Supplemental Security Income: SSA Provides Benefits to Multiple Recipient Households but Needs System Changes to Improve Claims Management
Released: 2016-09-15T00:00:00

Letter

Background

The SSI program was established in 1972 under Title XVI of the Social Security Act and provides payments to low-income aged, blind, and disabled persons—both adults and children—who meet eligibility requirements. SSA administers the SSI program through more than 1,200 field offices around the country where staff process applications for benefits, verify financial eligibility, and compute benefit amounts. Following SSA’s initial review, state disability determination services offices assess applicants’ medical eligibility for SSI. In order to be eligible for SSI benefits based on a disability, an individual must have a medically determinable physical or mental impairment that (1) prevents the individual from engaging in any substantial gainful activity, and (2) has lasted or is expected to last at least 1 year or result in death. After a person is found to be eligible for SSI and begins receiving benefits, SSA conducts periodic redeterminations of financial eligibility and continuing disability reviews to ensure that only recipients who remain medically eligible continue to receive SSI benefits.

Determination of Financial Eligibility and Benefits

To be financially eligible for SSI, individuals must meet program income and resource requirements. Specifically, in 2016, an individual recipient’s or married couple recipient’s monthly countable income must be less than the maximum monthly federal SSI benefit rate of $733 per month for an individual and $1,100 per month for a married couple. Generally, SSI recipients are eligible to receive up to a maximum benefit rate, with married couple recipients eligible for a lower maximum benefit rate approximately equal to 75 percent of the benefit rate for nonmarried individuals. Further, an individual’s or couple’s countable resources (such as financial institution accounts) must be $2,000 or less for individuals and $3,000 or less for married couple recipients in 2016.

Although SSI is a benefit for an individual, SSA generally considers income of certain other people in the household when determining the amount of an individual’s SSI benefit to reflect a family member’s responsibility for certain other family members. For example, a parent’s or spouse’s income is generally included as part of the income of a child or spouse, respectively, living in the same household. Therefore, if the SSI recipient lives with a spouse who does not receive SSI benefits, SSA considers the income of that spouse when determining the recipient’s SSI benefit amount, potentially reducing the benefit payment.

Similarly, food and shelter that an individual receives from others, referred to as in-kind support and maintenance (ISM), is also considered by SSA when determining an individual’s benefit amount. In situations where the householder is providing both food and shelter to an individual, SSA decreases the recipient’s SSI benefit by an amount equal to one-third of the federal benefit rate to account for ISM. In all other situations in which an individual is receiving ISM, SSA counts the presumed value of the food or shelter-related items received by the SSI recipient in-kind (including such assistance provided by individuals who do not live with the recipient) as unearned income, unless the recipient demonstrates that the actual value is less than the presumed value, in which case SSA uses the actual value. However, the amount that the recipient’s SSI benefit may be reduced in this manner is limited to an amount equal to one-third of the applicable benefit rate plus $20.

Overview of SSA’s Claims Management System

SSA operates two separate, but linked, systems to update and store SSI recipient information and process benefits: the Supplemental Security Record (SSR) and Modernized Supplemental Security Income Claims Systems (MSSICS). Field office staff use SSR to calculate benefits, including any reductions to benefits from ISM, based on information retrieved from MSSICS. MSSICS, an online data collection system, is used by field office staff to collect recipient information. MSSICS houses data such as whether the individual lives alone, owns a house, has certain kinds of expenses, and what, if any, financial support the person receives from others. MSSICS stores information like a paper file. When SSA staff need to update records, they can open the recipient’s file and make changes electronically. Overall, SSA’s database systems are 40 years old, and the agency plans to expand their capabilities through a multiple-year initiative beginning in fiscal year 2017.

Programs for Low-Income Individuals and Families

We previously reported that SSI is one of over 80 federal programs that target low-income individuals, families, and communities to help them meet basic needs or provide other assistance. We reported that financial and nonfinancial eligibility requirements are established for each program, with financial requirements generally limiting eligibility to individuals, families, or households with income and assets below defined levels. In some circumstances, federal law extends automatic eligibility for one program for low-income people based on an applicant’s participation in another program. Such provisions can simplify the application and eligibility determination process for applicants and reduce the time program administrators spend verifying applicants’ income and resources. In most states, SSI recipients are automatically eligible for Medicaid health insurance and, if they live alone or in households in which all members receive SSI benefits, are automatically eligible for the Supplemental Nutrition Assistance Program (SNAP).

Medicaid is a joint federal-state program that finances health insurance coverage for certain low-income individuals. An estimated 65 million low-income individuals were covered by Medicaid in fiscal year 2014, and the Centers for Medicare and Medicaid Services report that enrollment has been growing under the Patient Protection and Affordable Care Act. Medicaid allows significant flexibility for states to design and implement their programs; however, each state Medicaid program, by federal law, must cover certain categories of individuals and provide a broad array of benefits. Medicaid benefits are not adjusted based on an eligible individual’s income level.

SNAP is intended to help low-income households obtain a better diet by providing benefits to purchase food. SNAP is the largest of 15 domestic food and nutrition assistance programs overseen by the U.S. Department of Agriculture’s Food and Nutrition Service. States administer the program by determining whether households meet the program’s eligibility requirements, calculating monthly benefits for qualified households, and issuing benefits to them. A household generally includes everyone who lives together and purchases and prepares meals together. An SSI recipient is generally automatically eligible to receive SNAP benefits, if they live alone or in households in which all members receive SSI benefits, and an individual’s monthly SSI benefit is counted as income when determining the individual’s SNAP benefits. In contrast, for the purposes of SSI benefit determination, the amount of SNAP benefits an SSI recipient receives is excluded.

