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1 3 3 0 G S T R E E T N W , W A S H I N G T O N , D C 2 0 0 0 5 P H O N E : 2 0 2 - 3 4 7 - 5 2 7 0 , F A X : 2 0 2 - 3 4 7 - 5 2 7 4 W E B S I T E : W W W . K F F . O R G

December 2011

Performance Measurement Under Health Reform: Proposed Measures for Eligibility and Enrollment Systems and Key Issues and Trade-offs to Consider

EXECUTIVE SUMMARY

Beginning in January 2014, the Patient Protection and Affordable Care Act (ACA) will create a new continuum of coverage for millions of Americans through a Medicaid expansion and new health insurance exchanges. The ACA also includes requirements for coordinated and streamlined Medicaid and exchange enrollment systems. The adoption of new eligibility and enrollment requirements under the ACA provides states and the federal government an important opportunity to implement a meaningful set of performance measures for eligibility and enrollment systems. Performance measures could be used at the federal level to assess state performance in meeting the ACA’s eligibility and enrollment goals, while states could use measures for program management and quality improvement. To help inform the development of eligibility and enrollment performance measures, the Kaiser Commission on Medicaid and the Uninsured convened a roundtable that included federal and state officials, researchers, and other stakeholders to discuss performance measurement. Based on the roundtable discussion and expertise of the study team, a draft list of potential performance measures was then developed, and telephone interviews were conducted with several roundtable participants and additional state officials, researchers, and other stakeholders to obtain feedback on the list. This brief presents the list of potential performance measures (Table 1) that was developed based on the roundtable discussion, telephone interviews, and study team expertise. The list is not designed to be exhaustive of all potential measures, nor is it intended as a recommended set of measures. Rather, it offers a broad range of useful performance measures from which stakeholders could select, depending on their specific measurement needs and goals. It also discusses key issues identified by roundtable and interview participants in selecting and developing measures, including the following: It will be important to consider the balance of standardizing measures across states versus providing states flexibility in the adoption of measures. Participants emphasized the value of adopting a core set of measures with standardized definitions for constructing and reporting comparable data across states. Moreover, there was wide agreement that a few performance measures are key for all states to report, such as new and total enrollment and disenrollment as well as continuity of coverage. Although participants stressed the value of standardized measures, they also recognized that providing states flexibility in adopting measures beyond a core set will be important given states’ different starting places with their Medicaid programs and that states’ coverage systems will likely vary under reform.

There are key trade-offs between the accessibility and value of many performance measures. Potential measures vary widely in their accessibility, data needs, and difficulty to construct. Participants largely agreed that it might be useful to phase in some of the measures that are more difficult to construct in later years, as data systems and systems’ expertise evolve. However, it will be important to weigh this approach against the value of these measures, because many of the measures that require more effort to construct offer greater insights into performance than other, more readily available measures. Variation in the timeliness of measures is also important to consider. For example, some measures could be reported on a real-time basis, whereas others could have a significant lag time.

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Both single- and cross-program data will be valuable for understanding performance. Participants noted that program-specific data, such as Medicaid data, will be useful for understanding how processes and systems work within a single coverage program, but emphasized that cross-program measures that look across Medicaid, Children’s Health Insurance Program (CHIP), and exchange coverage will be necessary to provide a full picture of enrollment performance within a state.

Table 1: Potential Performance Measures for Eligibility and Enrollment Systems Under Health Reform

