Canada
Puerto Rico
USA
Belgium
France
UK
India
Client Background
The client is a mission-driven, non-profit healthcare provider providing quality and affordable coverage across retail, Medicaid, and Medicare lines.
Client Need
The client faced challenges with the following:
Difficulty in processing encounters within CMS-RAPS and EPDS, including handling supplemental data from post-adjudicated claims
Analyzing star rating measures and effectively improving care management and interventions for high-risk patients
Inadequate risk adjustment system to handle supplemental data from chart reviews
Excessive time spent on patient medical chart reviews with potential accuracy issues
Solution
Our experts implemented the following solutions to address the challenges:
Automated Regulatory Reporting: Implemented a system to ensure the seamless and accurate transmission of all encounter data variations, including standard, void, and adjusted encounters, from the payer system to CMS
Data-driven care Management: Leveraged Model Output Reports (MOR) to pinpoint Hierarchical Condition Categories (HCC) care gaps, enabling the development of targeted interventions for at-risk patients
Maximized Risk Adjustment Revenue: Developed a system for conducting retrospective chart reviews based on suspected member details and facilitated accurate linked and unlinked claims submissions to CMS
Transition to Value-Based Payment Models: Analyzed current provider reimbursement processes and provided a detailed implementation strategy for episode-of-care to treat Asthma, COPD, Heart Failure, Upper Respiratory Infection
Enhanced Data Accuracy: Implemented Optical Character Recognition (OCR) technology to automate extracting relevant medical information from scanned charts to pass through the Natural Language Processing (NLP) engine
Realized Benefits
The solutions implemented yielded the following outcomes:
Increased CMS EDPS acceptance rate by 5% and accurately reconciled RAPS and EDPS responses
Enabled the client to target high-risk populations prospectively, managed care 50% more effectively, and improved ratings for their plans
Improved the year-on-year average risk adjustment capitation rate by over 5%
Enhanced the quality of care for patients and saved over $1.6 million in payments to provider groups in the year of implementation
Reduced manual review efforts by 20% and dramatically improved reporting accuracy
Tools & Technologies
HYE
Microsoft SQL Server
Information Builders WebFOCUS
Greenplum Database
Microsoft .NET Framework
IBM Infosphere DataStage
Mongo DB
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