Medicaid and SNAP are not the only other federal assistance programs available to aged, blind, or disabled individuals with limited means. For example, monthly cash assistance is available to qualifying low-income families with children through the Temporary Assistance for Needy Families (TANF) block grant, administered by the U.S. Department of Health and Human Services (HHS). TANF provides federal funding to states, which states are required to supplement with their own funds, to provide cash assistance and a variety of other benefits and services to meet the needs of low-income families with children. In addition to eligibility requirements related to the target population, TANF includes both work requirements and requirements related to time limits on individuals’ receipt of TANF cash assistance benefits. While there is no federal prohibition to simultaneous SSI and TANF eligibility, most states prohibit payment of TANF benefits to SSI recipients, according to HHS. If an SSI recipient does receive TANF cash assistance benefits, that person’s benefit is counted dollar for dollar as income during SSI eligibility and benefit amount determinations.

Multiple SSI Recipient Households Represented an Estimated 15 Percent of All SSI Households in May 2013

Households with Multiple SSI Recipients Represented an Estimated 15 Percent of All Households with SSI Recipients and Typically Included Two Nonmarried Recipients

In May 2013, an estimated 15 percent of all households with SSI recipients included more than one SSI recipient (1.1 million households), according to our analysis of matched administrative and survey data. Specifically, households with married couple recipients represented an estimated 1.2 percent of all SSI recipient households; while 13.8 percent of SSI households were comprised of nonmarried multiple recipients (see fig. 1). Households with nonmarried multiple recipients include combinations of related or unrelated recipients living together, such as parents and children, siblings, or roommates. The vast majority of multiple recipient households reported having a one-family household (an estimated 86.7 percent or 941,000 households), with “family” defined as a group of two or more persons related by birth, marriage, or adoption who reside together. Based on our analysis of households with SSI recipients, we were unable to detect any changes in the proportions of one recipient and multiple recipient households, respectively, from 2009 to 2013.

A vast majority of multiple recipient households had two SSI recipients (see fig. 2). Specifically, an estimated 953,000 of the 1.1 million multiple recipient households in May 2013 included two recipients, while an estimated 131,000 households included three or more recipients.

SSI recipients living in multiple recipient households often shared their households with other individuals who did not receive SSI benefits (non- recipients). Almost two-thirds of multiple recipient households included at least one non-recipient (see fig. 3) and, as previously noted, most multiple recipient households reported being members of one family. As such, multiple recipient households may include a parent and child who both receive SSI benefits along with another parent who does not receive benefits, for example.

Most Multiple Recipient Households Included Adult Recipients Who Did Not Have Any Earned Income

An estimated 695,000 of 1.1 million multiple recipient households included at least one working-age adult recipient in May 2013 (see fig. 4). The most common recipient groupings in multiple recipient households were two or more working-age adult recipients or two or more elderly recipients. It was less common for multiple recipient households to have multiple generations of SSI recipients present, such as a combination of working-age adult recipients and child recipients, or working-age adult and elderly recipients.

Although representatives from some stakeholder groups and staff we interviewed at all five SSA field offices noted that, in their experience, multiple recipient households commonly included children, we found that an estimated 69.5 percent of multiple recipient households in May 2013 had no child recipients present (see fig. 5). For multiple recipient households with SSI recipient children in May 2013, most included only one child recipient, and it was rare for these households to have three or more child recipients.

Although SSA reports that a slightly greater percentage of SSI recipients were female, according to our analysis, a slightly greater percentage of SSI recipients in multiple recipient households were male in May 2013. Specifically, SSA reported that 53.4 percent of all SSI recipients were female in December 2013, and we found that 54.0 percent of SSI recipients in multiple recipient households were male in May 2013. This may be related to the fact that child SSI recipients were twice as likely to be male, according to SSA, and child recipients made up a slightly greater proportion of recipients in multiple recipient households than in the SSI recipient population as a whole, according to our analysis.

The majority of multiple recipient households—an estimated 87.9 percent of which had two SSI recipients—reported no earned income and some unearned income in May 2013. Further, the percentage of households that reported earned income and the average amount of earned income per household were similar across one recipient and multiple recipient households (see table 1). In contrast, although the majority of both one and multiple recipient households reported receiving unearned income, the average amount of unearned income reported by multiple recipient households was greater than that reported by one recipient households.

Recipients’ Living Arrangements May Be Driven by Various Factors

According to staff from SSA headquarters and our selected field offices, as well as disability rights advocates, and researchers, SSI recipients may make living arrangement decisions for various reasons. These may include family relationships and the role of genetics in the development of similar health conditions among family members. Married couples, parents and children, and extended families often share households because they are related. Further, some researchers we spoke with suggested that shared genetic conditions among parents or siblings could result in multiple members of the same household having the same disability, or a disability on the same illness spectrum.

The potential network effect resulting from individuals living in close proximity and sharing information was another factor cited by groups we spoke with that may increase the likelihood of SSI recipients living together. Network effects potentially reduce perceived barriers to applying for benefits for individuals who may be eligible, and could increase the prevalence of multiple recipient households. Specifically, SSA field office staff and representatives of a disability rights advocate group we spoke with described word-of-mouth communication among potentially eligible individuals as one way that applicants learn about the SSI program. According to one researcher we spoke to, some applicants may hear from others how to navigate the application and appeals process for SSI benefits, thus increasing their likelihood of applying.

The supportive care that comes from living with others may also contribute to SSI recipients choosing to live together. According to disability advocates we spoke to, SSI recipients may group themselves into a community to increase connectedness, decrease isolation, and receive supportive care when needed. In addition, one researcher told us that SSI recipients might also need assistance coordinating care or arranging appointments, and SSI recipients with different impairments may fulfill complimentary functions for other household members.

A range of the stakeholders we spoke to, including SSA field office staff, disability advocates, and researchers, stated that economic factors may also contribute to the living arrangement decisions of SSI recipients. Specifically, according to these groups, SSI recipients may choose to live together in order to pool resources to share rent and other household expenses such as utilities or food. Additionally, current fair market rent levels often exceed SSI benefit rates, research shows. For example, according to one study, the national average fair market rent for one bedroom rental units was $780 in 2014, and for studio/efficiency rental units was $674 in 2014, or about 104 percent and 90 percent, respectively, of the maximum monthly SSI benefit payment in that year.