Measure Definition I. Coverage of the Target Population 1. Total enrollment Number of enrollees in specified program(s) 2. Coverage rate among target population Percentage of program-eligibles that are covered/uninsured 3. Appropriateness of coverage Percentage of enrollees with incorrect eligibility determination II. New Enrollment 4. New enrollment Number of new enrollees in specified program(s) 5. “New-to-public-coverage” enrollment Number of new enrollees excluding churn and transfer, across program(s) 6. Timely approval rate (applications) Percentage of all approved applications with start/end dates within specified period 7. Administrative approval rate (applications) Percentage of all approved applications with income verified administratively 8. Multiple application method options Number of predefined application method options available 9. Simplified application steps Number of policies deemed as simplification III. Retention 10. Disenrollment Number of disenrollees from specified program(s) 11. Continuous coverage rate Percentage of new enrollees covered by program(s) for a specified period 12. Churn rate Percentage of disenrollees reenrolling within a specified period 13. Timely approval rate (renewals) Percentage of all approved renewals with start/end dates within specified period 14. Administrative approval rate (renewals) Percentage of all approved renewals with income verified administratively 15. “Unverified disenrollment” rate Percentage of disenrollees not verified program-ineligible (based on exit reason) 16. Multiple renewal method options Number of predefined renewal method options 17. Simplified renewal steps Number of policies deemed as simplification IV. Coordination 18. Coverage transfers Number of new program enrollees that transferred from other program(s) without gap 19. Transfer rate Percentage of program disenrollees that transfer to other program(s) without gap 20. Coordination with exchange Whether the program eligibility system is linked to exchange for data sharing V. User Experience 21. Availability of customer support Whether 24 hours a day, seven days a week (24/7) customer call center is available 22. Access/use of customer support Number of completed contacts at call center 23. Timeliness of customer support Average wait time (call center) 24. Customer complaints Number of complaints (call center) 25. Customer satisfaction Percentage of enrollees highly satisfied with application/renewal process 26. Customer appeals Number of appeals submitted related to program eligibility

In conclusion, measures of eligibility and enrollment system performance under reform will be important tools to help guide program management and quality improvement and for understanding state progress in implementing reform and its impacts. Setting clear expectations for performance measurement is key as many states have already begun work to upgrade their systems and creating cross-program measures will likely require significant lead time. Determining agreed upon measures now will both enable states to move forward and help establish a baseline set of measures against which ACA implementation can be tracked.

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INTRODUCTION Beginning in January 2014, the Patient Protection and Affordable Care Act (ACA) will create a new continuum of coverage for millions of Americans that will provide assistance to individuals with incomes up to 400 percent of poverty through a Medicaid expansion and tax credits to reduce the cost of purchasing coverage in new Health Insurance exchanges. The ACA also includes requirements for coordinated and streamlined Medicaid and exchange enrollment systems that connect people with the appropriate program and maximize reliance on technology to reduce burdens on individuals and enhance continuity of coverage. Measuring the performance of states’ eligibility and enrollment systems will be a key component of assessing the impacts of health reform. However, developing and implementing a set of meaningful performance measures is difficult due to both data and policy challenges. Moreover, selecting a specific set of performance measures requires consideration of a number of key issues and trade-offs and will depend, in large part, on who will utilize the measures and how they will use them. This brief seeks to inform the development of performance measures by presenting a broad range of potential measures from which a specific subset could be utilized for a variety of purposes at both the federal and state levels. It also identifies key trade-offs and issues to consider in selecting and developing a set of performance measures. BACKGROUND Eligibility and Enrollment Systems Under Reform The ACA envisions that states will create coordinated integrated eligibility and enrollment systems for Medicaid, Children’s Health Insurance Program (CHIP), and exchange coverage that will, in most cases, provide real-time eligibility determinations and rely on electronic data exchanges to the greatest extent possible. In guidance released in May 2011, the U.S. Department of Health and Human Services (HHS) identified several key goals for the new eligibility systems:

 Timely and appropriate coverage to eligible individuals  Seamless coordination and integration between Medicaid, CHIP, and exchange coverage  A high-quality user experience  Timely and complete data reporting to support quality improvement and management

Current Medicaid eligibility systems vary greatly across states. Some states have made significant progress in achieving real-time eligibility determination, other electronic simplification, and in coordinating Medicaid and CHIP enrollment. However, many other states continue to rely on outdated paper-based eligibility systems. Recognizing that most states will have to make significant improvements to their Medicaid eligibility and enrollment systems to achieve the requirements under health care reform, HHS made enhanced funding available to states to upgrade eligibility systems and maintain these systems over time. Available reimbursement for the design, development, and installation of eligibility and enrollment systems increased from a 50 percent federal match to a 90 percent federal match for states effective through December 31, 2015. The maintenance and operation of such systems also is eligible for an increased

