Second-Level Review (2LR) Strategies to Mitigate Risk on Final Submission to CMS

The Centers for Medicare and Medicaid Services (CMS) has focused on Risk Adjustment data submissions for many years with Risk Adjustment Data Validation (RADV) audits.  The Office of Inspector General (OIG) has been in collaboration with CMS to conduct additional reviews on the submitted Risk Adjustment data from health plans.  They have most recently been focused around high-risk diagnosis groups with more emphasis on accuracy and substantiation from medical records.  

Data sharing can be most impactful when measuring a patient’s risk score. Collaboration across your organization is critical in order to understand accurate submissions after internal and external audits.  

  1. If one diagnosis exists for the patient through a chart review source and/or a health risk assessment (HRA), it is recommended that 2LR be conducted if this is the only source of the diagnosis.  
  2. If an acute diagnosis is submitted on an outpatient setting where it is required to be managed in an inpatient setting, it is recommended that these diagnoses have a 2LR.  There should be a correlating inpatient stay for the acute condition.
  3. If your organization conducts Diagnosis Related Group (DRG) audits and the findings of these audits change a diagnosis code for the patient, it is recommended to delete the originally submitted code and submit the validated code through a medical record review.
  4. If you have any type of internal audits being conducted that involve changes to an ICD-10 CM code for a patient, it is recommended to follow the correct course of action to ensure your Risk Adjustment program is aware of the need to “delete” and/or “add” the accurate reflection of the patient’s condition.

You can find the most recent report released by the OIG discussing chart reviews and health risk assessments by vising their website at

CMS is focused on Medicare Advantage plans that leverage chart reviews and health risk assessments. They have identified concerns that are utilizing these types of data capture to disproportionately drive payments.

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