In addition, SSA headquarters and field office staff, disability rights advocates, and researchers, with whom we spoke, stated that the recession may have exacerbated the economic factors that contribute to living arrangement decisions for SSI recipients. However, one researcher we spoke with noted that the effects of the recession varied by state. According to our analysis of matched administrative and survey data, the rate of multiple SSI recipient households with two families present decreased from an estimated 26 percent in 2010 to an estimated 10 percent in 2013. This suggests that the 2007 to 2009 recession may have played a role in the family composition of households, which is consistent with other research that has found low-income people tend to combine households during recessions.

Other factors related to the location and features of housing may influence SSI recipients’ living arrangements, according to the groups with whom we spoke. In particular, these factors may contribute to a greater prevalence of multiple SSI recipient households in certain neighborhoods. For example, location-related factors noted by those we spoke with included proximity to accessible infrastructure and public systems such as transportation and schools. In addition, SSI recipients may need to live in housing units with universal accessibility features such as no-step entry, single-floor living, lever-style door handles, accessible electrical controls, and extra-wide doors and hallways. However, one study found that in 2011 less than 1 percent of U.S. rental housing units—roughly 365,800 units—included all five of these accessibility features.

Multiple Recipient Households Received an Estimated 30 Percent of All SSI Benefits in May 2013

In May 2013, the estimated 15 percent of all SSI households that had multiple recipients received an estimated 28.6 percent of all SSI benefits, or approximately $1.2 billion, according to our analysis of matched administrative and survey data. (See fig. 6.) Because the total amount of SSI benefits received by a household includes benefits for all recipient residents, households with multiple recipients received higher monthly average SSI benefit payments (an estimated $1,131) compared to households with one recipient (an estimated $507).

Marital status was also associated with different household benefit amounts. Households with nonmarried multiple recipients received a higher estimated average monthly benefit payment than married recipient households (see table 2). This is consistent with federal statute which stipulates a lower maximum benefit rate for married couple recipients, and those rates were $1,066 per couple or $533 per recipient in 2013. In comparison, all other recipients were not subject to this reduction and were eligible to receive up to $710 in 2013.

Households typically received SSI benefits close to the maximum benefit for which their recipients were eligible. For example, in May 2013, monthly benefit amounts for most multiple recipient households were over $1,000, while monthly benefit amounts for most households with one recipient were between $500 and $999. (See fig.7) These findings show a concentration of households received benefits in the range of SSA’s 2013 maximum benefit rates for individuals and married couple recipients. These data on benefit amounts for households with one or multiple recipients are also consistent with our finding that an estimated 87.9 percent (953,000) of multiple recipient households had two SSI recipients in May 2013.

Child SSI recipients received the highest estimated average monthly SSI benefit amounts, regardless of whether they were the only recipient in a household or lived in a multiple recipient household (see fig. 8). Elderly SSI recipients received the lowest estimated average monthly benefit amounts. According to SSA officials, children receive higher SSI benefit amounts because they are less likely to have other sources of countable income that would reduce their benefits. According to SSA’s 2013 SSI Annual Statistical Supplement and Report, about 28 percent of all SSI recipients age 17 or younger had some other countable income, compared to about 43 percent of adults ages 18 to 64, and 69 percent of recipients age 65 or older. Further, about two-thirds of all child recipients lived with one parent, and almost half of those parents had no other countable income.

The Effects of Changing Benefits for Multiple SSI Recipient Households Are Largely Unknown, and SSA Has Limited Ability to Electronically Manage Claims for Some of These Households

Options for Restructuring Benefits for Multiple SSI Recipient Households Have Been Discussed, but the Effects on SSI Program Costs, Households, and Other Programs Are Largely Unknown

Since the 1990s, members of Congress, SSA officials, and some advocacy groups have discussed alternative benefit structures for individuals living in multiple recipient households. Based on our interviews with SSA headquarters and field office staff, researchers, and representatives of advocacy groups, these previously considered alternatives generally involved either eliminating the benefit reduction for married recipients—so married recipients would have the same maximum benefit rate as individual recipients—or applying a similar reduction to other multiple recipient households. Although these alternatives have not been fully studied to determine the effects they may have on SSI recipients or SSA’s administration of the program, there is some information available on their potential effects on recipients and the program.

Eliminating the Benefit Reduction for Married SSI Recipients

Eliminating the benefit reduction for married SSI recipients—so they would have the same maximum benefit rate as individual recipients— would increase benefit equity, simplify administration of the program, and also likely increase benefit costs, according to SSA staff and other groups with whom we spoke and research we reviewed. Because married recipients have a lower maximum benefit rate than nonmarried recipients, most disability advocates and researchers we spoke with said that married recipient households are treated inequitably. Further, according to SSA, the current benefit structure has led to some SSI recipients reporting a change in their marital status to avoid the benefit reduction. Specifically, SSA officials in 3 of the 5 selected field offices said that some SSI recipients, upon learning of the married couple benefit reduction, shortly thereafter return to the SSA office to tell SSA staff they have separated and are no longer living together. According to SSI policy, the benefit reduction no longer applies if the SSI recipients divorce or no longer live in the same household, for example. Eliminating the benefit reduction for married SSI recipient households would also simplify program administration overall, according to SSA headquarters staff, because there would then be one maximum benefit amount that applies to all recipients. However, such a change for married recipients would also likely increase SSI benefit costs. According to a 2003 SSA study, eliminating the benefit reduction policy for married recipient households could increase program costs by more than $900 million annually.

