Across the country, one of the biggest impediments to improving the impact of government programs serving vulnerable and marginalized populations is a lack of insight into the complex factors that contribute to better outcomes. To understand the root causes of poor health and economic security and develop effective solutions, governments must be able to integrate and analyze data from siloed services that serve those populations. While some states and localities have prioritized integrated data and analytics, many others point to a lack of state and local resources and a lack of clarity about whether and how federal funds can be used to create enterprise-wide data capacity that spans multiple programs.
There’s an exciting new development. Last month, Treasury issued interim regulations that include explicit authority for states and localities to use some of the $350 billion in State and Local Fiscal Recovery (SLFR) funds to “build their internal capacity to successfully implement economic relief programs, with investments in data analysis, targeted outreach, technology infrastructure, and impact evaluations.” By setting aside a small fraction of their SLFR allocations to build and strengthen cross-program analytics capacity, State and local governments can achieve an enormous return on investment that improves outcomes, advances equity, and increases efficiency.
In order to spend Rescue Plan relief funds effectively in the near term and strengthen government results for the long term, states and localities should be able to answer questions such as:
- Which sub-groups are in greatest need of benefits and services and what are the best channels for reaching them?
- What mix of services and benefits is optimal for different sub-groups, and how could their delivery be better coordinated?
- What outcomes are program investments achieving, by subgroup and geographic area, and what gaps must be closed to achieve equitable outcomes for underserved populations?
- What interventions have the greatest impact and cost-effectiveness?
- What upstream prevention strategies produce better outcomes and reduce downstream costs in other programs?
- What operational streamlining would improve the user experience and reduce costs?
- What major sources of improper payments are readily discoverable by merging data across programs?
Answering these questions requires a better understanding of the intersection and interaction of programs serving different needs of overlapping populations: health, nutrition, income security, childcare, education and training, housing, and related community supports. Traditionally, federal funding for state and local data capacity has focused on building and maintaining program-specific IT systems designed to ensure compliance with eligibility and program delivery requirements. By building data analytics capacity that extracts and merges data from these disparate systems, states and localities can gain critical insights about how to help program beneficiaries access the optimal mix of services and benefits, delivered in human-centered and efficient ways, so that program investments lead to better outcomes.
Fortunately, leading state and local governments have forged ahead to demonstrate how robust data capacity can be created with modern, low-cost technology, in ways that protect individual privacy and generate aggregated statistics to inform decisions. There are a range of models that these jurisdictions are using. For example:
- In-house: Washington, South Carolina, Ohio, and Allegheny County, Pennsylvania– sometimes with assistance from contractors -- have built internal capacity to securely link and analyze data not only across programs, but across systems and sectors. They use in-house staff to generate analyses and also partner with external academics to augment their research and conduct evaluations. California recently launched CalData, a state data strategy that will integrate early childhood, K-12, financial aid, higher ed, and health and human services data.
- Government-university partnerships: A number of states have partnered with universities to allow government data to be held in secure environments managed by universities. Academic data scientists and researchers collaborate with government agencies to use the data, with privacy protections, to generate actionable insights on important policy questions. Some of these arrangements are state-specific, such as the California Policy Lab and the Colorado Evaluation and Action Lab. Other organizations that began inside universities are broadening their focus to serve multiple states. For example, the Coleridge Initiative is helping over 40 states learn how to use merged cross-state and cross-agency data in the Administrative Data Research Facility to analyze and improve education and workforce development strategies. Research Improving People's Lives, based in Rhode Island, is extending its services to other states and localities seeking to use data and science to move people from poverty to prosperity.
Innovative state and local governments are also building capacity to merge government data with data held by community-based organizations to improve child and family services, especially for marginalized populations. North Carolina supports NCCARE360, a shared technology platform to unite healthcare and human services organizations to deliver coordinated, human-centered services and report outcomes. The Camden Coalition's Health Information Exchange links healthcare and other records across southern New Jersey to better identify and serve individuals with unmet needs.
The unprecedented flexibility of the SLFR funding allows states and localities to design and build data infrastructure and analytics capacity tailored to their own needs, leveraging their existing platforms, staff expertise, and partnering arrangements that vary considerably across jurisdictions. For example, some states may want to use their education State Longitudinal Data System as the backbone for integrating data from other systems. Other states may prefer to use their healthcare platform as the backbone. Under either scenario, SLFR funds can create the connective tissue and analytical support to transform disconnected data held in siloed systems into actionable insights that improve outcomes, equity, and cost-effectiveness.
Once developed, a robust platform for integrating and analyzing high-value data can address a multitude of needs and policy-relevant questions that are important to government decision-makers, program beneficiaries, and the general public. Creating this capacity will be a necessary foundation for truly advancing equity in the allocation and delivery of services and benefits. States and localities should not let this window of opportunity pass.
Read Additional Posts from the American Rescue Plan Series:
Part 1 | Part 2 | Part 3 | Part 4 | Part 5 | Part 6 | Part 7 | Part 8 | Part 9