Supplemental Nutrition Assistance Program: More Information on Promising Practices Could Enhance States' Use of Data Matching for Eligibility
Published: 2016-10-19T00:00:00

Fast Facts:

Highlights:
section_title: Why GAO Did This Study
paragraphs: During fiscal year 2015, state SNAP agencies provided about 46 million low-income individuals approximately $70 billion in federally funded benefits, and an additional $7.6 billion in federal and state funds was spent in administering the program in fiscal year 2014, according to the most recent data. SNAP agencies use data matching to verify eligibility information about applicant or recipient households, including their incomes, as well as to help detect improper payments. GAO was asked to review issues related to data matching in administering SNAP.
This report examines (1) the extent to which states use data matching to obtain income information and find these matches useful for SNAP eligibility, (2) challenges states experience using data matching, and (3) actions FNS has taken to promote data matching for SNAP. GAO surveyed all state SNAP directors for a 100 percent response rate and interviewed state officials in six states that varied in caseload size, geography, and other criteria, and visited local offices in three of these states. GAO also reviewed relevant federal laws, regulations, and agency documents and interviewed agency officials.
section_title: What GAO Found
paragraphs: In administering the Supplemental Nutrition Assistance Program (SNAP), all state SNAP agencies verify household income by conducting multiple data matches, which they find useful for detecting potential discrepancies related to SNAP eligibility (see figure below), according to GAO's survey of all state SNAP directors. Most states reported that particularly useful data matches provided current information, can be accessed in real-time (i.e., immediately), and are from original sources. Some data sources for unearned income, including from the Social Security Administration, have all these characteristics. Data matches for earned income lacked one or more of these useful characteristics, but can be used as leads to follow up on with households or employers.
States identified challenges with following up on data matches and with the costs of data matching. The issue states cited most often in GAO's survey as very or extremely challenging was the need to conduct follow-up for data that are not sufficiently recent, accurate, or complete, which can be cumbersome and time-consuming. Officials GAO interviewed in several states were implementing ways to manage follow-up. Over one-third of states also reported that costs associated with accessing certain commercial data to verify earnings were very or extremely challenging, with some states limiting their use of these data due to costs.
The Department of Agriculture's (USDA) Food and Nutrition Service (FNS), which oversees the SNAP program, has efforts underway to promote data matching to improve program administration, but may be missing some opportunities. For example, FNS has initiated pilot or demonstration projects to improve program integrity or service to households. However, FNS has not actively collected or disseminated information on promising data matching practices, consistent with federal internal controls. Further, 32 states reported in GAO's survey that more information from FNS on promising data matching practices would be extremely or very useful. With more information, states will have increased awareness of other potentially useful or cost-effective practices. In addition, FNS has begun to explore ways to help states reduce the cost of using commercial data, but has not systematically analyzed spending and SNAP needs for these data to consider how to best leverage government buying power through strategic sourcing practices. Without this analysis, FNS may not be able to identify the best ways to lower data matching costs.
section_title: What GAO Recommends
paragraphs: GAO recommends that FNS disseminate information on promising practices to state SNAP agencies, and analyze spending and data needs as it explores ways to reduce costs of using commercial data. FNS agreed with these recommendations

