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The Data Committee supports the Children’s Commission’s data efforts and oversees the analysis of publicly available child welfare data to identify judicial processes and practices that produce desired outcomes, as well as which practices need improvement.

Members: Hon. Susan Brown, Chair; Hon. Rosie Alvarado, Ross Baxter, Dr. Monica Faulkner, Hon. Delia Gonzales, Dr. Jangmin Kim, Elizabeth Kromrei, Hon. Robin Sage, Hon. Michael Schneider, Vicki Spriggs, Hon. Carlos Villalon, Jr. 

Staff: Dylan Moench, Chelsea Martinez 

OCA Advisory Staff: Darrell Childers, Anissa Johnson, Casey Kennedy, Mena Ramon, Jeffrey Tsunekawa, Charlotte Velasco

For more information about current Data Committee projects, please link below:

In April 2019, the Texas Alliance for Child and Family Services (TACFS), through its Research and Policy Division and with funding from the Children Commission, hired a data analyst whose job is to access publicly available data from DFPS, court-specific data, and data from the TACFS, and analyze that data in a manner that provides helpful information to the judiciary. The data analyst supports the Commission’s Data Committee by analyzing publicly available child welfare data in a manner that facilitates discussions between DFPS and judges about data, judicial processes and practices, and potential systemic improvements. Working together, the analyst and the Data Committee anticipate developing multiple projects in FY2020 including reorienting how data is presented at the Commission’s annual Child Welfare Judges Conference to engage with courts about utilizing data to improve permanency outcomes; evaluating the Permanent Managing Conservatorship Specialty Courts in Houston and Dallas; evaluating data from DFPS Region 3B as Community Based Care is implemented; creating a “data dashboard” for Child Protection Court (CPC) judges utilizing the Child Protection Case Management System data collection system so they can make the best use of their existing data; and creating guidelines for CPC judges on differentiating required data entry compared to best practice data entry.