Medicaid Managed Care: CMS’s Accuracy Check Process For State-Submitted Medical Loss Ratio Data Has Limitations

Report Materials

• Full Report (PDF, 1.8 MB)
• Report Highlights (PDF, 646.5 KB)

Why OIG Did This Review

• Medical loss ratios (MLRs) are an important part of Medicaid managed care fiscal oversight.
• An MLR shows whether a managed care plan spent most of its Medicaid funds on medical costs. Specifically, an 85-percent MLR-the Federal standard-means that a plan spent 85 percent on patient care and quality improvements and 15 percent on administration and profit.
• States must develop their managed care plans' fixed monthly payment rates (hereafter "capitation rates") so that they will reasonably achieve at least 85-percent MLRs.
• This review looks at how CMS verifies the accuracy of State-submitted MLR data. Accurate MLR data helps States set appropriate capitation rates for managed care plans.

What OIG Found

We found limitations in CMS's process to check the accuracy of the MLR data that States are required to submit to CMS. Specifically, we found that:

• CMS performed only limited accuracy checks on the four required MLR data elements, and those checks showed that some State-submitted MLR data may be inaccurate.
• CMS did not follow up with the States that submitted potentially inaccurate MLR data.
• Results of MLR accuracy checks were not shared across CMS staff, and therefore, CMS missed the opportunity for these results to inform its review of managed care plans' capitation rates.

What OIG Recommends

1. CMS should establish procedures that outline the steps to be taken to address potentially inaccurate Medicaid MLR data submitted by States and follow up with States, as needed.
2. CMS should ensure that insights from its reviews of State-submitted Medicaid MLR data are communicated to CMS staff responsible for reviewing plans' capitation rates.
3. CMS should improve the efficiency and effectiveness of its oversight of the accuracy of State-submitted Medicaid MLR data.

CMS concurred with OIG's recommendations.