section_title: Letter
paragraphs: During fiscal year 2015, the Supplemental Nutrition Assistance Program  (SNAP), previously known as the Food Stamp Program, provided nutrition  assistance to almost 46 million low-income individuals each month for a  total of approximately $70 billion in federally-funded benefits for the year.  The Food and Nutrition Service (FNS) in the U.S. Department of  Agriculture (USDA) administers SNAP at the federal-level, in partnership  with states. According to the most recent data in fiscal year 2014, an  additional $7.6 billion—divided between federal and state funds—was  spent on administering the program that year, a large portion of which  was spent on certification procedures, such as collecting and verifying  information to determine whether households were eligible and, if so, for  what benefit amount. Federal laws and regulations require state SNAP  agencies to verify various aspects of SNAP eligibility; however, income  information can be particularly difficult to obtain and verify as correct. For  example, based on the most recent available data from fiscal year 2013  on improper payments made in the SNAP program, errors related to  household income were, by far, the largest cause of improper payments  over other causes of error, such as those related to household resources,  deductions, or non-financial information. To help avoid improper  payments and improve other aspects of program administration, SNAP  agencies use data matching— the process of matching information about  applicants and recipients against various data sources—as part of their  routine eligibility processes. In recent work, we have also reported that  SNAP agencies use data matching as one of various tools to detect  potential SNAP cases involving fraud.
You asked GAO to examine the use of data matching or sharing to  administer the SNAP program. In this review, we answered the following  questions:  1.  To what extent do states use data matching to obtain income  information for SNAP eligibility purposes and how useful do they find  these matches?  2.  What challenges, if any, do states experience with their use of data  matching?  3.  What actions has FNS taken to promote data matching and what  additional actions, if any, are needed?
To address these questions, we collected and analyzed information using  several methods. We administered a survey by e-mail to state SNAP  directors of all 50 states and the District of Columbia from February to  May 2016 to obtain information on all three research questions. We  obtained a 100 percent response rate. While we generally did not validate  specific information administrators reported through our survey, we  reviewed their responses and conducted follow-up, as necessary, to  determine that their responses were complete, reasonable, and  sufficiently reliable for the purposes of this report. As part of our survey  development, we pretested the questionnaire with four states, had  internal and external experts review it, and incorporated comments as  appropriate. Once we received the survey responses, they were  subjected to data entry, processing, and analysis. We verified the  accuracy at each step in the process with independent reviews. To ask  for elaborations on survey responses and other related questions, we  conducted semi-structured phone interviews with state SNAP officials  from six states that represented 31 percent of the national SNAP  caseload in fiscal year 2014 (California, Florida, Massachusetts, Texas,  Virginia, and Washington). Criteria for states we selected included  caseload size, geographic location, whether SNAP is state or county- administered, and participation in relevant demonstrations or pilots. We  also visited two to three local offices in three of these states (California,  Virginia, and Washington) to obtain perspectives from local program  managers and eligibility staff and to observe eligibility processes and  systems. Our selection criteria for localities within each state included  variation in population density and geographic location. The information  gathered from interviews with officials from selected states and localities  is not generalizable to all states and localities and is meant to provide  illustrative examples. To obtain pertinent federal-level information, we  reviewed relevant federal laws, regulations, guidance, and other  information and interviewed federal agency officials. Specifically, we  interviewed officials from FNS about pertinent initiatives, as well as  oversight, technical assistance, and guidance related to data matches.  We spoke with officials in FNS’ national office as well as a  nongeneralizable sample of three of its seven regional offices. To assess  FNS’ efforts, we reviewed prior GAO work on collaboration and strategic  sourcing and federal internal control standards. We also interviewed  officials and reviewed information from the Department of Health and  Human Services (HHS)’ Administration for Children and Families (ACF)  and Centers for Medicare & Medicaid Services (CMS), as well as the  Social Security Administration (SSA) to obtain information on relevant  data matches and other data matching or data sharing initiatives.  Additionally, we interviewed representatives with expertise on SNAP from  relevant national trade associations, private service providers, and  research or client advocacy organizations.
We conducted this performance audit from August 2015 to October 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.
subsections: section_title: Background
subsections: section_title: Determining SNAP Eligibility and Benefits
paragraphs: 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.
section_title: Use of Data Matching for Eligibility
paragraphs: 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.
section_title: States Reported Conducting Numerous Data Matches for SNAP and the Matches They Find Most Useful Provide Real- Time Access to Recent Data
subsections: section_title: All States Conduct a Range of Data Matches for SNAP, and Most States Have Implemented the Recently Required New Hire Data Match
paragraphs: 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.
section_title: Matches States Reported Finding Most Useful Provide Real-Time Access to Recent Data, and Other Matches May Detect Unreported Sources of Income
paragraphs: 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.
section_title: States Reported Challenges with Following Up on Data Matches, Using Data Matches for Multiple Programs, and Costs
subsections: section_title: Necessary Follow-Up on Data Matches Is Challenging, Especially Related to Earnings and Out-of-State Benefits
paragraphs: 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.
section_title: States Reported Barriers to Using Data Matches for Multiple Programs and the Cost of Conducting Matches as Challenges
paragraphs: 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.
section_title: FNS Has Efforts Underway to Promote the Use of Data Matching to Improve SNAP, but May Be Missing Some Opportunities
subsections: section_title: FNS Efforts Include Initiating Demonstration Projects and Pilots, Promoting Program Integration, and Working with CMS to Reduce Duplicative Processes
subsections: section_title: SNAP Demonstration Projects and Pilots
paragraphs: 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.
section_title: Program Integration Efforts
paragraphs: 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.”
section_title: Use of The Work Number
paragraphs: 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.
section_title: FNS Has Not Widely Disseminated Promising Practices for Data Matching or Assessed Options to Reduce Commercial Data Costs
paragraphs: 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.
section_title: Conclusions
paragraphs: 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.
section_title: Recommendations for Executive Action
paragraphs: 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.
section_title: Agency Comments and Our Evaluation
paragraphs: 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.
As agreed with your office, unless you publicly announce the contents of  this report earlier, we plan no further distribution until 30 days from the  report date. At that time, we will send copies to the appropriate  congressional committees, Secretaries of Agriculture and Health and  Human Services, the Commissioner of the Social Security Administration,  and other interested parties. In addition, the report will be available at no  charge on the GAO website at http://www.gao.gov.
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.
section_title: Appendix I: GAO Contact and Staff Acknowledgements
subsections: section_title: GAO Contact
paragraphs: Kay E. Brown, 202-512-7215, brownke@gao.gov.
section_title: Staff Acknowledgements
paragraphs: 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.