Understanding State Contexts for Benefit Administration

By Elizabeth Lower-Basch and Jesse Fairbanks

The United States’ core programs to help people with low incomes meet their basic needs for food, health care and income support are operated with substantial federal funding and oversight, but with extensive variation at the state (and in some cases, county) level. As a result, there is a significant difference in the experience of a low-income person seeking assistance depending on where they live.

This variation is most visible for Medicaid, where 12 states have failed to take up the expansion authorized under the Affordable Care Act, leaving millions of people uninsured and too poor to qualify for subsidies to buy insurance under the health care exchanges, and for cash assistance under the Temporary Assistance for Needy Families (TANF) block grant where states have full authority to establish benefit levels and eligibility rules. But it is also true for nutrition assistance under the Supplemental Nutrition Assistance Program (SNAP), even though the benefit levels are set at the federal level, benefits are fully paid for by the federal government, and states are not allowed to add additional eligibility requirements beyond those authorized in statute. This means that, in order to improve the delivery of these benefits, it is critical to understand what they look like in the states.

In this project, funded by the Bill and Melinda Gates Foundation, we sought to understand the variation across states and the factors that influence state administration of benefit programs. Some of these factors can be straightforwardly measured through available public data, while others will require consultations or analysis for each individual state. For some factors, the data we have collected provides a starting point, but additional research would be needed to fully understand the context.

We are making the compiled data available in the hope that it will be useful in the following ways, and perhaps others that we have not thought about:

  • State policymakers, administrators, or advocates trying to understand how their state compares to other states, looking for best practices, or seeking similar states with whom they might engage in peer learning opportunities;
  • Federal policymakers considering creating national requirements for these programs;
  • Researchers who want to quantify the variation across states for cluster or regression analyses; or
  • Philanthropic entities considering grants to state agencies or advocates to improve the delivery of benefits.

The measures of state contexts for benefits administration are divided into four broad categories:

1. Program participation and reach
2. Political and economic context
3. Governance, operations, and technology
4. State initiatives and policy choices and performance.

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Program Participation and Reach

  • States vary greatly in both their overall size and in their low-income population; obviously, the potential number of people helped by programs is greater in larger states with greater needs. Table G.PV.1 contains extensive data on the overall population and population in poverty by state.
  • SNAP is the only one of these programs for which the administering federal agency directly reports a measure of participation among eligible individuals. This information is shown in Table PS.1. Notably, states show a wide range of performance on this measure, from ~100% in several states to 52% in Wyoming in the most recent year for which data are available.1 Table P.S.2 combines this data on SNAP participation rates with the size of the underlying caseload to generate rough estimates of the number of eligible non-participants in each state.
  • For TANF, a readily used measure of program reach is the “TANF to poverty ratio” calculated by the Center on Budget and Policy Priorities as shown in Table P.T.1. This measure shows the number of families with children who receive TANF cash assistance for every 100 families with children with incomes under the federal poverty level. This measure ranges from 68 (in California) to 4 (in Louisiana and Texas). Note that because states set their own eligibility rules for TANF, this measure captures variation in both the share of families with low incomes who are eligible and participation among those who are eligible.
  • For Medicaid, it is difficult to calculate an overall participation rate for adults, because the eligibility rules vary so much among states. The Urban Institute calculates an estimate of participation among children eligible for coverage under either CHIP or Medicaid, as shown in Table P. M.2. The variation in this measure across states is smaller than for the other programs, but still shows meaningful differences, with several states reaching over 95 percent of eligible children, and Alaska, Utah and Wyoming reaching under 85 percent. P.M.3 reports the Kaiser Family Foundation’s estimate of the number of uninsured people in each state who are eligible for Medicaid or other public health programs, but are not covered.

