Second-Level Review for Risk Adjustment
Natural language processing in healthcare supports clinical decisions and coding accuracy, but not all NLP engines are created equal.

Second-Level Review for Risk Adjustment

Natural language processing in healthcare supports clinical decisions and coding accuracy, but not all NLP engines are created equal.

Why Artificial Intelligence and Natural Language Processing (NLP) in Healthcare are Indispensable

Is 95% Coding Accuracy Good Enough?

With increasing financial pressures and compliance audits from OIG and CMS, even health plans with 95-98% coding accuracy may be putting themselves at risk. In an era of uncertainty, health systems and healthcare providers are exploring technologies to decode medical records and deliver real time insights to improve the patient experience.

Natural language processing (NLP) can be used to support clinical decision making for providers looking for point of care solutions that simplify complex patient information. When it comes to coding accuracy, NLP and machine learning can be used to automatically extract risk factors associated with a medical record and help prioritize the most impactful add and delete codes.

Like any technology, NLP tools have their advantages and differences, so it is important to understand the challenges of integrating NLP technologies into a clinical care program. Many NLP applications intend on bringing order to unstructured data, but still many fall short.


Limitations of NLP in Healthcare:

  • Trained on a limited dataset
  • Poorly designed UI
  • Lack of human coder validation


Artificial Intelligence Meets Human Expertise

An effective NLP tool for second level coding review combines targeted machine learning capabilities with the power of real human coders. Which is why Episource developed a proprietary AI smart-engine that is trained by the industry’s largest bench of full-time coders who code over 10 million charts each year.

Now, healthcare providers and health systems can ensure full coding accuracy and compliance—all in a single SaaS platform.

EpiFinalCheck by Episource combines the power of best-in-class NLP technology with expert HCC coders to ensure an accurate and cost effective review of medical records.

Adhere to Regulatory Guidelines

Prioritize Interventions with the Right Adds and Deletes

Combine Machine Learning with Human Intelligence

Integrate with Multiple Data Files and Formats

Improve Coding Accuracy

Harness the power of advanced NLP to automatically detect errors missed by prior audits, which are then validated by expert coder review.

Reduce Compliance Risk

Designed to target coding errors that lead to financial and compliance risk. All NLP findings are subject to 100% QA, ensuring compliance with health plan and CMS guidelines.

Increase Program Transparency

Receive a net-impact assessment of your second level review and an independent coding accuracy assessment of your first level review, providing complete transparency into the value of new codes captured or removed.

Reduced Project Timelines

Scalable to quickly onboard new clients and handle large volumes of data, decreasing the time needed to complete projects vs. traditional chart audits while maintaining high-quality results.

Simplified Workflows

Receive a curated list of only the codes that need to be added or deleted, saving the time and effort of comparing codes from vendor to vendor and from coding to claims. Improve the accuracy of your coding program and reduce compliance risk with epiFinalCheck second-level review today.


We simplify the management of member programs by making it radically more efficient, and increasing value to healthcare organizations and their members

Dec. 2nd Webinar on Retrospective Strategies to Optimize Risk Scores w/o Causing Provider Abrasion