Better Data Sharing for Benefits Delivery

Robust federal assistance programs and social services are essential to a thriving society. This is especially the case as people continue to contend with the fallout from the COVID-19 pandemic, which jeopardized livelihoods and put millions out of employment. Government benefits at the federal, state, and local level help people across the country pay for food, housing, health care, and other basic living expenses. But more work is required at the federal level to ensure that these benefits reach everyone in need. For instance, the historic $1.2 trillion Infrastructure Investment and Jobs Act signed into law last year included a $14.2 billion program called the Affordable Connectivity Program (ACP) to help qualifying low-income households pay for internet service. While the program is off to a strong start, improved data sharing between federal agencies, state and local governments, and institutions can leverage existing data from other benefits programs to streamline eligibility processes and ensure those who qualify receive the benefit. Expanding data sharing for benefits eligibility also aligns with one of the goals in the recent executive order to advance racial equity.

We discuss how data sharing could be improved, as well as other steps that the federal government can take to maximize the impact of this benefit on the digital divide. The solutions outlined here can be applied to both current and future programs that help people find housing, prepare children for school, and ensure everyone has enough to eat.

Leveraging eligibility data from other government programs and promoting “cross enrollments'' is a baseline necessity to maximizing benefits. Cross-enrollments link existing data and/or eligibility determinations from one public benefit program to determine eligibility for another program, reducing both administrative steps and burdensome enrollment procedures. This also allows applicants to bypass having to manually provide some or all of the necessary documentation. In the case of the ACP’s National Verifier system, USAC already shares data with the U.S. Department of Housing and Urban Development (HUD) to verify participation in the Federal Public Housing Assistance program (FPHA) and with the Centers for Medicare and Medicaid Services (CMS) to verify participation in Medicaid. Cross-enrollment would allow qualified FPHA or Medicaid recipients to automatically be certified for Lifeline and ACP. In order to add new eligibility categories for the ACP, such as participation in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), USAC would need to identify and establish connections with databases that could be used to automatically verify eligibility based on participation in WIC. This means that USAC might have to enter into memoranda of understanding (MOU) or computer/data matching agreements (CMA) with each state and local agency to automate the process of verifying applicants and administering the benefit. USAC would also need to enter into interconnection security agreements with relevant state and local agencies to ensure the data being accessed will be protected in accordance with federal standards for privacy and information security to protect the personal information of WIC participants.

Data linkages can also help with renewal of program benefits. Most programs require periodic re-verification of eligibility, usually annually. This can be an onerous process resulting in eligible participants losing their benefits. Through data sharing, recertification from one assistance program can be used to extend eligibility for another program.

Legal issues, capacity constraints, fragmented data systems, and privacy concerns across federal and state governments can pose significant challenges to sharing data that would streamline cross-enrollments for many benefits programs.

• Perceived legal and privacy barriers: Many government administrators are wary of developing data-sharing agreements with other agencies for fear of legal concerns or issues of privacy in data sharing. These concerns, often unfounded, can delay MOUs and other types of sharing agreements.
• Outdated and incompatible legacy data infrastructure: Just as benefits programs have been developed in fragmented ways, the systems developed to support them were implemented in fragmented ways. Many parts of the government data infrastructure at the federal and state level are outdated and unable to effectively keep up with data demands from new programs like ACP. This is not a new issue; the Government Accountability Office in a 2016 report described the federal government’s heavy reliance on legacy systems.¹ State eligibility systems are in need of modernization as well, as past efforts such as the funding of integrated eligibility systems (IESs) have had mixed success.
• Capacity constraints: Agencies often lack clear procedures for sharing administrative data. Navigating this process, which includes issues of data quality, lack of data documentation, and interoperability and compatibility for linking data lead to capacity and budget constraints that hinder data sharing.

The challenges of improving government data sharing and infrastructure are not new. Various attempts have been made over the last three decades to improve and better integrate government data systems, through periodic legislation enacted to address the issue, such as the Paperwork Reduction Act of 1995 and the E-Government Act of 2002, and other administrative programs and pilots, such as the federal State Systems Interoperability and Integration Project. However, there are currently a number of promising legislative and technical initiatives to improve government data sharing, including the following:

