Tech Tuesday: The Wish List for Phase II of the Medicaid and CHIP Performance Indicators

Last week, I blogged about the release of phase I performance indicators requiring states to report the data elements “most critical to measuring the outcomes of the Medicaid and CHIP eligibility and enrollment process.” I am already thinking about phase II of the Medicaid and CHIP performance metrics but the most obvious question at this point is what data can we expect to see from the new marketplaces? When CMS put out its request for information on the proposed performance indicators, it asked respondents to comment on whether the measures should be applied to the marketplace. Well…yes, plus additional measures (i.e. number of exemption certificates, plan selection data, etc.) are needed that are unique to the marketplace. So, where are the companion performance indicators for the federal and state marketplaces?

Good question but let’s move on. Here’s what really keeps me up at night. How well will enrollment be coordinated between Medicaid or CHIP and the marketplace? When the ACA was implemented, the vision was to create streamlined access across the continuum of coverage with aligned eligibility rules and shared IT systems so no one would slip through the cracks. But we have strayed from this concept. In states where the federal marketplace will operate, and even in some of the states that have built their own marketplaces, eligibility is bifurcated. So there is a strong need for not only data reporting but also data reconciliation. While I touch on this issue below, in next week’s Tech Tuesday blog I’ll tell you about how we reconciled transfers and enrollment between Medicaid and CHIP in New Hampshire. For now, let’s talk about what should be on the list for Phase II performance indicators:

1)   Transfers between Medicaid, CHIP and the marketplace – Phase I requires the reporting of accounts transferred to and from the marketplace. Determining whether transfers are successfully handled requires an effective data reconciliation process but additional data reporting on transfers can be helpful. A good starting place for phase II would be to track eligibility by source (i.e., new application, renewal, transfers) so we can more readily isolate concerns associated with a specific source.

2)   Ineligibility reason codes –Phase 1 data will distinguish between the proportion of applicants denied because they were not eligible (i.e., over income, immigration status) vs. those for which there is insufficient information to determine eligibility (i.e., application missing a signature, sent request for additional information that was returned for a bad address). However, a primary goal should be to strive toward having virtually no applications or renewals for which eligibility cannot be determined. Our friends in Louisiana have mastered this on the renewal side, with less than one percent disenrollment at renewal due to non-eligibility reasons. To tackle this issue, it’s important to gather more detailed data reflecting why eligibility can’t be determined because different reasons require different strategies to resolve.

3)   Disenrollment and disenrollment reasons – While total enrollment reflects both new enrollment and disenrollment, it’s important to track disenrollment separately and the specific reasons for disenrollment. Similar to understanding why an eligibility was denied, it’s important to understand why potentially-eligible individuals are losing coverage. Both denial and disenrollment reason codes should be standardized for comparability across states and to ensure that data point to issues that need attention and can be improved either through administrative or policy changes. No need to re-invent the wheel here. The Maximizing Enrollment initiative already did the heavy lifting in working with a collaborative of states to identify a great set of denial and disenrollment codes, which can be found in this report.

Last but not least, it’s not just about the data, it’s about using data to continually improve our public coverage programs. Establishing benchmarks and setting expectations for program improvement should be the goal. To this end, when we commented on the performance indicators we recommended that CMS consider an incentive program (similar to the CHIPRA performance bonuses) to encourage states to quickly build their reporting capacity and show improvement in their measures over time. So we’ll keep these items on the wish list as well.

[This blog is part of a Tech Tuesday blog series highlighting the important IT issues involved in making the benefits of the Affordable Care Act easier to access for consumers.]


Tricia Brooks
Tricia Brooks is a Research Professor at the Georgetown University McCourt School of Public Policy’s Center for Children and Families