, and reliability.
Detect Exceptions and Anomalies in Claims Data
Leverage alert tags for unusual claim sequences, reversals, or high-dollar exposures.
Benchmark Payor and Service Line Performance
Compare payors by payment speed, denial frequency, and adjustment rates. Uncover patterns that influence revenue integrity and compare against peer benchmarks.
Identify Denial and Adjustment Drivers
Drill into CARC and RARC codes to pinpoint denial causes, track adjustment patterns, and prioritize high-impact recovery efforts. Diagnose root causes to prevent future denials.
