Identifying children at risk for maltreatment fatalities: assessing the Current landscape of birth match policies in the United States

Data-driven decision-making is a common approach for identifying child maltreatment. However, such strategies must be guided by ethical, equitable, and evaluative frameworks due to their potential for bias and error. This study analyzes the key features, potential challenges, and research evidence of a data-driven strategy known as Birth Match. Interviews with key informants across four states indicate that programs share features and objectives but that they differ regarding match criteria, data integrity processes, and responses to identified cases. Further, little outcome and equity evidence exists. Results emphasize the need for additional implementation and evaluation infrastructure to ensure transparency and effectiveness.