Data Dashboards Offer Transparency to Medicaid Unwinding Process

As Unwinding Wednesday blog readers know, we are obsessed with data. We’ve highlighted key data to use to monitor the unwinding (performance indicators and supplemental unwinding data), stressed the importance of monitoring call center statistics as they will be the canary in the coalmine, and dug into the nuances of data on procedural disenrollments. And last week Tricia Brooks walked through data that may show warning signs that a state’s unwinding is not going well. But the critical piece underlying all of our data discussions is the need for transparency, i.e., publicly reported data.

Now that the continuous enrollment protection (MOE) has ended, several states have launched unwinding data dashboards while others have indicated plans to do so. (Information on which states have or plan to have publicly available unwinding data can be found on our 50-state tracker). As with most things Medicaid, each state is different; the type and amount of data varies significantly. For example, Idaho provides just three data points focused only on number of renewals completed and how many were found eligible or ineligible for Medicaid, while Iowa provides a wide range of data on enrollment, applications, and renewals. Eight states currently have some form of a data dashboard, which includes some, or all, of the following data:

  • Enrollment – While most states published monthly enrollment data pre-COVID, states now include the metric as part of their dashboard. Minnesota provides total enrollment by renewal month with the ability to filter and sort the data, whereas Washington provides enrollment by renewal month including potential disenrollment numbers.
  • Renewals completed by month and/or disenrollment reason – As part of their required monthly reporting to CMS, states must provide the number of beneficiaries due for renewal and the outcome of those renewals. Six of the eight states with dashboards (IA, ID, MN, PA, RI, and UT) have data on renewals completed, which may be broken down by outcome. For example, Utah’s dashboard indicates how many cases (representing individuals or families) were closed due to ineligibility and were sent to the Marketplace and how many cases were closed due to procedural reasons and therefore not sent to the Marketplace. Some states also indicate how many renewals were able to be completed on an ex parte basis, aka a passive or administrative renewal. Through its “Medical Assistance Annual Renewals” dashboard, Iowa provides data on successful ex parte renewals as well the number of renewal forms sent when the renewal could not be complete through ex parte.
  • Individuals who maintained coverage during the MOE Most states continued to process renewals while the continuous enrollment protection was in place, so they have flagged individuals who appeared ineligible for coverage or did not return the renewal form. Estimates of how many individuals have been “protected” by the MOE is included by several states. In fact, Oklahoma’s dashboard only provides data on enrollees who have maintained coverage through the continuous enrollment protection. It’s important to keep in mind that circumstances may have changed for enrollees since they were flagged, which is why it’s so important for states to conduct full renewals based on current data before taking action. We should not assume that everyone on a flagged or protected list is no longer eligible. This is particularly true if the state is including counts of people who did not return their renewal form.
  • Churn – Once the continuous enrollment protection ends, we will likely see significant “churn” in Medicaid and CHIP, where enrollees lose coverage and then re-enroll within a short period of time. I admit that I was pleasantly surprised to multiple states commit to reporting data on churn. Pennsylvania will provide churn data on individuals who return to Medicaid within four months of having their case closed while Utah will report individuals who return to the program within three months.
  • Call center statistics (!) – Call center statistics can be a key warning sign of problems – as call volumes likely spike as individuals seek help with their renewals, call wait times may increase which means call abandonment rates will likely increase too. Two states (Rhode Island and Utah) have included call center metrics on their dashboards which detail wait times and abandonment rates in addition to a few other data points.

I am impressed by the data points that states have or plan to make available. But I am even more thrilled that much of this data is disaggregated by a variety of demographic and program-based characteristics. Stratified data can help determine which groups may be disproportionately affected by the unwinding and where targeted outreach is needed. Six of the states that have published dashboards have provided disaggregated data metrics beyond “protected” eligibility status. This includes data broken down by age (IA, MN,  OK, PA, RI, WA), race (MN, OK, WA), ethnicity (MN, OK, WA), eligibility category (IA, MN, OK, WA), and county or zip code (IA, MN, PA, OK, RI, WA). Minnesota, the state with the most comprehensive dashboard in terms of stratification, even breaks down its data by “social vulnerability” quartile, or most to least vulnerable based on communities that are disadvantaged due to historical and persistent underinvestment in social supports.

Along with gathering intel from the field, analyzing available data will be essential to monitoring how the unwinding is going. While CMS is required to post unwinding data reported by states, there is not a clear timeline for when we might see the first round of data nor an idea of the ongoing lag time between the data being reported and posted. Therefore, stakeholders’ ability to use data for monitoring at least for the foreseeable future will depend on state transparency. The data dashboards that are already up and running are great examples of how other states can accomplish this.

[Editor’s Note: This is the 29th blog in the Unwinding Wednesday series. For more information, visit our PHE Unwinding resource page where you’ll find other blogs in this series, reports, webinars and the 50-state tracker.]

Allexa Gardner is a Senior Research Associate at the Georgetown University McCourt School of Public Policy’s Center for Children and Families.