Reducing the Maximum Benefit Rate for Other Households with Multiple SSI Recipients

Other alternative SSI benefit structures that have been considered focused on reducing the maximum benefit rates for different groups of nonmarried multiple recipient households. For example, the 1995 National Commission on Childhood Disability suggested reducing the maximum SSI benefit rate for households with multiple child SSI recipients. Another alternative described by SSA in 2008 would replace the policy under which an SSI recipient’s benefits are reduced to account for any in-kind support and maintenance they receive with a benefit reduction for all adult recipients living with other adult recipients. The report noted that administering the in-kind support and maintenance policy often requires month-to-month, recipient-by-recipient recomputations based on information that is unverifiable. In addition, we have previously reported that administering the in-kind support and maintenance policy has become increasingly complex and is a primary cause for overpayments. Another suggested alternative included applying a reduced maximum benefit rate to all households with two or more SSI recipients, which SSA examined in 2002.

Potential Effects on Benefit and Administrative Costs If the maximum benefit rate for additional multiple SSI recipient households was reduced, SSI benefit costs would likely decrease, according to analyses we reviewed. Although not all of these alternative benefit structures have been analyzed for cost savings, those that have provide some information on potential savings. For example, the Congressional Budget Office estimated a cost savings of approximately $4.6 billion from fiscal years 2013 through 2022 if the benefit reduction for households with multiple SSI children suggested by the 1995 National Commission on Childhood Disability were to be implemented. Further, SSA’s Office of the Inspector General estimated a cost savings of approximately $3 billion for calendar year 2011 if the reduced maximum benefit rate for married SSI recipients was extended to all households with two or more SSI recipients.

SSA headquarters officials we spoke with reported that savings in benefit costs resulting from a reduction in the maximum benefit rate for additional multiple recipient households may be tempered by increases in administrative costs; however, SSA has no estimates to help determine any potential effect. SSA staff we spoke with in 3 of the 5 field offices said changing benefits for some SSI recipients also could result in an increase in field office workloads. For example, staff from these three field offices said a change in the maximum benefit rate for some SSI recipients would result in more recipients visiting their field offices, and some added that there would be a need for new training for field office staff and outreach to inform recipients about the change. However, SSA has not previously assessed how field offices may be affected by changes in SSI policy, and therefore the full effects of extending the reduced maximum benefit beyond married SSI recipients on administrative processes and related program costs are unknown.

Potential Effects on SSI Recipients Concerning the potential effects on recipients of a reduction in the maximum benefit rate for multiple recipient households, some of the groups we spoke with discussed how such a change may affect recipients’ financial situations, though research on these effects is limited. The reduced maximum benefit rate for married couple SSI recipients is based on the expectation that these couples realize economies of scale, according to previous SSA reports. In other words, married SSI recipients who live together are able to share certain household expenses, thus reducing the overall cost of housing and living expenses for each individual. Consistent with this, some SSA officials and researchers we spoke with told us that some multiple recipient households economize on living expenses, such as rent and food. However, disability advocacy officials from two organizations said that while recipients may share a living space, there may be certain out-of-pocket expenses that cannot be shared, such as medication or specific dietary requirements. While a 2006 report from SSA found that medical expenses for the majority of child SSI recipients were covered by health insurance rather than their SSI benefits, the extent to which multiple recipient households realize economies of scale, and for what purposes recipients in these households use their SSI benefits, have not been studied, according to SSA officials and several researchers.

A reduction in the maximum benefit rate for multiple recipient households may lead some SSI recipients to alter their living arrangements, according to groups with whom we spoke. Although the extent to which a benefit reduction leads to such changes has not been studied, as mentioned earlier, SSA field office staff told us that some married SSI recipients attempt to avoid the benefit reduction by telling SSA staff they have separated and are no longer living together. If a reduction in the maximum benefit rate is extended to include other multiple recipient households, affected SSI recipients may similarly take steps to avoid the benefit reduction, according to disability advocates, researchers, and SSA field office staff with whom we spoke. For example, some SSA field office staff said that families living with multiple SSI children may move their children to live with relatives to avoid a reduction in SSI benefits.

Potential Effects on Other Federal Programs for Low-Income Households and Individuals Because SSI recipients may be eligible to receive benefits from other federal programs for low-income households and individuals, these programs may be affected if a reduced maximum SSI benefit rate were to be extended to additional multiple recipient households, though the effects would likely vary by program. Federal programs that these households may also receive benefits from include, for example, Medicaid, TANF and SNAP. While the effects of changes in other federal means-tested programs, such as TANF, on SSI have been studied to some extent, the reverse effect of SSI benefit changes on other federal programs has not. However, based on our assessment of relevant laws, regulations, other reports, and data for selected programs, the effects of a reduced SSI maximum benefit rate on other programs would likely vary based on each program’s structure and rules and the extent to which SSI recipients already receive benefits from these other programs.

Medicaid, which many SSI recipients concurrently receive, would likely be minimally affected by the extension of the reduced maximum benefit rate to other multiple recipient households, based on our review of relevant program laws, regulations, other reports, and data. In most states, SSI recipients are automatically eligible for Medicaid, and many currently receive Medicaid benefits. For example, according to one SSA study, approximately 80 percent of individuals ages 18 to 64 received Medicaid coverage within a year of being deemed eligible for SSI. Therefore, a reduction in SSI benefits may result in the small proportion of SSI recipients who are not currently enrolled in Medicaid applying for the program and receiving coverage. Further, because Medicaid benefits are adjusted based on eligibility and not on income level, an SSI recipient’s Medicaid benefits would not be affected by a reduction in their SSI benefits so long as the recipient remains eligible for SSI.

