Supplemental Nutrition Assistance Program: More Information on Promising Practices Could Enhance States' Use of Data Matching for Eligibility
Released: 2016-11-17T00:00:00

Letter

Background

Determining SNAP Eligibility and Benefits

The goal of SNAP is to help low-income individuals and households obtain a more nutritious diet by supplementing their income with benefits to purchase allowable food items. The overarching rules governing SNAP are set at the federal level. Accordingly, FNS is responsible for promulgating program regulations and ensuring that state officials administer the program in compliance with program rules. The states, or in some cases counties, administer the program by determining whether households meet the program’s eligibility requirements, calculating monthly benefits for qualified households, and issuing benefits to participants on an electronic benefits transfer card. States are also allowed flexibility in establishing some state-specific policy modifications, such as through state options.

One financial criterion for SNAP eligibility and benefit amount involves household income, which can come from various sources, including earned income, such as wages and salaries, and unearned income, such as payments from other government programs (see table 1). Generally, under federal law, a household’s gross income cannot exceed 130 percent of the federal poverty level ($2,628 per month for a family of four for most states in fiscal year 2016). The household’s net income, which is determined by deducting certain expenses from gross income, such as certain dependent care and shelter costs, cannot exceed 100 percent of the federal poverty level ($2,021 per month for a family of four for most states in fiscal year 2016). Net income is used in determining the household’s benefit amount, subject to maximum benefit limits. Generally, eligibility is based on various household circumstances, including income. After eligibility is established, households are certified to receive SNAP for periods ranging from 1 to 24 months depending upon household circumstances and state-selected policy options. Households are required to report certain changes during the certification period which can affect their eligibility and benefit amounts. Once the certification period ends, there is a recertification process whereby households reapply for benefits and eligibility and benefit levels are redetermined.

Use of Data Matching for Eligibility

SNAP agencies use data matching to obtain information about households’ income, verify information that households provide when they initially apply or recertify for benefits, or identify potential discrepancies. For households that already receive SNAP benefits, data matching can provide information about changes in income that affect households’ eligibility or benefit levels (see fig. 1). In certain cases, data matching can take the place of traditional forms of verifying information provided by applicants, such as requiring households to submit documentation (e.g. pay stubs or a child support agreement) or making collateral contacts, such as a phone call to an employer.

Certain federal policies that help protect individuals from inappropriately losing benefits affect whether SNAP agencies need to take additional steps to verify information from a data match. Federal law generally requires that government agencies administering benefits using matching programs verify information from matches before reducing or terminating benefits unless specified government entities have determined that there is a high degree of confidence that the information is accurate. For SNAP, FNS defines some data matches as “verified upon receipt,” if the match is with a primary or original source of the data (such as information on a government benefit provided by the administering agency) and is not questionable. An example is a match with SSA that provides information on the amount of Old-Age, Survivors, and Disability Insurance (OASDI) benefits a household receives. Eligibility workers can use this information for eligibility determinations without taking additional steps to verify that the data are accurate, according to FNS guidance. In contrast, data from a secondary source (not verified upon receipt) require additional verification before they can be used in eligibility determinations. For instance, state quarterly wage data are considered a secondary source because they are a compilation of earnings data submitted by employers to the state workforce agency. Accordingly, the SNAP caseworker must take additional steps, such as contacting an employer or requesting paystubs from the client, to verify that information from that match is accurate before using it to change a household’s eligibility status or benefit amount. Failing to verify information from secondary sources can cause eligible households to lose benefits if caseworkers act on inaccurate information. Alternatively, if caseworkers do not follow up to verify information from secondary sources, they may miss opportunities to reduce or prevent improper payments. Regardless of whether the data are from primary or secondary sources, SNAP agencies are required to notify the household of the actions they intend to take and provide the household with an opportunity to request a fair hearing prior to any adverse action.

Federal law and regulations require states to conduct certain data matches for SNAP eligibility, including three matches that provide non- income related information on people who may be incarcerated, deceased, or otherwise disqualified from receiving SNAP benefits (see table 2). Most recently, the Agricultural Act of 2014 required SNAP agencies to conduct a match with the National Directory of New Hires (NDNH) to verify employment data.

