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What is Risk Adjustment Data Validation (RADV)?

What is Risk Adjustment Data Validation (RADV)?

Learn why your medical coding skills are more important than ever.

Simply stated, RADV is a course of action that allows the Centers for Medicare & Medicaid Services (CMS) to perform audits on patients’ medical records to verify diagnosis codes that are tied to hierarchical condition categories (HCCs). HCC codes are submitted for payment to all issuers participating in the individual and small group markets, both inside and outside of the exchange. The goal of this process is to eliminate premium differences among health plans based solely on favorable or unfavorable risk selection.

RADV is only one portion of the risk adjustment umbrella that a health plan utilizes for tracking and trending purposes. The results of the RADV process can help health plans better aid their member population by providing wellness programs geared toward specific health conditions. Not only can insurance companies utilize the results for member assistance, but the results can aid in collaboration between the provider and payer through a shared patient.

Follow Protocol

Per the CMS RADV protocols, there are six pieces to the RADV process:

  1. CMS creates a sample of a health plan’s enrollee records for audit.
  2. The health plan must select an initial validation auditor to audit demographic and enrollment data, prescription drug categories (RXCs), and health status data submitted on the health plan’s External Data Gathering Environment (EDGE) server for the selected sample enrollees.
  3. A second validation auditor performs a quality assurance audit on a subsample of the initial validation auditor’s data to verify the accuracy of the findings.
  4. CMS performs error estimations and calculates the health plan’s risk score error rates using the failure rate of each HCC.
  5. CMS administers the second validation audit findings attestation and discrepancy reporting process, the error rate attestation and discrepancy reporting process, and an administrative appeals process.
  6. Final results are used to adjust the risk adjustment risk scores and transfers.

What does this process look like through the eyes of the insurance company? RADV is a year-round process, focused on the following timeline:

  • October 1 – April 30: EDGE server data submission.
  • January – March: Health plans contract with an initial validation auditor.
  • Mid-May – June 30: CMS provides health plans with the selected sample enrollees.
  • June – December: Health plans work with their initial validation auditor to validate claims with medical records.
  • November – mid-January: Initial validation auditors submit documentation on behalf of the health plans via Package 1, Package 2, and (if needed) Package 3.

Each portion is important, but submitting correct claims to the EDGE server and ensuring the provider’s documentation supports the claim being submitted make the biggest impact on a health plan.

Prepare for RADV Audits

The RADV audit allows the health plan to get a better understanding of the population’s health, as well as how the providers are billing.

In general, CMS will provide a health plan a sample of 200 members targeted to audit. Out of the 200 members, only two-thirds of the members (those tied to an HCC) are truly utilized for the RADV audit. The remaining third is not tied to an HCC, which does not hinder or help the calculation of the health plan’s overall risk score. This leaves the health plan with roughly 134 members to audit.

Health plans may choose to allow the initial validation auditor to conduct the retrieval portion, or they may choose to take a more hands-on approach by conducting the retrieval portion themselves. This approach gives a health plan the opportunity to do a precursor audit using their own coders. Either way is fine, but a health plan can gain a significant amount of knowledge about their providers and members, and save on operating costs, when they work with the data. Like any auditing process, data is vital in bettering practices and, specifically in this case, coding practices.

Coding Is Key to Success

Provider offices play a massive role in the success of a health plan’s RADV audit, but they truly impact the member more with their coding practices. For example, let’s say a provider office submits a claim with diagnosis code E08.21 Diabetes mellitus due to underlying condition with diabetic nephropathy (tied to HCC 20; the highest HCC in its group), but the medical record supports diagnosis code E08.9 Diabetes mellitus due to underlying condition without complications (tied to HCC 21; the lowest HCC in the group). The result drastically changes the risk score for the patient, which ultimately changes the overall risk score for the health plan. Even though the health plan’s risk score is affected, the member is impacted significantly more because a true picture of their health is not accurately reflected. This patient’s care is hindered further when other providers care for the patient. Missing pieces in the documentation create mistreatments and misdiagnoses.

By utilizing the RADV findings, a health plan can easily use the data to identify trends. These simple, finite numbers are easy to monitor via the reports CMS and initial validation audits provide to the health plan. Healthcare is a world of teamwork with a mutual goal of ensuring the care of the patient. RADV can facilitate better outcomes for patients, providers, and health plans. Go team healthcare!

Cara Wentland
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Cara Wentland, CPC, is a quality review coder at Physicians Health Plan of Northern Indiana in Fort Wayne, Ind. Working within the Quality Department, she retrieves and audits medical records for HEDIS compliance and risk adjustment projects. Wentland also plays a key role in the company’s URAC accreditation process. She is a member of the Fort Wayne, Ind., local chapter.

One Response to “What is Risk Adjustment Data Validation (RADV)?”

  1. Tricia Slone says:

    Good article! I clicked on it because I’m interested in HCC coding and then it was nice to see the author is from my home town 🙂

    Thank you