Political and Economic Context

  • Are there identifiable champions for benefit access in the Governor’s office, critical state agencies, or key legislative roles? Has benefit access been included in a State of the State address or a strategic plan to address poverty, racial disparities, or children’s outcomes?
  • What is the overall political environment, and does it vary by issue? This includes overall orientation to issues affecting families with low-incomes and workers in the Governor’s office and the state legislature. It also includes the political salience of these issues, how they are framed, and how partisan they have become. For example, while some states historically had a bi-partisan focus on “good government” that allowed for cooperation across party lines, over the past decades many of them have become increasingly polarized.
    • Table A.PO.1 shows the political party of the Governor and party control of the state legislature. In general, our observation is that Democratic administrations and legislators are more likely to be willing to publicly advocate for benefit access, particularly around health care, given the way the ACA has assumed symbolic importance. However, the Work Support Strategies (WSS) project was successful in partnering with state agencies with both Democratic and Republican governors coming out of the 2008 recession, with different states choosing different framings (e,g., reducing bureaucratic duplication and obstacles vs. getting families all the help they need).
    • How salient is benefit access in the political debate? Salience can cut in either direction. Highly visible problems can increase the political will for the state to fix the system. On the other hand, the extreme political polarization around Medicaid has made it very difficult for states controlled by Republicans to make choices that improve access to Medicaid, while such states may still be able to expand access to SNAP which is less politically visible. For example, many states with both Democratic and Republican governors have both used “broad-based categorical eligibility” to expand SNAP access to people with higher gross income levels.
    • How is discussion around benefits framed? Is it focused around specific populations (children, seniors) or needs (health care, food) or more broadly around the economy or rights? Is the dominant discussion about preventing fraud?
    • Has the state expanded Medicaid, and was this politically controversial? Was it done through a ballot initiative rather than legislative or administrative action? (Table P.M.1 shows status of Medicaid expansion.)
  • Will leaders remain in office long enough to effect change? Are they early enough in their administration to be looking for initiatives to own/ not be defensive about past actions? (Table A.PO.1 also shows the year each Governor took office, the date of the next Gubernatorial election and whether they are term limited.) The administration of a governor who will be leaving office due to term limits in a year or two is less likely to be able to manage a major project to completion.
  • Does the state recognize the importance of using a racial equity lens to diagnose problems in its benefit delivery systems? Given the profound impact of systemic racism in both the broader economy and in the development and operations of public benefit programs, a race neutral approach to reform is likely to perpetuate current inequities. While we would need to interview leadership to answer this question, Tables A.RE.1 and A.RE.2 identify states that have declared racism a public health emergency or explicitly built a racial equity framework into their COVID-19 response, which gives a starting point for this analysis.
  • What is the overall economic context? Is the state facing fiscal constraints that limit its capacity to invest in improving benefit access? Is there a concern about making policy or practice changes that would increase the cost of providing services? (Note: SNAP benefits are 100% federally funded, but states share in the cost of administration. States share in the costs of Medicaid, and TANF is a block grant, meaning that states bear the entire burden of providing additional benefits.) While fully answering this question would require state-specific conversations, table A.RB.1, shows how states’ unemployment rates varied during the pandemic and how states’ tax revenue varied in 2020 compared to the previous year.