States Reported Conducting Numerous Data Matches for SNAP and the Matches They Find Most Useful Provide Real- Time Access to Recent Data

All States Conduct a Range of Data Matches for SNAP, and Most States Have Implemented the Recently Required New Hire Data Match

In response to our survey, all states reported conducting multiple data matches for income information that they use to determine SNAP eligibility. These matches gather information from federal, state, and commercial data sources on earned income from employment or self- employment, or unearned income from other government benefit programs (see table 3).

As of September 2016, 39 state SNAP agencies conduct the federally- required match with the NDNH New Hire data (see sidebar), according to our survey and information from HHS/ACF’s Office of Child Support Enforcement (OCSE) on states’ progress in implementing the match. FNS required states to implement this match for SNAP eligibility purposes by September 21, 2014; however, some states have experienced implementation delays, and FNS officials said that each of the 12 remaining states is working towards implementing the match. States that experienced implementation delays had not yet developed the capacity to conduct the NDNH New Hire match or faced competing priorities for resources, according to FNS, OCSE, and state officials. For example, two of the remaining states said they will implement the match in coordination with efforts to upgrade or replace SNAP eligibility systems. Two other states said in their survey responses that a lack of resources has delayed their implementation of the match. FNS monitors states’ progress in implementing the required NDNH New Hire match and promotes states’ compliance by reviewing monthly reports on states’ matching activities and following up with states as needed, according to FNS officials. Specifically, FNS officials reported that the national office in Washington, D.C., reviews monthly reports from OCSE on states matching activities and forwards information to FNS regional offices for follow up as needed.

Matches States Reported Finding Most Useful Provide Real-Time Access to Recent Data, and Other Matches May Detect Unreported Sources of Income

Data matches with primary sources, those that allow for real-time access to data, and those that provide up-to-date information are useful because they enable efficient and accurate SNAP eligibility determinations, and matches that combine these characteristics are particularly useful, according to our analysis of state survey responses. Officials from SNAP agencies we interviewed explained that these data matching characteristics streamlined the eligibility determination process for caseworkers and households.

Data matches with primary data sources are more useful because caseworkers can use the information without having to conduct additional verification, according to officials from each of the six state SNAP agencies we interviewed.

Matches that can be accessed in real-time, or immediately upon request, can help caseworkers make determinations more quickly or eliminate the need to revisit eligibility or benefit determinations multiple times, according to officials we interviewed in five of the six states. Real-time access allows caseworkers to verify information provided by applicants and discuss apparent discrepancies during interviews rather than contact households again later. It can be difficult for caseworkers to contact households, according to officials we spoke with in four of the six states, and the need to do so can create delays in processing applications, a key FNS performance measure for SNAP.

FNS regulations generally require recent information on income for SNAP eligibility and benefit determinations. Generally, FNS directs states to use income received in the last 30 days as the basis for determining SNAP benefit amounts. Accordingly, matches that provide current information can be used to accurately calculate or adjust benefits whereas older data may introduce errors if not updated. Officials from each of the six states we interviewed emphasized the importance of up-to-date information.

Four data matches for unearned income have each of the useful characteristics described above, while the data matches for earned income lack one or more of these characteristics. The four data matches most states reported using and finding very or extremely useful are with primary sources including state or federal agencies that administer benefit programs that provide households’ unearned income (see fig. 2). Matches with SSA can provide real-time access to current SSI and OASDI program benefits that a household may receive. Matches with state-level unemployment insurance and child support enforcement agencies can provide up-to-date and real-time access to information on households’ receipt of benefits or support payments, depending on states’ matching capabilities. The data source for earned income that the most states reported as very or extremely useful was the commercial verification service The Work Number®, which is owned by Equifax Inc. and stores employment and earnings information gathered from participating employers’ payroll systems. Equifax representatives told us they estimate that The Work Number covers about 35-40 percent of the working population at any given time. Additionally, FNS officials told us that while The Work Number is a secondary source of information for SNAP eligibility purposes, SNAP agencies can use it to verify earned income reported by households or to identify potential earnings that were not reported. Similar to our findings in a recent report on the use of commercial data services to help identify fraud and improper payments, officials from five of the six states where we interviewed SNAP agency officials said The Work Number can improve program integrity or program efficiency by providing real-time access to accurate and up-to-date information. Also, use of The Work Number can reduce the reporting burden on households and employers because caseworkers can use it in lieu of collecting pay stubs from households or contacting employers to confirm reported earnings, according to state or local officials in these five states and Equifax representatives we interviewed.

