The Temporary Assistance for Needy Families (TANF) Data Collaborative Pilot Initiative is a component of the TANF Data Innovation project. The 30-month pilot offered technical assistance and training to support cross-disciplinary teams of staff at eight state and county TANF programs in the routine use of TANF and other administrative data to inform policy and practice.
The Temporary Assistance for Needy Families (TANF) Data Collaborative Pilot Initiative is a component of the TANF Data Innovation project. The 30-month pilot offered technical assistance and training to support cross-disciplinary teams of staff at eight state and county TANF programs in the routine use of TANF and other administrative data to inform policy and practice.
This brief describes the TANF Data Collaborative (TDC), an innovative approach to increasing data analytics capacity at state Temporary Assistance for Needy Families (TANF) agencies.
This toolkit offers strategies and tools to help agencies build the culture and infrastructure needed to apply data analysis routinely, effectively, and accurately – referred to in this publication as “sustainable data use.” It covers a variety of subjects – from staffing and technology to collaboration and funding – that can impact the longevity of analytics work in the public sector.
This article explores how although SNAP and Medicaid programs have succeeded in narrowing health and nutrition disparities, certain policies hinder goals of racial and ethnic equity, even though they do not explicitly mention race or ethnicity.
Initially created to inform federal staff at the U.S. Department of Health and Human Services, this tip sheet highlights the importance of using equitable communication and includes tips, guiding questions, and additional resources.
Office of the Assistant Secretary for Planning and Evaluation (ASPE)
Initially created to inform federal staff at the U.S. Department of Health and Human Services, this tool describes how to conduct intensive equity assessments of existing programs, policies, and processes. It may be useful for state and local governments, tribal governments, and other private or non-profit organizations focused on programs and policies relating to health and human services.
Office of the Assistant Secretary for Planning and Evaluation (ASPE)
Initially created to inform federal staff at the U.S. Department of Health and Human Services, this guide explores opportunities to advance equity in quantitative analysis, including by recognizing common biases (e.g., research and measurement bias). The guide also discusses specific quantitative methods and tools to help quantitative analyses address equity.
Office of the Assistant Secretary for Planning and Evaluation (ASPE)
This guide explores intersectionality and why it is essential for advancing equity. It explores strategies for planning and conducting research with an intersectional lens, describes quantitative measures and methods to examine differences across groups of people with intersecting identities, and provides key considerations for using qualitative data to better understand intersectionality.
Office of the Assistant Secretary for Planning and Evaluation (ASPE)
Originally created for use by federal staff at the U.S. Department of Health and Human Services, this tool describes the six steps for conducting equity assessments and provides tips for completing each step. This resource may be relevant for state and local governments, tribal governments, and other private or non-profit organizations focused on programs and policies relating to health and human services
Office of the Assistant Secretary for Planning and Evaluation (ASPE)
The goal of the brief is to encourage policy makers and employers to consider benefits cliffs as they look to create mandatory wage increases, with a look at a legislative action in NYC.
This post from the Center on Budget and Policy Priorities argues that the traditional measures of program performance say little about the human experience of accessing benefits, and argues for enhanced performance metrics to support more human-centered delivery.