TANF, which SSI recipients generally do not concurrently receive, would also likely be minimally affected by a reduction in the maximum benefit rate for additional multiple SSI recipient households, based on our review of relevant program laws, regulations, other reports, and recipient data. Although the federal government sets some requirements for TANF, states have broad flexibility to design their TANF programs, and most states do not allow individuals who receive SSI to simultaneously receive TANF monthly cash assistance benefits, according to the Department of Health and Human Services. However, other family members, living in households with SSI recipients, may receive TANF cash assistance benefits. The Department of Health and Human Services reported that about 267,000 child-only TANF families had a parent or adult caretaker who received SSI in fiscal year 2013. In contrast with Medicaid, TANF benefits are generally adjusted based on a family’s income level, and for child-only TANF cases, the income and assets of the parent or adult caretaker is factored in when determining the child’s TANF benefit. Therefore, TANF cash assistance benefits received by family members living in a household with multiple SSI recipients may increase if a family member’s SSI benefit was reduced. However, given that federal funding for TANF is provided through a block grant to states, the amount of federal spending on TANF is not adjusted for changes in cash assistance benefits provided to eligible families.

In comparison with Medicaid and TANF, SNAP is more likely to experience an increase in program spending if a reduction in the maximum SSI benefit rate is established for additional multiple recipient households, based on our review of relevant program laws, regulations, other reports, and recipient data. Similar to Medicaid, SSI recipients can be automatically eligible for SNAP. According to a report by USDA, 82 percent of individuals in households with SSI recipients received SNAP benefits in fiscal year 2013. Further, according to SNAP administrative data, about 4.5 million households receiving SNAP benefits included at least one member who also received SSI benefits in fiscal year 2013. For the group of SSI recipients who do not receive SNAP benefits, a reduction in SSI benefits may cause them to apply for these benefits. In addition, because SNAP benefit amounts are adjusted based on household income, a reduction in SSI benefits would likely increase a household’s SNAP benefit, unless the SSI recipient’s household already receives the maximum SNAP benefit amount. According to SNAP administrative data, the average monthly SNAP benefit received by households with SSI as a countable income source was $205 in fiscal year 2013. Further, these data show that 15.4 percent of households with disabled nonelderly individuals received the maximum SNAP benefit that year, compared to 40.7 percent of all SNAP households. Although a reduced maximum SSI benefit rate for additional multiple SSI recipient households may therefore result in increased federal spending on SNAP, federal spending may decrease overall. Specifically, due to the way SNAP benefits are structured, each lost dollar in SSI benefits would represent less than one additional dollar gained in SNAP benefits.

SSA Has Limited Ability to Electronically Manage Claims for Multiple Recipient Households

SSA’s claims management system, which is comprised of MSSICS and the SSR, is not able to automatically update the claim records for recipients living in multiple recipient households. SSA officials told us the claims management system was designed to manage the claims of, and pay benefits to, individual recipients. When SSA conducts periodic redeterminations of SSI recipient claims, or SSI recipients inform SSA of changes in their income or living arrangements, field office staff said they update recipients’ claims to ensure the correct benefits are paid. However, SSA headquarters and field office staff told us the system does not have the ability to automatically connect and adjust the claim records of individuals living in multiple recipient households. Although changes to one of the SSI recipient’s income or living arrangements in a multiple recipient household may affect another recipient’s claim in that household, SSA headquarters officials stated that staff have to go into each record separately to update each recipient’s benefits. For example, if a mother lives with two of her children who are both SSI recipients, and the mother reports a change in her earned income, SSA’s system does not automatically adjust both children’s benefit amounts to account for the mother’s change in income. Rather, while the system will add the new income information into all relevant claims records, staff need to go into each record separately to process the change. Further, if SSA field office staff do not go into a claim record to process such a change, the system does not alert them to do so. Without the ability to automatically connect and adjust the claim records for individuals living in multiple recipient households whose benefits are inter-related, SSA is at increased risk for improper payments because staff may not adjust benefits for all recipients in a multiple recipient household after a relevant change.

Furthermore, SSA staff reported that processing claims for SSI recipients who marry another recipient or separate from another recipient are not possible in the claims management system. Field office staff must process these claims manually, outside of the claims management system, according to SSA headquarters officials and staff from 3 of the 5 field offices with whom we spoke. For these claims, they said field office staff must manually complete forms to gather recipient information, calculate benefits outside the claims management system, and then enter the information into the system. Although SSA officials stated SSA provides training on how to use the forms, staff from 3 of the 5 field offices with whom we spoke said they rely on more seasoned field office employees to demonstrate how to properly complete these forms. Further, staff from 3 of the 5 field offices we spoke with told us that manually processing these married and separating recipient household claims are a common part of their daily work. Although an SSA official told us that improper payments made in married couple claims in fiscal year 2014 were attributed to recipient errors, staff from 3 of the 5 SSA field offices with whom we spoke said processing claims outside of the claims management system is time consuming and error prone. This issue may be exacerbated in the near term due to the Supreme Court ruling recognizing the right of same-sex couples to marry, a concern specifically noted during one of our interviews with field office officials.

SSA has no plans to update its claims management system to address issues with processing claims for multiple recipient households, including marrying and separating recipients, although the agency has broadly committed to improving other areas of its technology infrastructure. SSA officials told us that they have not conducted any specific assessments of the effects manual payment processing for multiple recipient household claims has on claim processing errors or improper payments as part of their payment accuracy reporting. SSA officials explained there is no program requirement to have the claims management system connect the records of individuals living in multiple recipient households, and they do not plan to make changes to do so. Yet, SSA has previously stated its commitment to investing in the capacity and modern technologies needed to update its aging and strained IT infrastructure. Furthermore, in its 2017 budget request, SSA stated its data systems are no longer the best solution to administer the agency’s programs, and added that it plans to undertake a larger, multiyear reform effort. According to our Organizational Transformation: A Framework for Assessing and Improving Enterprise Architecture, improving an agency’s enterprise architecture is an essential means to having operations and technology environments maximize institutional mission performance and outcomes. Moreover, Standards for Internal Control in the Federal Government states that agencies should identify and address risks to achieving their objectives, including significant changes to both external and internal conditions, as well as design their information systems to support the completeness, accuracy, and validity of information needed to achieve objectives. The increased opportunities for improper payments resulting from the claims management system’s limitations in updating and processing benefit claims for those living in multiple SSI recipient households is a risk to SSA’s overall goal of strengthening the integrity of SSA’s programs. According to staff at 2 of the 5 field offices with whom we spoke, fully automating the payment process for all claims and electronically connecting the records for multiple recipient households would make processing these claims more efficient and lower the number of improper payments by reducing errors in claims processing. However, SSA has not assessed the risks these systems limitations pose, despite its plans to make changes to its data systems. Absent such an assessment and without upgrades to the claims management system, SSA is missing an opportunity to improve its day-to-day work processes. Further, the agency will likely continue to experience related claim processing errors and improper payments, both under current program policies, as well as in the event related policy changes are implemented in the future.