Data matches that do not have the characteristics that states found particularly useful can be used as leads to detect income that households may not have reported. For example, although state new hire directories and the NDNH New Hire data do not include information on the amount of employee earnings, caseworkers can use them to identify new employment that may not be reflected in households’ case files and follow up with households or employers to verify earnings. Eligibility workers at one county office we visited said that although not all data matches they used had complete or up-to-date information, they were still useful because they prompted action and helped prevent potential improper payments.

States Reported Challenges with Following Up on Data Matches, Using Data Matches for Multiple Programs, and Costs

Necessary Follow-Up on Data Matches Is Challenging, Especially Related to Earnings and Out-of-State Benefits

In our survey, we asked states about overall challenges for the income- related data matches they use, and the issue the most states found very or extremely challenging was following up to verify information provided by those matches. Other issues related to the data, such as the recency of information, were also noted as challenges (see fig. 3). SNAP agency officials we interviewed in each of the six states said that following up on data matches to ensure information is accurate and up-to-date can be time intensive and difficult to achieve. As discussed earlier, the need to follow up on data matches stems from limitations in using the data for SNAP eligibility purposes. According to FNS guidance, before taking certain actions that affect households’ benefits, SNAP agencies should confirm income information that is not considered verified. FNS does not consider information that is questionable or that comes from a secondary rather than a primary source of information to be verified. These secondary data sources are often collected for multiple purposes and thus may not be sufficiently recent, accurate, or complete for SNAP eligibility determinations. NDNH files, for example, contain data used for many purposes. They are used to help state child support agencies locate parents and enforce child support orders. They also assist with the administration of SNAP, TANF, and child and family services programs, among others. However, some information, such as NDNH’s Quarterly Wage file, may not be sufficiently recent to serve as the basis for SNAP eligibility determinations without potentially leading to improper payments. It can take months to compile this information from employers at state and national levels—states have four months after the end of a calendar quarter to transmit quarterly wage data to NDNH. Thus, it may be difficult to accurately calculate SNAP benefits from quarterly earnings if employees experienced changes in employment, hours worked, or wage rates. In addition, officials we spoke with from four of the six states said that a new hire match may not indicate that someone actually earned wages, such as when someone signs up with a temporary employment agency but has not actually been placed in a job.

Working families make up a growing share of SNAP households; yet earned income information can be particularly difficult to obtain through data matches. Data matches that provide earned income information do not come from primary sources and have unique advantages and disadvantages in how recent or comprehensive their data are for determining SNAP eligibility (see table 4). Unlike several data matches for unearned income, all data matches for earned income lack one or more characteristics that are useful for determining SNAP eligibility. Earned income data sources such as the PARIS federal file, The Work Number, and various state sources do not include all employers, whereas more comprehensive sources such as NDNH or Internal Revenue Service earnings and tax data are more than 30 days old, lack relevant details, and are not available in real-time. In addition, states reported that the security and privacy safeguards needed to use tax data can be particularly challenging. Accordingly, SNAP agencies reported that they rely on multiple data matches for earned income information, which they should confirm is correct and relevant for SNAP eligibility before using the information for eligibility or benefit determinations.

Similarly, several data matches provide information on whether households received unearned income in the form of benefits from programs in other states or receive benefits from the same program in multiple states at the same time, but following up to confirm matches across states can be difficult. Data matches on benefits in other states can help SNAP agencies identify when a household or household member moves from one state to another but has not reported the move, as well as detect possible instances of intentional fraud. Data matches such as the PARIS Interstate file and NDNH Unemployment Insurance file aggregate income information across states and can provide useful leads for follow up by states. However, 13 states reported in our survey that lack of access to income information from other states was very or extremely challenging. In addition, officials we interviewed in four of six states said that it is time consuming to conduct follow up verifications with other states in terms of obtaining verification from other states or in terms of providing verifications to other states upon request. For example, an official from one state noted that the state receives approximately 500 inquiries a month from other states following up on matches from the PARIS Interstate file, and the state must respond to each one in writing. Officials from another state said that out-of-state-benefits were the most cumbersome form of income to verify because the process varies by state or even by county, and other agencies may be slow to provide information, place verification requesters on hold for extended periods of time, or frequently change their points of contact.

