New Resource: HCC Tearsheet 2025. Access Now!
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New Resource: HCC Tearsheet 2025. Access Now!
Achieve Unparalleled Coding Accuracy
Utilize our quality review tool to go beyond 95% accuracy and ensure revenue growth.
By leveraging our industry-leading NLP coding engine, Final Check Review automatically identifies codes that were overlooked or unsupported by sufficient evidence during earlier audits by other vendors.
Our vast staff of retrospective risk adjustment coding specialists manually validates each suspected code in accordance with CMS and client criteria. During this procedure, we identify previously missed HCC codes and eliminate any unsupported codes. From complete medical records to potential RAF lift — enjoy all the benefits of accurate risk adjustment coding.
Seamless integration of input files provided by the client.
Our advanced NLP is tuned specifically to highlight potential errors made by the current coding vendor.
Validates coding accuracy through a meticulous examination of coding practices ensuring that codes align with industry standards and compliance requirements.
Provides incremental risk adjustment coding updates based on the NLP audit and coder validation, and conducts ROI analysis to assess the impact of coding changes on overall outcomes.
Compares diagnostic information from the medical record against existing diagnoses received through claims to validate proper coding and identify instances lacking supporting documentation.
Go beyond the industry-standard 95% to ensure accurate clinical documentation
Leverage an advanced NLP engine to assimilate millions of charts each year
Gain complete transparency into the value of new codes captured or removed
Reduce compliance risk with our rigorous QA testing
coding accuracy
per chart average of incremental RAF value obtained
NLP-enhanced coding accuracy
It was really a no-brainer for us to continue to build out our solutions with Episource.
We’ve tremendously increased our efficiency across all solutions for risk adjustment thanks to Episource.
It was really shocking to see how much data corresponded to at least $1 million in revenue for our company. [This] may be a drop in the bucket to some of your larger plans out there, but to a smaller plan like us, that’s very critical.
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