Understanding the Consequences of Hurricane Katrina for ACF Service Populations: A Feasibility Assessment of Study Approaches

Published: April 15, 2008
Topics:
Other
Projects:
Feasibility Assessment of Studying the Consequences of Hurricane Katrina for ACF Service Populations, 2006-2008 | Learn more about this project
Types:
Reports

This report is a feasibility assessment—an analysis of alternative datasets and analytic approaches that might be used to assess the effects of Hurricane Katrina on populations served by the Administration for Children and Families (ACF) of the U.S. Department of Health and Human Services (HHS). Understanding these effects would help ACF serve two purposes: to address the needs of Hurricane victims who will continue to need help from a range of programs that ACF administers; and to identify lessons for delivering services in future disasters—including how to build data systems to track clients, and how to create relationships across programs and jurisdictions that would connect people to needed services in the context of a disaster.

The assessment identifies ways of answering four overarching research questions of practical and policy importance to ACF: where did populations of interest go when Hurricane Katrina struck in August 2005 (migration and housing); how are they doing (income and employment); what are their needs for ACF programs and services; and how did the disaster affect the ACF programs themselves? In each of the four, the review further asks, implicitly or explicitly, how changes resulting from Katrina affect child and family well-being. The analysis is concerned with assessing changes over time and across geographic areas and, importantly, how to track families as they relocate or return, and as their needs change over time.

The assessment emphasizes using existing datasets to their greatest effect, and innovative uses of administrative data as they are currently collected. In a small number of instances, the utility of new data collection is noted, as well as opportunities for adding new markers into existing datasets, which might, for example, be used to identify program participants affected by a disaster and follow them over time and across jurisdictions to ensure they get the services they need.