States reported efforts to target and streamline data matching activities in order to reduce some of the manual work associated with data matching, including those associated with worker follow-up. SNAP agency officials we interviewed in three of the six states reported initiatives underway to improve data matching efficiency by better prioritizing which matches need follow up. For instance, in response to earlier challenges it encountered with data matching processes, Massachusetts has gone through a yearlong effort to better distinguish patterns of information from their quarterly wage and new hire matches that indicate whether follow up is worthwhile, according to state officials. By developing more sophisticated data matching algorithms, they hope to be able to filter out new hire matches that are not likely to affect SNAP benefits such as for one-day employment as an election worker or college students’ income from federal work-study programs that are not counted when determining SNAP eligibility and benefits. Massachusetts officials said that efforts such as these to use data matches more strategically can improve program integrity and service to households, as well as administrative efficiencies. Also, among states we interviewed, Texas, Virginia, and Washington have implemented information systems that enable caseworkers to look up available client information from multiple state and federal data systems with one search rather than conducting each data match individually. In addition, five states responded to our survey that they have systems to automatically import information from most or all matches into their eligibility systems without additional manual data entry.

Similarly, SNAP agency officials in two of the six states we interviewed (Massachusetts and Washington) said they were involved in state- initiated efforts to address the need for faster, more complete cross-state data. For example, Massachusetts officials described a direct match that their state does with New York to provide one another data on households receiving benefits. Massachusetts officials said they can take action on exact matches showing household members receiving benefits from both states, and follow up on leads as appropriate if matches are not exact. Washington state officials told us that they provide neighboring states with certain read-only access to an online benefits verification system to allow those states to more easily confirm whether applicants already receive benefits in Washington. Washington officials told us this online system is easier than faxing or phoning the information to other states, and that they are pursuing access to other states’ information through similar online systems.

States Reported Barriers to Using Data Matches for Multiple Programs and the Cost of Conducting Matches as Challenges

States reported ways they have integrated SNAP eligibility processes with other programs, particularly TANF and Medicaid, but also reported that limitations on using the same data matches for multiple programs were challenging. States sometimes integrate aspects of the SNAP eligibility process with those of other programs, such as through combined applications, common eligibility workers, or integrated or linked eligibility systems. According to our survey, SNAP eligibility processes were most commonly integrated with state TANF cash assistance programs, as well as with state Medicaid programs, although to a somewhat lesser degree. However, 21 states reported that they found it very or extremely challenging that Medicaid and other programs use income information from matches differently than SNAP because, for example, processes for verifying income information or definitions of household income differ across programs.

One way state Medicaid programs verify income information differently than SNAP is by accessing data sources through CMS’s federal data services hub (the Hub). As we have previously reported, CMS created the Hub to implement provisions of the Patient Protection and Affordable Care Act (PPACA). The Hub provides a single access point for state agencies to gather information from various data sources used to verify eligibility determinations for Medicaid and related insurance affordability programs. More specifically, the Hub provides access to OASDI data from SSA and earnings data from Equifax’s Work Number, among other data, according to our prior work and additional information from CMS, SSA, and Equifax. Although these data are also used for SNAP, if state agencies access this information from the Hub, they cannot use it for SNAP eligibility determinations, even for a household that applies for or receives both Medicaid and SNAP benefits, according to FNS guidance. This is because data use agreements between CMS and federal agencies and the contract between CMS and Equifax do not authorize states to also use data accessed through the Hub for SNAP, according to officials from CMS and SSA. Due to these restrictions, when a state uses the Hub for Medicaid eligibility and a caseworker would like to use information on OASDI benefits or earnings available from The Work Number to determine SNAP eligibility, the caseworker would need to access this information independently, in effect conducting duplicative data matches to verify some of the same information for the same household. (See fig. 4).

Officials we interviewed in four of the six states and officials in six additional states in their responses to open-ended survey questions reported they would like to use the Hub for SNAP determinations or that it was challenging they were not able to do so. During interviews, officials from two of these states noted that this was challenging given that households that participate in SNAP are often also enrolled in Medicaid. For instance, an official from one state we interviewed expressed frustration with the duplicative work caused by not being able to use data accessed through the Hub for Medicaid eligibility verifications, to also verify SNAP or TANF eligibility, when applicable. An official from another state told us that having different processes to verify income for SNAP and Medicaid posed challenges to integrating program operations. Specifically, the official said that it was difficult to train eligibility workers to verify income in different ways for Medicaid and SNAP, and that it is also more difficult to integrate eligibility systems and combine households’ records across these programs when income information from data matches can be used for Medicaid but not for SNAP. Concerns regarding program inefficiencies, duplicative work, or additional costs were echoed by representatives we interviewed among five of seven stakeholder groups.