Governance, Operations and Technology

  • Who has the power to make the decisions? Are all the key players supportive? How do they work together?
    • In some states, the legislature has passed laws explicitly limiting the administration’s ability to make changes in programs. Most prominently, seven states have passed laws that prohibit the Governor from requesting a waiver of the SNAP time limits for “able bodied adults without dependents.” (ABAWDs). Other examples include laws requiring the Governor to request and implement Medicaid waivers. These restrictions are most salient in the handful of states where the Governor’s party does not also control the legislature. (Table A.PO.2)
    • If the legislature is supportive of benefit access, do the champions work cooperatively with state agencies or are there tensions?
    • What is the role of local decision-making? Ten states are formally considered “state-supervised, county administered” for SNAP and TANF. That means that enrollment processes are conducted by county employees in county-run offices. Many of the largest states are in this category, and while there is significant variation among these states, any initiative needs to have a county as well as state focus since state agencies have limited ability to make changes in those states without county buy-in (Tables A.S.1 and A.T.1 show the distribution of responsibilities in SNAP and TANF respectively). In other states, even without formal county administration, local offices may still have significant independence, particularly if they have political ties (e.g. to state legislators).
  • What agencies are involved in aspects of program policy, technology, and operations? All else equal, it is usually easier to align the client experience and to make changes in multiple programs at once when they are administered together.
    • Are health care and human services eligibility processes administered by the same agency? We were not able to directly answer this question for all states, but in most cases, the question of whether the same IT system determines eligibility acts as a proxy for this.
    • Are multiple programs in the same online application? (See Table A.TE.1, which contains information collected by Code for America as part of their review of online applications).
    • Does the same IT system determine eligibility across health and human service programs? Table A.TE.2, attempts to answer this question with data drawn from both the health care and SNAP sides. Note that there are some states where the two sources give different answers.
    • Are the eligibility workers who process cases in different programs in the same job classification, and would changes need to be negotiated with a union?
  • Whether or not they are formally within the same agency, is there a history of internal coordination? Are there standing working groups or teams charged with coordinating across programs? Or other kinds of governance structures? Experts suggested that this could be evaluated in part by asking a state team to convene a cross-agency meeting as part of a site visit.
  • How easy or difficult is it for the state to make modifications to the eligibility systems? This can be a function of many factors, including the age and design of the system, the contract with the vendor, the specific staff that support the project, and the number of projects that are already on the “runway.”
    • How old are the eligibility systems? Did the state take advantage of the 90% federal funding for Medicaid eligibility systems and waiver of cost allocation requirements under OMB Circular A-87 to modernize across programs? Is the state already planning a major overhaul or system upgrade soon? What changes are planned?
    • Who “owns” the eligibility system(s) and negotiates with the vendor for any required changes? In some states, this is handled by each agency, while in others a central IT agency procures systems for all states agencies. California is unique in having multiple systems, owned by county consortia.
  • Is the agency (or agencies) interested in improving their outcomes? Are they tracking progress on factors other than the federally required measures in internal or external dashboards? Do they look at information across programs or in silos? Do they disaggregate data by race or other key demographics?
  • Is there an existing process for bringing together policymakers, technologists, and operational experts to analyze proposed changes collectively? While sometimes policymakers deliberately use administrative burden to limit access to programs, at other times they make decisions without understanding the operational consequences. At other times, policy choices are inadvertently left to contractors developing IT systems because the parameters have not been sufficiently described in the specifications.
  • Does the agency have the capacity to run ad hoc queries about the performance of their programs? This could be constrained by either technology or lack of personnel with the needed skills. Experts suggested that this could be evaluated in part by asking a state to pull data on their programs for a site visit.

State Initiatives and Policy Choices

  • Has the state participated in a previous benefit access initiative, such as Work Support Strategies or the Integrated Benefits Initiative (See Table A.PP.1)? What were the outcomes? Were changes that were made sustained? Was the process of making changes sustained? Why or why not?
  • What is the agency’s history of performance in rolling out new programs or systems? What challenges did they encounter? Is there evidence that they learned from past problems? Have there been major leadership changes since?
  • Has the state incorporated client perspectives into its work, such as through human centered design or a participant advisory board?
  • Has the state adopted state options to maximize client access and reduce burden? Many policy choices, such as the requesting of Medicaid work reporting requirement waivers, use of available waivers of the 3 month SNAP time limit for non-working “able bodied adults without dependents” (currently suspended due to COVID) or the use of Broad Based Categorical Eligibility to remove asset limits and raise the SNAP gross income limit both directly affect eligibility and also impact the documentation burden on those who remain eligible (Tables A.S.2, A.M.1, A.M.2). Researchers have created an “Medicaid Accessibility Index” (Table A.M.3) that traces state policies as documented in the KFF annual report on state eligibility and enrollment policies and practices over time, including an Administrative Burden subindex. However, the ACA required all states to drop asset limits and in person application requirements for MAGI Medicaid eligibility, making this index no longer as meaningful as it once was.
  • Has the state used—and continued to use – the flexibilities allowed as a result of COVID-19 to maximize benefit access during the pandemic? Information on what waivers each state has received is available, however, our conversations with state advocates suggest that these waivers do not always accurately reflect the situation on the ground. For example, some states with waivers that allow them to postpone redeterminations under SNAP, are nonetheless terminating people for failure to return these forms. It may be more meaningful to simply look at what has happened to caseloads during the pandemic (Table P.S.3), whether states are continuing the public health emergency declarations that allow for emergency allotments (Table A.S.4), and their plans for reviewing eligibility when the Medicaid MOE requirement (which prevents people from being terminated from Medicaid during the Public Health Emergency unless they leave the state or request case closures) ends.
  • Under Pandemic EBT, were states able to do data matching to identify students receiving free or reduced-price lunches, or did they require non-SNAP families to submit applications (Table A.S.3)?

To gain access to any of the tables mentioned in this report, please complete this brief google survey: