Automate & Prioritize Gap Identification & Remediation
Our solution offers a comprehensive analysis of end-to-end encounter data accuracy to automate and prioritize gaps for remediation. We utilize proprietary algorithms to uncover the primary root causes impacting revenue and compliance, allowing you to resolve issues at the source and prevent future inaccuracies.
All results of our analysis are delivered on our secure, web-based tool with configured reporting to enable speedy resolution and resubmission to CMS in advance of submission deadlines.
Holistic Data Evaluation
- Encounter-level data evaluation identifies where data quality issues exist
- Financial exposure quantification determines the value of data discrepancies and prioritizes remediation
- Root cause investigation allows for resolution of issues at the source
- Web-based platform provides actionable insights into current performance and allows for additional data exploration
- Compliance evaluation identifies potential under- and over-reported encounter submissions
Complexities of the Encounter Data Process
- Data intake from disparate sources: Providers, Clearninghouses, Ancillary Claims, Supplemental Claims
- Processing & Submission: Front End System Edits, Claims Processing System, Electronic Data Warehouse, Regulatory Data Submission Preparation
- Regulatory Processing: State Encounter Reports (Medicaid), RAPS Response (MA), EDS Response (MA), EDGE Response Reports (ACA), HEDIS/Stars Submissions
Why Pareto?
Compliant
We focus on complete and accurate encounter data to mitigate compliance exposure.
Data on Demand
Pareto Hub offers unparalleled access to insights through a ready-to-analyze data environment, enabling users to build independent analytics in a self-service manner.
Flexible
From a one-time diagnostic assessment to full operational evaluation, we offer multiple delivery options, as well as configurable outputs to support specific needs.
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A Powerful Foundation
Our Data Management Platform
Pareto’s Data Management Platform, the foundation to our solutions, is built around data lake, artificial intelligence, and open source big data technologies to allow us to effectively ingest data in all formats and types at scale, organize them with appropriate data governance mechanisms within our data catalog, and provide efficient configuration capabilities to democratize data access and analytics.
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