Costs may also be a factor in states’ ability to access data. About one- third of states reported in our survey that upfront and ongoing costs associated with conducting data matches were very or extremely challenging overall (see fig. 5), and states reported costs as particularly challenging with respect to use of The Work Number. Upfront costs are those associated with establishing a new data match, such as developing data sharing agreements, updating information systems or adapting business processes to use the match. Ongoing costs include those charged by the source agency or the commercial provider for ongoing use of the match, such as a per match charge. Additionally, there are costs associated with maintaining data sharing agreements. More states reported that costs associated with The Work Number were very or extremely challenging than they did for other national data sources. Of the 45 states that used The Work Number match, upfront costs were a challenge for 17 states, and ongoing costs were a challenge for 19. Some states limit their use of The Work Number or do not use it at all due to costs, according to interviews with state and FNS officials and comments from states in response to our survey. For instance, officials from one state we interviewed said they would like to be able to use The Work Number for every application and that applicants ask them to verify earnings through The Work Number, but because of the cost of these matches, caseworkers are asked to only conduct these matches as a last resort when other forms of verification are not available. Even with these limitations, the state contracts for a limited number of matches per month and frequently loses access to The Work Number when that limit is met before the end of the month, according to officials in this state and Equifax representatives. Such challenges can create inefficiencies for eligibility workers and increase the burden for households.

FNS Has Efforts Underway to Promote the Use of Data Matching to Improve SNAP, but May Be Missing Some Opportunities

FNS Efforts Include Initiating Demonstration Projects and Pilots, Promoting Program Integration, and Working with CMS to Reduce Duplicative Processes

SNAP Demonstration Projects and Pilots

FNS has initiated several demonstration projects or pilots aimed at using data matching to improve client access, program integrity, or program efficiencies for SNAP (see table 5). Two of these initiatives, the Combined Application Project and the Elderly Simplified Application Project, are designed to help vulnerable populations, particularly the elderly, obtain benefits more easily. Currently, states are able to participate in these projects by requesting waivers from FNS. However, based on the success of these demonstrations in increasing elderly participation in SNAP, FNS recently proposed creating a state option (instead of the use of waivers) that would allow states to adopt a set of policies to streamline and simplify SNAP application, reporting requirements, and recertification for low-income elderly individuals. In contrast, based on the results of another demonstration that explored the use of quarterly wage data matches, FNS recently concluded that it could not recommend the use of these data, as it affected the accuracy of benefit amounts.

A fourth FNS-sponsored project, the National Accuracy Clearinghouse (NAC) pilot, created a new data sharing system in 2013 that enabled five pilot states affected by Hurricane Katrina (Alabama, Florida, Georgia, Louisiana, and Mississippi) to share information across states about the receipt of SNAP. The 2015 evaluation of the NAC reported that the five participating states were able to identify or prevent duplicate receipt of SNAP benefits among these states. Unlike the PARIS data match, which identifies potential duplicate receipt a number of months after it has occurred, the NAC’s real-time data could help states prevent duplicate receipt of benefits. These sentiments were echoed by Florida officials we interviewed, who told us that the NAC is more useful than PARIS because it is updated daily rather than quarterly. The evaluation also found that net cost savings were achieved in each of the five participating states, although to varying degrees.

Program Integration Efforts

Funding Available for Health and Human Services Integration The federal government funds 90 percent of the qualifying costs of information technology (IT) improvements for investments in the design and development of state eligibility- determination and enrollment systems for Medicaid and the Children’s Health Insurance Program. Under normal cost allocation rules, human services programs that benefit from these systems improvements would be required to pay their share of associated costs. However, under a waiver of these rules through 2018, state human services agencies do not need to pay their share of costs for certain systems improvements that benefit both health and human services programs.

