INTUS REVENUE INTEGRITY SYSTEM - IRIS

A risk adjustment system harnessing Natural
Language Processing (NLP), built for PACE to empower proactive and compliant workflows

PROACTIVE
AI-DRIVEN HCC CODING

Support your providers by surfacing prospective condition codes for review during assessments. Using NLP and certified risk adjustment coders, our solution identifies relevant conditions. Ensuring precise documentation and improved outcomes. 

Providers are prepped prior to all encounters

Ongoing provider education to improve notes for coding accuracy

Monthly generation of CMS submission file for streamlined submission to CMS

Pre-encounter preparation ensures that providers address all relevant conditions during each encounter

Timely coding and submission ensures that revenue is accurate in each payment period

Analytics allows finance teams to address payment inaccuracies each month

ENHANCED CODE CAPTURE ACCURACY

Partner with our team of certified, onshore coders to ensure all condition codes are accurately captured and documented. With a focus on precision, IRIS empowers you to leverage expert coding support, enhancing the accuracy and completeness of your coding processes. 

ENHANCED
REIMBURSEMENT
ACCURACY

With a focus on accurate coding and documentation, IRIS optimizes revenue capture by ensuring compliance with reimbursement requirements.

Pre-encounter preparation ensures that providers address all relevant conditions during each encounter

Timely coding and submission ensures that revenue is accurate in each payment period

Real-time analytics allows finance teams to address payment inaccuracies each month

CONTINUOUS
PERFORMANCE
MONITORING

IRIS delivers actionable insights into revenue cycle data, identifying re-coding opportunities and predictive conditions. This process is repeated multiple times per year, ensuring ongoing accuracy in risk adjustment and optimized incoming revenue.

Revenue Integrity Analytics

Breakdown and summarize key payment details from your CMS files

Identify revenue and submission gaps as well as missed coding opportunities

100% census completed twice a year

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