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reimbursement rate, from a 50 percent to a 75 percent federal match, which will remain available indefinitely, provided the systems continue to meet specified requirements. In addition, several states have received “Early Innovator” grants from HHS to support development of exchange eligibility and enrollment systems. Although these grants focus on exchanges, they have clear connections and impacts on Medicaid given the close connections between the systems and coverage envisioned under the ACA. For many states, the new requirements for eligibility and enrollment systems under reform and the availability of enhanced federal funding will enable their first substantial systems upgrade in decades. Many states currently are engaged in the planning process to upgrade their systems or have already begun work on their upgrades. Uses of Eligibility and Enrollment System Performance Measures Under Reform The adoption of new eligibility systems under the ACA provides states and the federal government an important and unique opportunity to develop and implement a meaningful set of eligibility and enrollment performance indicators. In fact, as outlined earlier, one of the key expectations HHS has for new eligibility systems is that they produce “timely and complete data reporting.” Performance measures could be used in a number of ways under reform by a variety of different stakeholders. At the federal level, the proposed rule to implement the eligibility and enrollment provisions of the ACA notes that the federal government, in collaboration with states, will develop performance standards and metrics for the streamlined and coordinated eligibility and enrollment system required under the ACA. Moreover, it notes that these metrics will be used to support the standards and conditions that eligibility systems must meet to qualify for the enhanced federal Medicaid funding match available for system upgrades and maintenance. At the state level, performance measures could be used to assist in planning new eligibility systems, particularly to ensure that necessary reporting capabilities are built into them. States could further use performance measures to aid in program management and continuous quality improvement of Medicaid and other coverage programs. Finally, researchers and other stakeholders might use performance measures to analyze the impacts of health reform and its success in reducing the uninsured and providing a simple, streamlined enrollment process for individuals. Current Eligibility and Enrollment Performance Measurement Capabilities Although a few states have progressed in measuring their performance, to date most states use few, if any, performance measures to assess how successfully they enroll or retain eligible individuals in Medicaid or CHIP coverage. For some states, this could be a matter of choice; short of federal requirements, they might be reluctant to invest the resources needed to develop, maintain, and assess a set of performance measures over time. However, for a number of states, the issue has historically been less one of choice than of limited options. Often working with antiquated and/or highly fragmented data systems, many states simply have not had access to the kinds of data elements or data linkages necessary to produce quality performance measures. Currently, states track enrollment of individuals in their programs and manage payment of related claims through a state management information system (MIS). Some states maintain more than one

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MIS; for example, a state can have an MIS for its Medicaid program (commonly known as the MMIS) and a separate MIS for its CHIP. In many states, the MIS is maintained separately from the program eligibility system, which is the system that supports the MIS by tracking individuals through the application and renewal processes and more generally monitors their program eligibility. In some states, the eligibility system can operate on a relatively old platform and serve multiple benefit programs, such as Temporary Assistance for Needy Families (TANF) and the Supplemental Nutrition Assistance Program (SNAP). As a result, data elements in these systems might be difficult to access and to reliably maintain. This system fragmentation and reliance on outdated platforms is a key complication that many of the current investments to modernize eligibility systems aim to address. Development and implementation of quality performance measures under reform will require focused effort in most states. The scope of challenges states might face will depend, in part, on the capabilities of their current data systems to support measure development. And, perhaps even more importantly, it will depend on the decisions that states make going forward—both in how they respond to Medicaid eligibility and enrollment policy options under reform and how they choose to design their exchanges. The governance, structure, and eligibility systems of exchanges all will have important implications for measuring enrollment and retention in Medicaid given the interrelatedness of their enrollment processes under reform. For example, whether the exchange uses the same eligibility system as Medicaid or a different system will dictate how easily data can be combined across programs and whether linkages must be designed and ultimately built between the two systems to obtain cross- program data. At the federal level, performance measurement of Medicaid and CHIP enrollment also has been relatively limited to date. Medicaid currently requires states to meet certain timeliness standards with regard to determining eligibility. Further, the Children’s Health Insurance Program Reauthorization Act (CHIPRA) made available a new performance bonus incentive to states that adopt certain enrollment policy simplifications and meet specified enrollment goals for children in Medicaid and CHIP, which has served as an effective motivating factor for some states. Medicaid programs also are subject to a number of program integrity efforts. However, these efforts focus primarily on identifying errors in enrollment processes rather than achieving the streamlined enrollment process outlined under reform. Federal performance measurement efforts have also been pursued in other programs, such as TANF and SNAP, with mixed and, sometimes unclear, results. STUDY DESIGN To help inform the development of performance measures for eligibility and enrollment systems under reform, in 2011 the Kaiser Commission on Medicaid and the Uninsured convened a roundtable that included federal and state officials, researchers, and other stakeholders to discuss the current status of performance measurement among states, what types of measures would be most useful under reform, and potential challenges to developing performance measures. Following this roundtable, a draft set of potential performance measures was developed based on feedback from the roundtable discussion and the expertise of the study team. In September 2011, follow-up telephone interviews were conducted with several of the roundtable participants and additional state officials, researchers, and other stakeholders to review the draft list of performance measures, make recommendations on measures listed, and identify key issues associated with selecting and developing measures. This feedback and information from roundtable and interview participants is reflected in the brief’s description of potential measures and key issues to consider.

