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On June 30th, CMS announced it was enhancing its Program Integrity efforts that focus on addressing improper Medicaid payments and CMS oversight of state Medicaid programs. The announcement introduced 8 initiatives, including stronger audit functions, enhanced oversight of state contracts with private insurance companies, increased beneficiary eligibility oversight, and stricter enforcement of state compliance with federal rules. While CMS has yet to provide any additional detail on implementation or enforcement of the Program Integrity initiatives, we anticipate early focus will be on targeted assessments of Medical Loss Ratio (MLR), capitation rate setting, and beneficiary eligibility determinations.

Fundamental to all of the Program Integrity initiatives announced is improving overall data accuracy within the Medicaid program. As such, states are expected to continue to tighten policy and expectations around data accuracy as it is fundamental to proving Medicaid payments are proper and accurate. States that expanded Medicaid or received a 1115 Medicaid waiver will be likely targets of early CMS focus. With all the changes from Medicaid expansion, work requirements, and category of aid requirements, Managed Care Organizations (MCOs) may experience operational challenges to meeting the stricter requirements.

ADOPTING A COMPREHENSIVE APPROACH TO PROGRAM INTEGRITY

MCOs should use this added emphasis on Program Integrity as an opportunity to reassess their current performance and conduct a diagnostic to understand any potential issues to remediate in advance of any CMS inquiry. A comprehensive view of Program Integrity is necessary. This includes not only looking at fraud, waste, and abuse, but also revenue completeness and potential revenue underpayments—which can be a result of not having complete and accurate risk score documentation or inaccurate categories of aid—as well as the impact on long-term rate setting. Bringing together both analyses into one comprehensive look helps to streamline the process and mitigate discrepancies that can occur when data integrity reviews are performed independently in functional silos.

RAISING THE BAR ON ENCOUNTER DATA QUALITY

True Program Integrity means having complete, accurate, and timely eligibility and encounter data. There is variation among states as to what they deem adequate for encounter data submission, ranging from 90%-98%. However, we anticipate this variation will narrow over time as more states migrate to the higher end of the range as demonstrated with recently awarded Medicaid contracts.

Achieving the minimum state requirements may satisfy compliance requirements but may also miss substantial revenue underpayments. Plans should target achieving at or above a 99% data accuracy level to ensure appropriate revenue capture reflecting the overall population risk and appropriate category of aid. Additionally, because encounter data serves as the basis for state capitation rate setting, any incomplete, late, or rejected encounter submissions will misrepresent the true underlying cost, risk, and revenue paid to the plan. This misrepresentation can lead to inaccurate revenue capture or lower capitation rates in the future, as described in the recent client example provided.

GROWING IMPORTANCE OF ELIGIBILITY AND CLASSIFICATION OF AID VALIDATION

Accurate eligibility classification is critical for MCOs to receive correct capitation payments as eligibility and classifications of aid can shift throughout the year. While the state is responsible for identifying eligibility, MCOs will need to be vigilant in collecting accurate data, identifying and documenting any changes to classifications of aid, maintaining updates, and sending updated information back to the state to create an accurate picture of the population. A proactive strategy is needed to help mitigate any revenue degradation in the event that enrollment falls, beneficiaries are inaccurately deemed ineligible to receive benefits, or if a segment of the membership is not receiving accurate capitation rates to reflect the appropriate current classification of aid.

MCOs in states considering work requirements should pay particular attention to the experience of states currently phasing in the program. Early results from Arkansas indicate that 8,500 people were disenrolled for failure to comply with the program requirements for 3 months. Over 80% of the individuals who were required to report their work-related activities did not report any activities. Coverage loss projections indicate that some people disenrolled for non-compliance may still be eligible for Medicaid but experienced barriers in providing the monthly documentation, ultimately lowering MCO revenue levels.

To combat unintended eligibility loss, MCOs should evaluate operational processes to identify opportunities to:

  • Educate their membership base on reporting requirements
  • Identify barriers they may have to accessing the online reporting platform
  • Use encounter data to identify members susceptible to churn to provide employment resources and encourage compliance with work requirements

Maintaining accurate classifications of aid can also have a material impact on MCO revenue. States perform initial category of aid determinations, but MCOs are responsible for reassessing members annually, creating greater focus on maintaining accurate classifications of aid. All MCOs would benefit from taking a critical look at operational processes in place to maintain accuracy of the category of aid throughout the year. Misclassification can cost the MCO thousands of dollars per member per month (PMPM), as illustrated in the Virginia example.

As a result, MCOs should review their operational processes to identify how they integrate encounter data with health screening assessments. Those MCOs in states using functional health status data to determine capitation rates (as with the MLTSS populations) will need to place even greater financial weight on accurately reporting encounter data. To ensure accuracy, MCOs should take advantage of all opportunities to verify members’ attributed aid categories throughout the year and properly reclassify and document changes in the appropriate category of aid.

CREATING AN ACTION PLAN

MCOs can prepare for CMS assessments and increased oversight of Program Integrity by operationalizing both near-term and long-term organizational strategies.

Near-Term Strategy

  • State Collaboration: MCOs should continue to monitor CMS program initiatives to understand program requirements specific to their state.
  • Audit Preparation: MCOs should thoroughly review financial reports and MLR calculations to ensure accuracy.
  • Data Integrity Diagnostic: MCOs should conduct a diagnostic to gain an understanding of current data accuracy gaps, identify potential financial implications, and prioritize near-term operational change to improve data accuracy and revenue completeness.

Long-Term Strategy

  • Review the Operational Model: MCOs should strive to create an operationally efficient, integrated process for receiving state data files, verifying eligibility, and reviewing encounter data to connect the appropriate members with resources to address social determinants of health.
  • Monitor Revenue Accuracy: MCOs should address changes in Medicaid program integrity requirements as part of ongoing data improvement efforts. Data integrity should drive both compliance and revenue management.
  • Build Stakeholder Engagement: MCOs should educate providers on submitting complete and timely encounter data to facilitate data accuracy from the initial intake. MCOs can prepare for CMS assessments and increased oversight of Program Integrity by operationalizing both near-term and long-term organizational strategies.

HEALTHSCAPE AND PARETO CAN HELP.

Do you need to evaluate your data integrity and how you are leveraging your operational model to help maintain the highest level of data accuracy? HealthScape and the Pareto Intelligence analytics platform are the resources you need. Contact Michelle Werr at (630) 546-5044 or mwerr@healthscape.com for more information.