Along with several SNAP-focused demonstration projects and pilots, FNS has also worked with HHS on initiatives that affect SNAP and its integration and interoperability (the ability to exchange information across systems) with other health and human services programs. These efforts have largely been spurred by time-limited funding opportunities aimed at promoting more streamlined and efficient enrollment and eligibility systems across state health and human services programs, according to information from HHS and FNS. Specifically, to help states meet requirements under the PPACA, CMS increased the level of federal funding for information technology (IT) modernization for health systems improvements. Human services programs can benefit from these improvements at little or no additional costs, under a time-limited waiver to normal cost allocation rules (see sidebar). FNS has worked with CMS and ACF to promote states’ awareness and use of this funding. For example, these three agencies sent a joint letter to states in 2011 that announced the cost allocation waiver and another in 2015 that announced an extension of the waiver through 2018. According to FNS, 38 states had availed themselves of the cost allocation waiver to fund health systems improvements that also include improvements to SNAP eligibility systems, at the time of this review, and according to our survey, almost three-fourths of states (29 of 40) that rated the usefulness of this funding said that it was very or extremely helpful.

Since 2013, FNS also has been involved in CMS-led interagency efforts to address duplication and program integration challenges, previously discussed, related to restrictions of data accessed through the Hub for joint Medicaid cases that include SNAP or TANF. Officials from FNS, CMS, and ACF (the federal agency that oversees TANF) as well as SSA, told us that they have been working for several years to develop policy options and modified data sharing agreements to allow for SSA data accessed through the Hub for Medicaid verifications to also be used for SNAP and TANF in joint cases. Officials told us that progress in addressing these issues has been slow, due to complex issues related to various legal requirements, including those under the Privacy Act of 1974. However, CMS officials told us that they have the support of multiple agencies, including SSA and the Office of Management and Budget (the federal agency that provides guidance on the Privacy Act), to allow TANF and SNAP agencies’ use of Hub data and they hope to resolve these issues by the end of the calendar year. In our prior work on data sharing across state and local human services programs, we noted that strong leadership support across agencies is a key factor for success in facilitating data sharing.

These interagency efforts to improve efficiencies across programs for Hub-accessed data are in line with several efforts aimed at better coordination across government. In our extensive work on duplication, fragmentation, and overlap in the federal government, we defined duplication as occurring when two or more agencies or programs are engaged in the same activities or providing the same service to the same beneficiaries. We have reported that federal agencies should identify opportunities to reduce duplication, which could enable better management of program administration or result in potential cost savings. In the case of the Hub, because some duplicative data matching processes related to eligibility determinations occur due to the current Hub restrictions, reducing these duplicative processes may result in improved administrative efficiencies. Additionally, the interagency efforts related to the Hub are also in line with HHS recommendations, developed in response to requirements under the PPACA, which called on federal agencies to promote greater interoperability across health and human services programs to streamline program administration, including the use of data for eligibility determinations among several programs when possible. Similarly, officials from CMS, FNS, and ACF indicated that their current efforts in facilitating use of data from the Hub across Medicaid, SNAP, and TANF were part of a larger vision to promote health and human services interoperability and integration overall, and were related to current funding opportunities for such integration, discussed earlier in the report. In a tri-agency letter to states, these agencies stated that they were “committed to a strong partnership with states and our federal stakeholders as we work together to implement our shared vision of interoperable, integrated and consumer-focused health and human services systems.”

Use of The Work Number

FNS also has begun to explore ways to help states address some of the cost challenges associated with use of The Work Number discussed earlier in the report. Equifax representatives told us that each state SNAP agency that conducts data matches with The Work Number contracts independently with Equifax, and states pay different prices to use the service due to various factors including the volume of matches that each state purchases. In contrast, CMS has negotiated a single contract with Equifax that allows states to access information from The Work Number through the Hub to determine eligibility for Medicaid and related insurance affordability programs. Due to volume-pricing, Equifax representatives told us that a single contract to cover all state SNAP agencies use of The Work Number would likely lead to lower costs per match than what most state SNAP agencies pay now through individual contracts. It would also help states by eliminating the need for each state to negotiate separate contracts. FNS and CMS officials told us that they have discussed opportunities to expand use of The Work Number through the Hub for SNAP verifications when CMS’ current contract with Equifax expires in 2018 and the service is reprocured. In addition, FNS officials told us that FNS could also consider negotiating a separate, single contract for The Work Number that would allow all state SNAP agencies to access the match, but would first explore possibilities that involved access through the Hub. Various options have the potential to result in cost savings such as through volume pricing discounts or enabling the use of the match across programs.