• The COVID-19 pandemic highlighted the need to improve and accelerate government data sharing, and sparked efforts to improve the public data landscape, such as CDC’s Data Modernization Initiative (DMI), a large-scale project to modernize the data infrastructure of federal and state agencies. The DMI aims to standardize data use and sharing agreements, transform legacy public data systems, and improve interoperability across federal and local data systems. Though the goal of the DMI is to improve sharing and reporting of health data, the establishment of this framework would positively impact sharing of benefits eligibility data as well.
• The current Federal Data Strategy Action Plan calls for accelerating practices that “increase the sharing and use of data for federal decision-making and operational needs,” and the Chief Data Officers Council recently solicited feedback on how best to achieve that goal.
• Improving data matching algorithms for data sharing, an important aspect of streamlining data linkages, is currently being addressed by 18F, a special technology and design consultancy within the General Services Administration. They have launched an Eligibility APIs Initiative to develop application programming interfaces (APIs) to help federal, state, and local governments update their benefits systems when policy changes. When new benefits programs that require data across various agencies and states—such as ACP—are created, APIs can allow for clearer communication and data linkages for eligibility determinations. Beyond the API work of 18F, capabilities are also needed in the government to employ emerging analytical methods for matching data that may drive more accurate data linkages, including machine learning and neural networks.

Improving data sharing to enable more cross-enrollments will involve solving challenges in several areas:

• A culture and clear framework that enables benefits data sharing: Federal law and most states authorize data sharing for appropriate governmental purposes, including benefits administration. However, legal and privacy concerns are consistently identified as a significant barrier to creating data sharing agreements. While this sometimes results from misinterpretation of laws and policies, it is often due to ambiguous or inconsistent federal and state laws, and absence of clear regulations. This ambiguity gives rise to a culture that is risk averse beyond the actual risks posed by legal rules, leaving a status quo of ad hoc data sharing and lengthy sharing agreement processes. There is a need for clear legal and organizational policies that create a foundation to support the sharing of data while protecting privacy.
  
  Now that federal agencies and most states have chief data officers, CDOs can provide the leadership to establish a culture of data sharing through setting the tone and direction, prioritizing sharing and collaboration, and developing clear data and privacy policies that can accelerate the formation of data sharing agreements.
  
  The Federal CDO Council and the State Chief Data Officers Network are well positioned to build a culture of data sharing in government and to provide guidance and clarification on appropriate data linkages. The CDO Council has a Data Sharing working group, and the State Network is engaging in projects such as generalizing MOU language to streamline the sharing of data. We recommend both groups prioritize facilitating data sharing for purposes of benefits cross-enrollments in their work. This work should include cataloging the regulatory and legal restrictions on data sharing for benefits eligibility and renewal, providing sample data sharing templates that agencies can use in developing their data sharing practices, and identifying opportunities for cross-enrollment. The chief dataofficer groups should draw from the expertise of organizations such as Actionable Intelligence for Social Policy (AISP), which works with state and local governments to develop data sharing capacities.
• Building capacity and an interoperable data infrastructure: Lack of data documentation can make data sharing processes difficult and time consuming. Many agencies do provide useful data dictionaries and documentation, but there is a lack of standardization for data documentation across government, as well as gaps in updating shifting data definitions and other important data changes over time. Sharing data can thus require significant time investment from personnel, who may need to acquire knowledge about key data attributes and variables across datasets. Current government data standardization initiatives, such as the Data Standards Repository (established by the 2020 Federal Data Action Plan) and the National Information Exchange Model, should be leveraged to streamline data sharing for benefits eligibility.
  
  To enable and streamline data linkages, we recommend the development of further cross-government projects (such as the aforementioned API Eligibility Initiative), as well as innovative projects to develop tools and applications that allow for enrollment in more than one benefit at once.
  
  Funding, of course, is an oft-cited barrier to data sharing, and increasing data sharing for benefits eligibility will require significant investments in building a more interoperable data infrastructure, modernizing systems (such as state integrated eligibility systems), and developing administrative capacity for linking data.

Streamlining enrollment processes through sharing data across programs can help individuals and families receive benefits from ACP and other programs without burdensome, redundant applications, eligibility screenings, and verifications. At the same time, reducing steps in eligibility determination and recertification can realize administrative savings through increased efficiencies and the reduction of improper payments. The COVID-19 pandemic has changed the status quo by highlighting obstacles to government data sharing and the need to enable and accelerate better sharing.

At all levels of government, the lack of clear guidelines for data sharing⁠—combined with penalties for improper data use⁠—results in a reticence to share data and inhibits the completion of data sharing agreements in a timely manner. Establishing clear legal and leadership guidance at both the federal and state levels on allowable data sharing and data disclosures, while working to improve data interoperability and infrastructure, can help build more efficient benefit verification processes and increase program enrollments to deliver vital help to those in need.

¹ Three years later, the agency found that only three out of the 12 agencies they had examined had implemented their recommendation and made progress in planning to modernize their legacy systems.

² p. 12.