This report explores innovative solutions and insights from CMS Innovation Center's Hackathon series to address the unique healthcare challenges faced by rural, Tribal, and geographically isolated communities.
A modern system that helps people learn about, apply for, and gain access to affordable housing. Bloom Housing is an open source platform that digitizes the process of finding and applying for affordable housing, turning a time-consuming paper process into a 15 minute activity from one's smartphone or computer.
This toolkit outlines actionable changes for government practitioners looking to improve the accuracy and accessibility of the questions on their forms that collect information about a user’s gender.
This panel discussion from the Academy's 2025 Policy Summit explores the intersection of artificial intelligence (AI) and public benefits, examining how technological advancements are influencing policy decisions and the delivery of social services.
This landscape analysis examines data, design, technology, and innovation-enabled approaches that make it easier for eligible people to enroll in, and receive, federally-funded social safety net benefits, with a focus on the earliest adaptations during the COVID-19 pandemic.
NYC's My File NYC and New Jersey's unemployment insurance system improvements demonstrate how successful digital innovations can be scaled across various programs, leveraging trust-building, open-source technology, and strategic partnerships.
Presentation covering the findings of a research study analyzing the structural and budgetary layout of of eleven US-based Digital Service Teams (DSTs) at the municipal, county, and state levels.
This research study analyzes the structural and budgetary layout of eleven US-based Digital Service Teams (DSTs) at the municipal, county, and state levels. In doing so, it sets out to answer the research question: “How are digital service teams structured and funded?”
In this summary, the authors use WBNS data to provide updated estimates of chilling effects in 2023 among immigrant families (i.e., in which the respondent or a family member living with them was not born in the US).