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POTENTIAL PERFORMANCE MEASURES FOR ELIGIBILITY AND ENROLLMENT SYSTEMS Table 2 presents the list of potential performance measures developed as part of this study. The list was not designed to be exhaustive of all potential measures, nor is it intended as a recommended set of measures. Rather, it offers a broad range of useful performance measures from which stakeholders could select a subset based on specific performance measurement needs and goals. The measures are organized based on five categories that together encompass the goals outlined for new state eligibility and enrollment systems under the ACA, including (1) coverage of the target population, (2) new enrollment, (3) retention, (4) coordination, and (5) positive user experience. Although the measures are organized by category, the categories are not mutually exclusive. As such, measures listed within any one category may apply more broadly. For example, a measure of timeliness with the renewal process is included in the retention category, but it also pertains to the positive user experience category. To the right of each measure listed in the table is a series of columns that provide (1) a brief definition of the measure, (2) a summary of its purpose, (3) a classification of the measure type, (4) a description of the data needs to create the measure, and (5) its anticipated data source. We define each of these next. Definition. The definition of each measure is given in text form (as opposed to a formula or equation) as a basic guide for how it can be constructed. For several measures, this definition will have to be expanded before it can be put into use, by specifying both the programs and time frame over which the measure applies. These dimensions are left unspecified because they reflect a choice, driven in large part by how—and by whom—a particular measure will be used. As an example of this choice, consider two potential users of performance measures. The first is a state Medicaid administrator, who wants to monitor program performance by tracking three simple measures shown in the table—total enrollment (measure 1), new enrollment (measure 4), and disenrollment (measure 10). The second is a federal policymaker, who wants to assess coverage growth across states using these same three measures:

 For the state Medicaid administrator, each of these measures would presumably span only the Medicaid program and be defined over a relatively short period (such as a month) to allow for regular tracking. By constructing these measures over a series of months to form a trend line, the administrator can effectively track not only the growth of the program but also assess the source for any notable change—that is, whether the measures are driven by shifts in new program enrollment (inflow) and/or disenrollment (outflow).

 By contrast, the federal policymaker might construct these same measures more

broadly—for example, spanning a longer time period (for example, a year) and capturing the full range of coverage programs (Medicaid, CHIP, and exchange coverage). By comparing these broader measures across states, the policymaker can gain an understanding of how enrollment growth has varied across states, potentially identifying both those that could improve performance and those that might serve as successful models.

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Table 2: Potential Performance Measures for Eligibility and Enrollment Systems Under Health Reform

Measure Definition Purpose Type Data Needs Data Source

I. Coverage of the Target Population 1. Total enrollment Number of enrollees in

specified program(s) Starting point to monitor progress covering target population

Outcome Minimal; requires basic enrollment data tracked on an ongoing basis

State program MIS

2. Coverage rate among target population

Percentage of program- eligibles that are covered/uninsured

Assess state coverage rates, including coverage in private market

Outcome Requires household survey data and access to data expertise

Major household survey(s) (e.g. ACS)

3. Appropriateness of coverage

Percentage of enrollees with incorrect eligibility determination

Assess/monitor program integrity

Outcome Requires audit to obtain necessary data

State program audit

II. New Enrollment 4. New enrollment Number of new enrollees in

specified program(s) Monitor flow into state program(s); starting point to assess changes to total enrollment

Outcome Minimal; requires basic enrollment data tracked on an ongoing basis

State program MIS

5. “New-to-public- coverage” enrollment

Number of new enrollees excluding churn and transfer, across program(s)

Assess source of new enrollment and the effects of outreach and other policy changes linked to new coverage uptake

Outcome Requires linking a person’s enrollment over time and across programs

State program MIS

6. Timely approval rate (applications)

Percentage of all approved applications with start/end dates within specified period

Monitor application timeliness, flag procedural issues

Process Requires reliable eligibility system data (e.g., application start/end dates)

State program eligibility system(s)