Conclusions

Although SSI provides cash assistance benefits to individuals, it is not surprising that some SSI recipients live together due to family relationships or economic and social factors. Any household with more than one member may potentially experience economies of scale, and when the SSI program was created, it included a lower maximum benefit rate for certain married couple recipients. However, despite the fact that the majority of households with multiple SSI recipients report including members of only one family, few report that they include married couple recipients. This raises questions for some about benefit equity and disincentives to marriage, as well as the ability of program administrators to effectively determine a recipient’s marital status. Although the potential effects of various benefit restructuring options have not been fully studied, our finding that households with multiple SSI recipients receive almost 30 percent of all SSI benefits suggests that changing the benefit structure for all or some of these households may have a significant effect on benefit costs. Further, regardless of whether a change to benefits for households with multiple recipients is made, there are limitations in SSA’s information systems with managing claims for SSI recipients who live with other recipients, which puts the agency at risk. However, absent a risk assessment, SSA lacks information on the impact current systems limitations may have on improper payments. The recent Court ruling recognizing the right of same-sex couples to marry also likely increases opportunities for improper payments to SSI recipients, because of the expected increase in the number of claims SSA staff must process manually due to the system’s constraints in converting claims for individual recipients to married couple recipients. Despite reported plans to upgrade SSA’s aging technology systems, SSA currently does not have plans to address issues related to processing claims for SSI recipients who live with other recipients, leaving the program at risk for improper payments. Should Congress choose to revise benefit structure policy for households with multiple SSI recipients, SSA will be poorly positioned to implement and administer those changes in the future.

Recommendation for Executive Action

To ensure the agency has sufficient information about risks to SSI program integrity when making decisions about efforts to address them, we recommend that the Commissioner of the Social Security Administration conduct a risk assessment of the current manual process for connecting and adjusting claim records of SSI recipients who live in households with other SSI recipients, and, as appropriate, take steps to make cost-effective improvements to SSA’s claims management system to address identified risks.

Agency Comments and Our Evaluation

We provided a draft of this report to SSA for review and comment. In its written comments, reproduced in appendix III, SSA disagreed with our recommendation stating that current SSI program rules do not support connecting records of unrelated individuals living in multiple recipient households. SSA also noted that it does not have evidence from its fiscal year 2014 payment accuracy reviews that manual processing of married couple multiple recipient household claims led to payment errors. As such, the agency stated that it could not commit resources to address our recommendation at this time, but noted if a legislative proposal is put forth that affects unrelated multiple SSI recipient households, SSA will assess program policy and systems risks as part of its evaluation and planning. However, we continue to believe that the manual processing currently used to connect and adjust claim records of SSI recipients who live in households with other SSI recipients leaves the agency at risk. SSA has acknowledged that it has not assessed the extent to which manual processing leads to payment errors, and the data they provided us on fiscal year 2014 improper payments to married couple recipients does not address the full scope of the issues we identified. Specifically, field office staff reported several instances in which manual processing is used to connect and adjust claims records for multiple recipient households due to system limitations, and indicated that these manual adjustments increase the likelihood of erroneous payments. These manually processed claims are for households with multiple related recipients whose SSI benefits are currently inter-related under program rules, such as multiple child recipients who are siblings or individual recipients who marry another recipient. Without an assessment of the risks associated with the manual processing of these claims, SSA is unable to determine if additional adjustments to its system would be a cost-effective use of its resources. SSA officials also provided technical comments, which we incorporated into the final report, as appropriate.

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If you or your staff have any questions about this report please contact me at (202) 512-7215 or bertonid@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this report. GAO staff who made key contributions to this report are listed in appendix IV.

Appendix I: Scope and Methodology

To better understand multiple Supplemental Security Income (SSI) recipient households and the potential effects of implementing a change in the amount of benefits received by these households on program administration and other factors, we employed several methods, including: analysis of matched data from Social Security Administration (SSA)

Supplemental Security Record (SSR) and U.S. Census Bureau (Bureau) Survey of Income and Program Participation (SIPP) review of relevant program laws, regulations, and other reports for other federal programs for low-income individuals and families interviews with SSA staff.

We conducted this performance audit from March 2015 to August 2016 in accordance with generally accepted government auditing standards. Those standards require that we plan and perform the audit to obtain sufficient, appropriate evidence to provide a reasonable basis for our findings and conclusions based on our audit objectives. We believe that the evidence obtained provides a reasonable basis for our findings and conclusions based on our audit objectives.

Analysis Using Matched SSR and SIPP Data

To respond to our questions, we obtained and analyzed matched data from the Bureau’s SIPP and SSA’s SSR on the number and characteristics of SSI recipients living with other SSI recipients, and the amounts of benefits received by these recipients. We determined SIPP was the best choice for matching with the SSR after interviewing experts who had worked with this and other similar data sets. According to these experts, SIPP was the best choice for our work because it is updated on a monthly basis, so it is well matched to the SSR data on the SSI program.

Analytical Goals and Target Population

To describe the living arrangements of SSI recipients, we needed data on both the population of SSI recipients and the characteristics of their households and families. SSA collects detailed data on recipients for the purpose of administering the SSI program. These data primarily included variables related to eligibility, benefit amounts, and beneficiary activities relevant to the program, such as earned and unearned income. SSA does not collect data on recipients’ living arrangements. This makes administrative data incomplete for the purpose of describing household and family composition among recipients.