FNS Has Not Widely Disseminated Promising Practices for Data Matching or Assessed Options to Reduce Commercial Data Costs

Despite FNS’ current efforts, 32 states reported that more information from FNS on promising data matching practices, such as on the use of different data matches or on ways to filter data to streamline worker follow-up, would be extremely or very useful, according to our survey. However, information on such practices available on FNS websites is limited, based on our review. FNS uses both its public website and its PartnerWeb site (a web portal available to state agencies and others) to publish guidance, share information on state practices, and communicate other information to SNAP agencies. Officials at one FNS regional office said that, while states may engage in more informal communication with other states in their region, the PartnerWeb site serves as a broader source of information that can facilitate additional communication across states about relevant practices. Through these websites, FNS has provided detailed information on what states are doing to modernize their SNAP eligibility systems and processes in areas such as states’ use of call centers, document imaging, or alternative methods for managing SNAP caseloads. However, based on our review of FNS’ websites, we found few documents with specific information on data matching strategies, such as data brokering (allowing access to various data sources in a centralized portal), data filtering (using data analytics and information on program rules to better identify discrepancies and prioritize follow-up), or automatically populating the eligibility determination system (information obtained from reliable matches are automatically added to a client’s SNAP case file). For example, an FNS document on one of the websites listed states that used data brokering, but did not include information that described the practice in detail or its implementation. Additionally, although FNS has been engaged in recent efforts to test new data matching practices described earlier, such as the NAC, it has not yet widely disseminated findings from the NAC evaluation to states. FNS officials told us that they submitted these findings to Congress and relevant stakeholders in May 2016 and intend to more broadly disseminate the information once a determination has been made regarding the pilot’s future expansion. In our survey, 28 states said that information from FNS on cross-state data matching or sharing would be extremely or very useful. Accordingly, timely dissemination of findings from the NAC evaluation would be useful for states, even while decisions regarding its expansion are pending.

Regarding other state practices, FNS officials told us that they would typically consider disseminating information on data matching practices considered effective based on evidence, and not necessarily on state practices that have not been evaluated. While supporting and sharing information on practices that have been proven effective is vital, information on various implementation and program administration issues are also useful for agencies operating programs. Likewise, officials we interviewed from three of the six states said that it would be useful for FNS to facilitate additional information sharing on state practices, such as implementation issues, so they could be aware of how other states were implementing data matches:

Officials from one state said FNS could provide information about whether other states were effectively using data matches that they found challenging to implement in their state.

An official from a second state said that FNS could serve as a clearinghouse for state practices on data matching. While this official acknowledged that FNS’ guidance on data matches needed to be relatively high level, this official said that more specific information on what other states were doing to implement data matches would be useful and that FNS could play a more active role in facilitating this type of information sharing.

An official from a third state said it would be helpful to get additional information about state practices so states would not have to “reinvent the wheel” each time and could learn from each other.

Our prior work on collaboration practices has shown that agencies can enhance and sustain collaborative efforts and identify and address needs by leveraging resources, such as through information sharing. In other work on human services integration, we have found that federal agencies can help states improve their information systems by acting as a facilitator to help states work together and share their models with other states. Additionally, federal standards for internal controls call for agencies to communicate necessary quality information to external parties in order to achieve the agency’s objectives. If FNS took additional steps to facilitate information sharing on promising practices, state SNAP agencies would be better positioned to improve program integrity, experience greater administrative efficiencies, and place fewer burdens on SNAP applicants and recipients. States would also be better able to leverage existing knowledge and resources and avoid duplicative efforts.

Further, although FNS is beginning to explore ways to reduce the costs of The Work Number for state SNAP agencies by working with CMS to expand its use through the Hub, it has not yet systematically analyzed spending and SNAP data needs for this service and more thoroughly considered how various factors would affect costs. For example:

Not all states currently access The Work Number for Medicaid eligibility through the Hub, according to CMS officials. Although there is potential for expanding Hub use among states, it is unclear how much cost savings would result if some states do not use the Hub to access The Work Number, and FNS officials indicated that they had not yet gathered information from states to assess this.