7. Administrative approval rate (applications)

Percentage of all approved applications with income verified administratively

Monitor adoption of administrative procedures for the application process

Process Requires reliable eligibility system data (e.g., administrative approval flag)

State program eligibility system(s)

8. Multiple application method options

Number of predefined application method options available

Assess state application process policy

Policy Simple measure; requires clear definitions

State program administrator

9. Simplified application steps

Number of policies deemed as simplification

Assess state application process policy

Policy Simple measure; requires clear definitions

State program administrator

III. Retention 10. Disenrollment Number of disenrollees from

specified program(s) Monitor flow out of program(s); starting point to assess changes to total enrollment

Outcome Minimal; requires basic enrollment data tracked on an ongoing basis

State program MIS

11. Continuous coverage rate

Percentage of new enrollees covered by program(s) for a specified period

Monitor progress retaining individuals in coverage; starting point to assess changes in disenrollment

Outcome Requires linking a person’s enrollment over time/programs

State program MIS

12. Churn rate Percentage of disenrollees reenrolling within a specified period

Monitor program churn; e.g. as an indicator of where/for whom retention might be improved

Outcome Requires linking a person’s enrollment over time

State program MIS

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Measure Definition Purpose Type Data Needs Data Source 13. Timely approval rate (renewals)

Percentage of all approved renewals with start/end dates within specified period

Monitor renewal timeliness, flag procedural issues

Process Requires reliable eligibility system data (e.g., renewal start/end dates)

State program eligibility system(s)

14. Administrative approval rate (renewals)

Percentage of all approved renewals with income verified administratively

Monitor adoption of administrative procedures for the renewal process

Process Requires reliable eligibility system data (e.g., administrative approval flag)

State program eligibility system(s)

15. “Unverified disenrollment” rate

Percentage of disenrollees not verified program-ineligible (based on exit reason)

Monitor disenrollment not tied to ineligibility(e.g. paperwork), as a process measure linked to retention

Process Requires reliable eligibility system data (e.g., meaningful exit reason codes)

State program eligibility system(s)

16. Multiple renewal method options

Number of predefined renewal method options

Assess state renewal process policy

Policy Simple measure; requires clear definitions

State program administrator

17. Simplified renewal steps

Number of policies deemed as simplification

Assess state renewal process policy

Policy Simple measure; requires clear definitions

State program administrator

IV. Coordination 18. Coverage transfers

Number of new program enrollees that transferred from other program(s) without gap

Monitor seamless transfer of individuals across programs; e.g., as an indicator of progress retaining individuals in coverage

Outcome Requires linking a person’s enrollment over time/program(s)

State program MIS

19. Transfer rate Percentage of program disenrollees that transfer to other program(s) without gap

Monitor seamless transfer of individuals across programs; e.g., as an indicator of progress retaining individuals in coverage

Outcome Requires linking a person’s enrollment over time/program(s)

State program MIS

20. Coordination with exchange

Whether the program eligibility system is linked to exchange for data sharing

Assess state policy regarding program coordination

Policy Simple measure State program administrator

V. User Experience 21. Availability of customer support

Whether 24/7 customer call center is available

Assess availability of customer assistance

Outcome Simple measure, requires ongoing tracking

State program administrator

22. Access/use of customer support

Number of completed contacts at call center

Monitor use of customer assistance

Outcome Requires vendor data tracked on an ongoing basis

Call center vendor

23. Timeliness of customer support

Average wait time (call center)

Monitor timeliness of customer assistance

Outcome Requires vendor data tracked on an ongoing basis

Call center vendor

24. Customer complaints

Number of complaints (call center)