The Bureau’s program of matching administrative and survey data provided these data to supplement SSA’s administrative records. The Bureau matches SSA’s administrative data to SIPP public use files, using a complex algorithm that we describe in more detail below. The matched SIPP files provide detailed information on other people living in SSI recipients’ households, including related family members. Although SIPP data on SSI benefit receipt and amount are subject to measurement error, the survey’s data on households, families, and other social demographic variables were more detailed and reliable than SSA’s administrative sources. In this sense, the matched data benefit from each data source’s strength, and produced more reliable data for our purposes.

The target population for our analysis included SSI recipients who do not live in large group housing environments, such as boarding houses or dormitories. The SIPP classifies these environments as “group quarters.” As a result, we analyzed a subpopulation of the matched SIPP respondents who received SSI benefits, according to the SSR, and who did not live in group quarters, according to the SIPP. We analyzed this subpopulation using methods for domain analysis that set analytical weights to zero for sample units that were out of scope.

Data

We analyzed two specific series of data from the Bureau and SSA: public- use “core” files from the 2008 SIPP panel and SSR data extracted at equivalent time periods.

2008 SIPP Core Data

The 2008 SIPP is a longitudinal survey of civilian, non-institutionalized residents of the United States, with final-stage sampling of housing units. In the first wave, the survey attempted to interview people living in an initial sample of 52,031 eligible housing units. In subsequent waves, the survey attempted to re-interview respondents from the first wave, along with all other people living with them at later waves. The population covered by the SIPP is generally the same as the population eligible for SSI. However, the SIPP may exclude certain SSI recipients who live in institutions such as long-term medical facilities. We believe this coverage error to be minimal and therefore, we did not make weight adjustments for this population.

The survey interviewed respondents roughly once every four months. Respondents provided data about the previous four month “reference” period, with many variables measured each month within the period. The Bureau administered the survey using a system of interview rotation groups, such that in any month, one-quarter of the eligible sample gave responses. For any month of measurement, data from four rotation groups, interviewed on different dates, make up a complete sample.

We analyzed data for five unique time periods: May of each year from 2009 through 2013. We chose May as the reference month to align with the month of the most recent SSR extract in May 2013 (see below). In each time period, we built a complete sample by selecting rotation groups and waves that corresponded to the reference month of interest. For example, a complete sample for the reference month of May 2013 included data from rotation groups 1 from wave 16 and groups 2-4 from wave 15. Selecting complete sets of rotation groups avoided the need to adjust weights and maximized the available data. We applied monthly weights to make generalizeable estimates for the SIPP target population for each of the five distinct reference months. We did not include longitudinal data on whether respondents gave responses or were in- scope for all time periods, and instead made five cross-sectional estimates.

SSR Extracts

The SSR contains various fields that describe SSI recipients’ participation in the program. For our purposes, the primary fields of interest include benefit receipt, benefit amount, marital status, earned income, and unearned income.

The Bureau maintains a cumulative file of the SSR extracts that it has received since its record linkage program began. One record in the file exists for each SIPP respondent who ever matched an SSR extract. Fields include a subset of SSR fields in SSA’s version of the file, some of which are measured at multiple times and some only for the date of the file. We analyzed a May 2013 vintage of this file, which contains monthly historical data for all variables of interest except marital status.

Record Linkage

The Bureau has developed a general method of linking data with personally-identifying variables to their surveys, known as the Person Identification Verification System (PVS). PVS seeks to produce a unique identification number for a given person, called a Protected Identification Key (PIK), across all data ever used as input and reference files that the Bureau maintains from federal sources, such as SSA.

According to Bureau documentation, PVS uses blocking and matching methods to estimate the probability that a given input record matches verified reference files and can be assigned a PIK. Blocking variables, such as the first three digits of a Zip code or first or last names, reduce the space of potential matches to make computation feasible. Matching variables, such as Social Security number, name, or date of birth, serve as input for calculating multivariate weights that describe the degree of record similarity across the matching variables. PVS assigns a PIK when the value of the match weight exceeds a threshold of similarity, assumed as an input parameter. The system contains multiple modules with different blocking and matching variables and similarity parameters. Records that are not assigned PIKs in one module move on to later modules.

The Bureau research shows that PVS reliably assigns PIKs to federal data sources, such as the SSR. Since the Bureau has access to detailed data files on Social Security transactions, the agency can verify the accuracy of PVS using reference files. A 2014 validation found that observed false match rates varied from 0.005 percent to 1.174 percent for Medicare data extracted in 2011, with similar results found for the same file extracted in 2012. These low levels of misclassification are acceptable for our purposes. The matched data have some additional error from the record linkage process, but have substantially lower measurement error of key variables, such as SSI receipt.

Although the Bureau research has found that the PIK is accurate, once it can be assigned, PVS cannot always assign PIKs for all records in a particular application. PIK assignment rates for 2008 SIPP panel waves range from 89.4 percent to 90.6 percent. This adds commensurate amounts of missing data to our analysis, which requires data from both the SIPP and SSR.

The Bureau research has found that survey records without PIKs assignment are unlikely to be missing at random. This suggests that analysis of survey and administrative data matched using the PIK should adjust for potential bias from the PIK assignment process. We discuss our method of adjustment below.

We matched the 2008 SIPP public-use core files to the Bureau version of the SSR using the PIK and unique identifying variables in each file. We then joined the two files using the PIK. This approach is not documented publically, but follows guidance we received from the Bureau staff.

Missing Data, Imputation, and Weighting

Since the SIPP is a longitudinal survey, missing data can accumulate across waves as members of the original sample stop participating. According to Bureau documentation, sample loss rates range from 19.4 percent in wave 1 to 53.1 percent in wave 16.

