We continued Rules as Code Demo Day with Daniel Singer and Preston Cabe from Benefits Data Trust. Benefits Data Trust provides benefit outreach and application assistance services in seven states. Using Benefits Launch, their in-house interview and rules engine, they support two hundred contact center employees as they screen and apply thousands of clients each year. They also offer a self-service screener, Benefits Launch Express. Additionally, they offer an eligibility API to integrate with other services.
In February 2023, the Digital Benefits Network at the Beeck Center for Social Impact + Innovation released a dataset documenting authentication and identity verification requirements that unemployment insurance (UI) applicants encounter across the United States. This resource outlines high-level observations from the data and more information about the research process.
At Rules as Code Demo Day we heard from Song Hia of the NYC Mayor’s Office for Economic Opportunity and Ethan Lo of the NYC Office of Technology and Innovation who demoed the NYC Benefits Platform Screening API which provides machine-readable calculations and criteria for benefits screening that power the ACCESS NYC screening questionnaire. This makes it easier for NYC residents to discover multiple benefits they may be eligible for. The City is now extending the API to support the new MyCity platform, a one-stop shop for all services and benefits.
This resource outlines strategies for cross-enrollment outreach, which can break down silos between programs and reach applicants who may be eligible for under-enrolled benefits programs.
NYC Opportunity collaborated with the Administration for Child Services (ACS) to design a family-centered process for prevention services, addressing confusion and lack of choice in the current system. By creating tools like the Provider Profile and Family Voice booklet, the team empowered families to choose providers based on their needs while ensuring their feedback reaches ACS. The project aims to improve family experiences and communication with ACS, with plans to expand through testing and future innovations like a web portal.
Oklahoma Human Services (OKDHS) modernized their service delivery by reducing their real estate footprint, designing trauma-informed and user-friendly spaces, and expanding an embedded worker program to improve accessibility and client experience. Through their "Service First" strategy, OKDHS aims to create more equitable and compassionate interactions, reaching vulnerable populations while addressing high occupancy costs.
In response to COVID-19, the Workers Lab and Steady developed the "Income Passport" to streamline gig workers' unemployment benefit applications by pulling income data directly from gig platforms and financial accounts. This tool reduced manual verification time, helped prevent fraud, and improved workers' access to full benefits, with successful tests in Alabama and Louisiana demonstrating significant time savings and improved service delivery.
Alluma is a nonprofit that provides digital solutions to simplify eligibility screening and enrollment for social benefit programs, supporting cross-benefit access in 45 counties and two states. Their One-x-Connection product suite streamlines Medicaid and SNAP applications using a business rules engine, with a focus on human-centered design and anonymous, simplified eligibility checks, having helped screen over 10 million individuals and submitted over 67 million applications.
Across the United States, a number of state and local governments are embarking on digital transformation efforts. This case study is part of the Beeck Center’s Digital Service Teams project, which is learning how leading government digital service units are introducing new approaches to service delivery. Beeck Center researchers are documenting work as it happens, including analyzing challenges and opportunities, and disseminating this information to benefit both the people of New York City and collaborators in other governments.
The team conducted experiments to determine whether clients would be responsive to proactive support offered by a chatbot, and identify the ideal timing of the intervention.