Monitor quality of user experience

Outcome Requires vendor data tracked on an ongoing basis

Call center vendor

25. Customer satisfaction

Percentage of enrollees highly satisfied with application/renewal process

Assess/monitor quality of user experience

Outcome Requires customer survey

Enrollee satisfaction survey data

26. Customer appeals

Number of appeals submitted related to program eligibility

Assess/monitor quality of user of experience

Outcome Requires reliable data on appeals

State administrative data on appeals

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Purpose and type. The next two columns of the table summarize each measure’s general purpose and type, offering a sense for how the measure can be used to monitor or otherwise assess performance within a given category. The type classification distinguishes measures by organizing them into (1) outcome measures, which provide the most direct indication of performance within a given category; (2) process measures, which account for factors believed to be closely linked to outcomes (such as a state’s timeliness in reviewing renewals, which might be closely linked to the program churn and other retention-related outcomes); and (3) policy measures, which reflect policy or procedural steps believed to promote gains in process or outcomes (such as the adoption of enrollment simplifications). Within each of the table’s five categories, the measures have been ordered by the type—from outcome, to process, to policy. This ordering reflects the view, broadly shared by participants, that outcome measures are most closely linked to quality performance monitoring, whereas policy measures are relatively easy to obtain but less meaningful indicators of performance relative to outcome and process measures. Data needs and data source. The final two columns of the table summarize the data needs and data source for each measure. As seen in the table, many proposed measures have relatively minimal data needs. For example, most of the basic enrollment measures—including total enrollment (measure 1), new enrollment (measure 4), and disenrollment (measure 10)—can be obtained from the MIS for each state’s program(s). Likewise, all of the policy measures can be obtained by contacting state program administrators or others with detailed knowledge of state programs. Measures with more substantial data needs include those requiring the linkage of individuals across different data systems and/or over time—such as the continuous coverage rate or churn rate (measures 11 and 12)—as well as measures requiring expertise to construct—most notably, the coverage rate among the target population (measure 2). For some of the measures, a further complication is that they rely on data from a state’s program eligibility system, which, as noted earlier, a number of states administer separately from the program MIS and can contain data elements that are not easily accessible, are not verified for quality, or are not reliably maintained. KEY ISSUES AND TRADE-OFFS TO CONSIDER IN SELECTING PERFORMANCE MEASURES

As noted, Table 2 presents a broad range of potential performance measures from which a subset of indicators could be selected to track and monitor and potentially compare against a set of standards or benchmarks. The roundtable discussion and the follow-up interviews revealed a number of key issues and trade-offs to consider in selecting and developing performance measures, as discussed next. Use and Structure

Different users or audiences have different priorities and preferences for performance measures. For example, as noted earlier, the measures a state might use for its own program management will likely differ from measures the federal government might use to assess state performance. Further, researchers would likely have differing priorities regarding a set of desired performance measures. Roundtable discussants identified incentives and penalties tied to measures, data ownership, and reporting responsibilities as important factors related to the selection of measures. In particular, some state Medicaid agency officials expressed apprehension about how potential performance measures that are influenced by factors outside of their control—for example, insurance coverage among the target population and continuity of coverage across coverage programs—might be used. They also raised some concerns related to potential increased burdens associated with meeting reporting requirements.

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It will be important to consider the balance of standardizing measures across states versus providing states flexibility in adoption of measures. Participants emphasized the value of adopting a core set of measures with a standardized definition for constructing and reporting comparable data across states. Moreover, there was wide agreement that a few performance measures—such as new and total enrollment and disenrollment as well as a measure of continuity of coverage—are key measures for all states to report. Several participants suggested that, if a required set of standardized measures is developed, it will be important to ensure it is a reasonable and feasible number of measures for states to report. They cautioned that requiring too many measures could create a burden for states, especially amid current budget challenges. Although participants stressed the value of standardized measures, they also recognized the importance of providing states flexibility in adopting measures beyond a possible core set. This flexibility was viewed as key given that states are in different starting places with their Medicaid coverage levels and eligibility systems. In addition, under reform there will likely be significant state variation in coverage systems, including how Medicaid interacts with CHIP and exchange coverage and the structure of exchanges. Accessibility, Timeliness, and Scope There are key trade-offs between the accessibility and value of many measures. Potential measures vary widely in their accessibility and data needs—some can be readily drawn from existing data sources, whereas others might require significant effort and investment to construct. Participants largely agreed that it might be useful to phase in some of the measures that are more difficult to construct in later years, as data systems and systems’ expertise evolve and improve. However, it will be important to weigh this approach against the value of these measures, because many of the measures that require more effort to construct offer greater insights into performance than more readily available measures. For example, measuring the continuous coverage rate across all coverage programs in a state would require linking a person’s enrollment data over time and across programs. However, once developed, this measure can provide a rigorous and precise understanding of how well a state retains individuals in coverage and whether its retention improves over time. Both single- and cross-program data will be valuable for understanding performance. Participants noted that program-specific data, such as Medicaid data, will be useful for understanding how processes and systems work within a single coverage program, but emphasized that cross-program measures that look at transitions across Medicaid, CHIP, and exchange coverage will be necessary to provide a full picture of enrollment performance within the state. Participants noted that cross-program measures are necessary to identify an individual’s coverage status before enrolling in his or her current coverage and what happens to an individual’s coverage status following an eligibility denial or termination. Participants further stressed that producing cross-program data will require significant planning and coordination across coverage programs, including key decisions about what additional program data (for example, unsubsidized exchange coverage) should be incorporated into performance data efforts. As such, participants noted that the importance of cross-program data should be taken into consideration early, while states are in the process of developing their new eligibility systems. Subgroup measures could also be useful for understanding enrollment experiences and outcomes for vulnerable groups and within-state variations in enrollment. Specific suggestions for subgroup analysis included racial/ethnic groups, eligibility groups determined financially eligible based on Modified Adjusted Gross Income (MAGI) versus those whose eligibility continues to be determined based on current Medicaid rules (MAGI versus non-MAGI groups), and among different localities within a state (for example, counties or urban versus rural areas).