CMS and FNS officials told us they are currently considering expanded use of The Work Number through the Hub for joint cases involving both Medicaid and SNAP benefits. Thus, states may still need to maintain individual contracts for The Work Number for SNAP cases that do not include Medicaid or related health programs, and it is unclear what subsequent cost implications there might be for these state-level contracts. FNS officials indicated that they had not yet obtained information on the extent that states would need to maintain individual contracts for SNAP-only cases and analyzed how state spending for the service would be affected.

CMS and FNS officials told us that there was the potential for cost savings in facilitating use of the match across programs (i.e., a state agency would not need to run a query twice for a case that includes both SNAP and Medicaid). However, CMS officials did indicate that the price CMS pays Equifax to allow states access to The Work Number through the Hub would likely increase if they were to expand its use to other programs and said they needed to work through cost implications of possible scenarios.

Both GAO and the Office of Management and Budget have emphasized opportunities for agencies to lower prices, reduce duplication, and reduce administrative costs by leveraging the government’s buying power through practices such as strategic sourcing and category management. For instance, in 2013, we found that leading commercial companies achieve savings by pooling purchases by using various practices, including analyzing spending of purchased services across entities, understanding the needs or requirements of services across various users, and promoting transparency about acquisitions within the organization to help identify inefficiencies. It is possible that the options FNS is exploring with CMS could help lower the cost of The Work Number across multiple government users by leveraging the government’s buying power. However, FNS will not be able to identify informed ways to best do this without conducting a more thorough analysis of SNAP data needs and spending across state and federal-level contracts and in relation to other programs.

Conclusions

Data matching is a tool that has the potential to help SNAP agencies increase program integrity, improve administrative efficiency, and reduce household burden. The extent to which these benefits occur, however, may sometimes depend on the characteristics of the match or the use of promising data matching practices. Although FNS has efforts under way to promote the use of data matching to improve SNAP, it has not yet widely disseminated information on the results of all of these efforts or taken steps to more broadly facilitate information sharing about other promising data matching practices that states employ. With wider, timely dissemination of promising practices, state SNAP agencies will be better positioned to be aware of potentially useful ways to help them address implementation issues and improve the effectiveness of their data matching processes. Additionally, we applaud the interagency work done by CMS, FNS, and other agencies to try and reduce duplicative work across programs and promote the use of technology advances to facilitate program integration overall. These efforts are important, as is sustained attention to make further progress toward effective solutions. FNS has also taken initial steps to explore ways to reduce costs related to the use of commercial data services, such as through cross-program efficiencies. However, FNS, working with CMS as appropriate, has not yet systematically analyzed spending and taken steps to understand data needs for these services. Without such an approach, FNS will not be able to identify the best ways to leverage the government’s buying power through strategic sourcing practices and potentially reduce costs and improve performance.

Recommendations for Executive Action

We recommend that the Secretary of Agriculture: 1. Take additional steps to collect and disseminate information on promising practices that could help improve data matching processes among state SNAP agencies, including broad and timely dissemination of information on results of recent relevant pilots or demonstrations. 2. Work with HHS (as appropriate) to analyze spending and understand data needs for SNAP across federal and state contracts and in relation to other programs as FNS explores ways to potentially reduce the costs of using commercial data services.

Agency Comments and Our Evaluation

We provided a draft of our report to USDA, HHS, and SSA for review and comment. On September 21, 2016, FNS officials from SNAP’s Program Development Division and SNAP’s Program Accountability and Administration Division provided us with the agency’s oral comments. FNS officials told us that they agreed with the recommendations in the report. They noted that they have been moving in the general direction of these recommendations and would build on current efforts to address them. FNS and SSA also provided technical comments, which were incorporated into the report as appropriate. HHS did not have any comments on the report.

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If you or your staff have any questions about this report, please contact me at (202) 512-7215 or brownke@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this report. Key contributors to this report are listed in Appendix I.

Appendix I: GAO Contact and Staff Acknowledgements

GAO Contact

Kay E. Brown, 202-512-7215, brownke@gao.gov.

Staff Acknowledgements

In addition to the contact above, Gale Harris (Assistant Director), Theresa Lo (Analyst-in-Charge), David Reed, and Russell Voth made key contributions to this report. Also contributing to this report were Holly Dye, Alexander Galuten, David Lin, Jean McSween, Mimi Nguyen, and Jerome Sandau.