Our analysis used data from multiple waves for each reference month of interest, including later waves that have moderate levels of unit nonresponse. To adjust for potential bias, we used the weighting cell adjustments that are integrated into the weights provided by the Bureau. As a further check, we compared select estimates to known values from SSA publications. Specifically, we compared, by age group, estimates of total beneficiaries and total and mean SSI benefits. If our estimates’ confidence intervals did not span the control values, we applied an additional post-stratification adjustment to align the results. Because many of our key estimates involve total beneficiaries and benefit amounts by age group, post-stratification adjusted for unit nonresponse bias for our specific population, supplementing the general Bureau adjustments.

When the Bureau cannot assign a PIK to SIPP respondents, as discussed above, they have a zero probability of matching the SSR and contribute additional unit missing data. Rates of PIK assignment in our matched data ranged from 89.4 percent to 90.6 percent, depending on the SIPP wave, which implies that the matching process adds a small amount of missing data. However, Bureau research suggests that younger, non-white, and lower household income respondents, among others, are more likely to lack PIKs. As a result, we estimated the relationship between variables relevant to our analysis, such as age, income, and disability status, and the probability of a missing PIK, in order to mitigate potential bias and scale up estimated totals back to the controls used in the Bureau post-stratification adjustment. The latter goal is particularly important, because our analysis estimated many population totals.

We used nonparametric weighting class methods to adjust for missing data due to record linkage. First, we cross-classified the adjustment variables to obtain a categorical variable identifying joint group membership, collapsing groups containing less than 0.1 percent of the sample into a residual group to avoid excessive weight variance and instability. Letting Xij denote the joint adjustment variable for respondent i, having levels j = {1, 2, …, J}, and letting Yi = I(Missing PIK), we estimated the probability of a missing PIK conditional on the adjustment variable with where wi is the final person weight provided by the Bureau . We calculated the adjusted weight as Following the Bureau methods, we used the adjusted weight for the household reference person as the adjusted household weight.

Rates of item nonresponse and Bureau imputation are extremely low for the SIPP variables of interest. Item imputation rates generally do not exceed 5 percent for the SIPP variables we analyzed, which mostly include household, family, and age variables. Of the small fraction of data that are imputed, most are imputed responses from prior waves or logically implied by other, observed variables. The remaining imputed values are statistical estimates. Given the low rates of item missing data and the high rates of non-statistical imputation, we used the imputed data that the Bureau provides and assume that statistical imputation error is ignorably small.

Estimation

The SIPP is a multi-stage, stratified, cluster sample of households. Since the Bureau does not provide sample design variables to preserve respondent privacy, we used the supplied bootstrap replicate weights to calculate balanced repeated replication estimates of sampling variance. We analyzed small subpopulations, so we applied a Fay adjustment to ensure stable estimates across groups, consistent with Bureau guidelines. All estimates of interest are linear functions of weighted totals (e.g., mean and total recipients, benefits, or income), so standard estimators are appropriate.

Other Federal Programs for Low- Income Individuals and Families

To better understand the potential effects of changing an SSI recipient’s benefits on other federal benefit programs, we reviewed relevant program rules and relevant data for three federal programs—Medicaid, Temporary Assistance for Needy Families (TANF), and the Supplemental Nutrition Assistance Program (SNAP). We selected these programs because they each serve large numbers of low-income individuals, and households with SSI recipients may be eligible to receive these benefits as well. To understand the extent SSI recipients receive benefits from each of these programs, we reviewed relevant studies on Medicaid and SSI, federally available TANF caseload data from the U.S. Department of Health and Human Services, and the U.S. Department of Agriculture, Food and Nutrition Service’s report on the characteristics of SNAP Households.

Interviews with SSA Staff

To gather information on the characteristics of multiple recipient households, SSA’s administration of SSI claims for individual recipients and multiple recipient households, and how changing the amount of benefits received by multiple recipient households may potentially affect SSA, we conducted interviews with staff from SSA headquarters and select field offices. Specifically, we interviewed staff from SSA’s Office of Research, Demonstration, and Employment Support; Office of Systems; and the SSI Simplification Workgroup. In addition, we conducted interviews with field office managers and SSI claims representatives from five SSA field offices located in Los Angeles, California; Louisville, Kentucky; Baltimore, Maryland; Brooklyn, New York; and Houston, Texas. We selected these field offices to account for geographic dispersion, with at least one office representing the east coast, west coast, mid-west, and southern United States. We also selected these field offices based on their location in states and cities with high concentrations of SSI recipients, to better ensure the likelihood that the field offices we selected were managing claims of multiple SSI recipient households. Of the five states we selected, we included one state where at least 40 percent of its population lived in rural areas. The views of staff from these field offices are not generalizable to all field offices nationwide. To gain additional perspectives from SSA field office staff, we interviewed 10 additional SSA field office managers affiliated with the National Council of Social Security Management Associations.

Appendix II: Data Estimates Related to Multiple Supplemental Security Income (SSI) Households

All one recipient households

All multiple recipienthouseholds Multiple recipient households with earned income Multiple recipient households with unearned income

15,005 – 34,700 54,396 516,439 – 788,617 $147.50 $69.10 - $226.00 $622.10 $560.20 - $683.90 95 percent confidence interval 2.5 – 9.2 95 percent confidence interval 15.6 – 27.0 $1,000 - $1,455 $2,838 - $3,280 67.4 – 75.3 95 percent confidence interval (in dollars)

One recipient households All recipient households

One recipient households

Appendix III: Comments from the Social Security Administration

Appendix IV: GAO Contact and Staff Acknowledgements

GAO Contact

Staff Acknowledgements

In addition to the contact named above, Rachel Frisk (Assistant Director), Kristen Jones and Michelle Loutoo Wilson (Analysts in Charge), William Carpluk, David Forgosh and Jeff Tessin made key contributions to this report. Additional contributors include Carl Barden, Holly Dye, Alexander Galuten, Sheila McCoy, Mimi Nguyen, Monica Savoy, Mark Ward, and Margaret Weber.