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Classifying and Describing Exemplary Data Use in Temporary Assistance for Needy Families (TANF) Agencies

Author

Listed:
  • Emily Wiegand
  • Leah Gjertson
  • Emma Monahan
  • Robert Goerge

Abstract

State human service agencies often collect a wealth of administrative data, but the extent to which those data are accessed and leveraged for evaluation or program improvement varies greatly across time, states, and agencies. The current study is focused on data use in state agencies administering the Temporary Assistance for Needy Families (TANF) program, a federal cash assistance program for families with low incomes. Using data from a national needs assessment administered to state and territory TANF agencies (n = 43), we identified three categories of data use: basic (describing 22 state TANF agencies; 51%), advanced (9; 21%), and exemplary (12; 28%). We examined the relationship between data use and agency characteristics and found that a culture of communication, collaboration, and transparency around data, as well as the development of quality external partnerships, are associated with higher quality agency data use. Factors like new data systems, data access tools, or increased financial resources were not consistently associated with higher quality agency data use; in particular, new data systems were inversely correlated with data use in the years immediately after implementation. 州级人类服务机构通常会收集大量的行政数据, 但这些数据被访问和利用以进行评价或改进的程度在不同时期、州和机构之间存在很大差异。本研究聚焦于那些管理贫困家庭临时援助计划(TANF)的州级机构的数据使用情况, TANF计划是一项针对低收入家庭的联邦现金援助计划。通过使用对州和领地TANF机构(n = 43)进行的一项国家需求评估的数据, 我们确定了三类数据使用情况:基础类 (描述22个州级TANF机构；占51%) 、高级类 (9个；占21%) 和示范类 (12个；占28%) 。我们研究了数据使用与机构特征之间的关系, 发现(拥有一个)围绕数据的传播、协作和透明度的文化, 以及建立高质量的外部合作伙伴关系, 与更高质量的机构数据使用相关。新的数据系统、数据访问工具、或增加的财政资源等因素并非始终与更高质量的机构数据使用相关；具体而言, 在实施后的几年内, 新的数据系统与数据使用呈负相关。 Las agencias estatales de servicios humanos suelen recopilar una gran cantidad de datos administrativos, pero el grado en que se accede a ellos y se aprovechan para la evaluación o la mejora de los programas varía considerablemente según el tiempo, los estados y las agencias. El presente estudio se centra en el uso de datos en las agencias estatales que administran el programa de Asistencia Temporal para Familias Necesitadas (TANF), un programa federal de asistencia financiera para familias de bajos ingresos. Utilizando datos de una evaluación nacional de necesidades realizada a las agencias estatales y territoriales de TANF (n = 43), identificamos tres categorías de uso de datos: básico (que describe 22 agencias estatales de TANF; 51%), avanzado (9; 21%) y ejemplar (12; 28%). Examinamos la relación entre el uso de datos y las características de las agencias y descubrimos que una cultura de comunicación, colaboración y transparencia en torno a los datos, así como el desarrollo de colaboraciones externas de calidad, se asocian con un uso de datos de mayor calidad por parte de las agencias. Factores como nuevos sistemas de datos, herramientas de acceso a los mismos o mayores recursos financieros no se asociaron consistentemente con un uso de datos de mayor calidad por parte de las agencias; en particular, los nuevos sistemas de datos mostraron una correlación inversa con el uso de datos en los años inmediatamente posteriores a su implementación.

Suggested Citation

  • Emily Wiegand & Leah Gjertson & Emma Monahan & Robert Goerge, 2025. "Classifying and Describing Exemplary Data Use in Temporary Assistance for Needy Families (TANF) Agencies," Poverty & Public Policy, John Wiley & Sons, vol. 17(2), June.
    • Handle: RePEc:wly:povpop:v:17:y:2025:i:2:n:e70019
    DOI: 10.1002/pop4.70019
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    References listed on IDEAS

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    1. Robert M. Goerge, 2018. "Barriers to Accessing State Data and Approaches to Addressing Them," The ANNALS of the American Academy of Political and Social Science, , vol. 675(1), pages 122-137, January.
    2. David C. Ribar & Marilyn Edelhoch & Qiduan Liu, 2008. "Watching the Clocks: The Role of Food Stamp Recertification and TANF Time Limits in Caseload Dynamics," Journal of Human Resources, University of Wisconsin Press, vol. 43(1).
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