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Data disaggregation as a means to improved health research and policy-making

Past Event

Introduction and Welcome

Concluding discussion and summary of next steps
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Concluding discussion and summary of next steps

Researchers and policy makers have initiated a recent push towards improved data availability to inform evidence-based policy making. Often the goal of research and policy is to examine differences in outcomes across pre-determined demographic, socio-economic, or geographically distinct populations, and to address the root causes of any documented disparities in these outcomes. In particular, basic socioeconomic differences across racial and ethnic groups must be recognized and studied in order to adequately address health and welfare disparities. Using only average group characteristics in this type of analysis may mask important differences for heterogeneous groups or communities and result in unsuccessful policies.

To adequately address such questions, data must be available at a sufficiently disaggregated level so that the populations of interest are identifiable and there is sufficient statistical power to produce credible empirical estimates. The question of what level of disaggregation is suitable in different settings is not trivial. On September 26 the Economic Studies program at Brookings organized a conference to highlight and discuss issues related to data disaggregation as a means to improve the quality of empirical work and policy effectiveness with an emphasis in health and well-being.

Download full agenda here. 

Agenda

Introduction and Welcome

Panel 1: “Critical Needs for Data Disaggregation for Race and Ethnic Groups” – Why do we need to disaggregate?

John C. Yang

President and Executive Director - Asian Americans Advancing Justice | AAJC

Yvette Roubideaux

Vice President for Research and Director, Policy Research Center - National Congress of American Indians

Academic session 1

Paper 1:  “Asians and Hispanics Earnings Inequality in Administrative Data”
Randall Akee, Maggie R. Jones, Sonya Rastogi Porter and Emilia Simeonova
Discussant: Marcus Casey, Brookings Institution

Paper 2:  “Disaggregating Data to Advance Health Equity: the Case of Native Hawaiians and Pacific Islanders”
Sela Panapasa and James McNally, University of Michigan
Discussant: Emilia Simeonova, Johns Hopkins

Academic session 2

Paper 3: “Analyzing the Impact of Differential Privacy on the Accuracy Decennial Census Data”
David Van Riper, University of Minnesota
Discussant: Ravi Aron, Johns Hopkins Carey School of Business

 

Paper 4: “Welfare Reform and Adolescents: Are the Boys Alright?”
Dhaval Dave, Nancy Reichman, Hope Corman
Discussant: Valentina Duque, University of Sydney

 

Paper 5: “Disaggregating the Data for Bisexual People”
Shabab Ahmed Mirza, Center for American Progress
Discussant: Phil Phan, Johns Hopkins Carey Business School

Panel 2: “Data collection and data access: current issues and future challenges” – Where disaggregation is going and obstacles

Ninez Ponce

Director - UCLA Center for Health Policy Research, UCLA

Meagan T. Khau

Director, Data and Policy Analytics Group - Centers for Medicare & Medicaid Services

Moderator

Emilia Simeonova

Associate Professor - Johns Hopkins Carey Business School

Concluding discussion and summary of next steps

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