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Variation in the timeliness of measures is also important to consider. Some measures, such as total and new enrollment, could be constructed fairly easily and reported on a real-time basis. Several participants noted that including these types of real-time indicators as part of a performance measurement dashboard would be useful to provide readily accessible measures of performance and guide program management and improvement. Measures with a considerable lag time to construct, such as surveys of consumer satisfaction and coverage among the target population, could not be used for this purpose. However, it was broadly recognized that such measures would add considerably to the monitoring of state progress and system performance, albeit with some lag in timing.

Benchmarking of Measures

Benchmarks for performance measures can be tied to a state’s progress over time and/or national standards or best practices. Participants noted that measuring a state’s progress over time will likely be useful to some extent given the significant variation in starting points across states. However, participants uniformly cited the value of benchmarking measures to national best practice standards or goals for helping to incentivize performance improvement and increasing the value of the measures. Participants also noted that these standards might evolve and adjust over time as states’ enrollment efforts progress. There was general consensus that a mix of both types of benchmarks would likely be most effective for understanding and measuring state performance. If performance measures are used to establish federal standards or requirements, it will be important to align these standards or requirements with program integrity efforts. States currently are subject to a wide variety of HHS program integrity efforts, which include a focus on identifying errors in eligibility determinations and can result in significant financial penalties for the states. Current program integrity efforts and error rates will have to be balanced against any new performance standards or requirements tied to states’ progress in developing the streamlined and simplified enrollment process required under health reform. Several participants noted that current program integrity measures might have to be revisited new performance standards are developed to ensure alignment in incentives and penalties.

CONCLUSION

Currently, there is limited capability at both the federal and state level to measure performance of Medicaid eligibility and enrollment systems. The implementation of health reform provides a unique and valuable opportunity to establish meaningful performance measures as states develop and implement new eligibility and enrollment systems. These measures will be important tools to help guide program management and continuous quality improvement and for understanding the impact of reform.

Setting clear expectations for performance measurement is key as many states have already begun planning and work to upgrade their systems and creating cross-program measures will require significant lead time, planning, and coordination across different groups within states, as well as with the federal government. Determining agreed upon measures now will both enable states to move forward and help establish a baseline set of measures against which ACA implementation can be tracked. Further, it might be valuable to phase in additional measures and/or reassess and adjust benchmarks over time as states fully implement their new systems, coordinate with the exchanges and the federal government, become more sophisticated in their reporting capabilities, and enroll millions of new individuals into health coverage.

This brief was prepared by Julie Hudman, principal at the Julie Hudman Group, Christopher Trenholm of Mathematica Policy Research, and Samantha Artiga of the Kaiser Commission on Medicaid and the Uninsured. The authors thank the federal and state officials, researchers, and other stakeholders who graciously shared their time and expertise. Moreover, they acknowledge the valuable work underway by Mathematica and the National Academy for State Health Policy as part of the Maximizing Enrollment project (http://www.maxenroll.org/), funded by the Robert Wood Johnson Foundation, which helped inform this work.

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The Kaiser Commission on Medicaid and the Uninsured provides information and analysis on health care coverage and access for the low-

income population, with a special focus on Medicaid’s role and coverage of the uninsured. Begun in 1991 and based in the Kaiser Family

Foundation's Washington, DC office, the Commission is the largest operating program of the Foundation. The Commission's work is

conducted by Foundation staff under the guidance of a bi-partisan group of national leaders and experts in health care and public policy.

This publication (#8269) is available on the Kaiser Family Foundation’s website at www.kff.org.