There are two center projects and several pilot projects within the CICM. These projects include multiple universities and various disciplines from statistics to developmental psychology and newborn medicine. Below are summaries of each project, its intention, and the leader(s) of each.

Center Projects


The Child Welfare Data SMART

(Specification, Management, Analysis, Replication & Transfer)

DataSMART is a project where states can, with modest reformatting of their in-state existing data, run “off the shelf” programs designed by national child maltreatment researchers. States wishing to use DataSMART programs work with the project team to modify their inhouse data, and then execute available programs. Currently existing programs include analyses of racial disproportionality (while considering economic and other factors) and recurrence (configurable for timeframe and type). Utility programs allowing states to import census geographic data and attach those data to their in-state data are also available. More utility programs are in process, including programming allowing states to attach Social Vulnerability Index ratings based on zipcode or county. There is also a predictive risk modeling program in progress.

DataSMART will begin working with states in early February, 2023, and interested states should contact Brett Drake at brettd@wustl.edu

Site Principal Investigators 

Paul Lanier, PhD

Member of the Scientific Learning Collaborative

Associate Professor at University of North Carolina at Chapel Hill

Emily Putnam-Hornstein, PhD

Member of the Scientific Learning Collaborative

John A. Tate Distinguished Professor for Children in Need and Director of Policy at the University of North Carolina at Chapel Hill

Co-Director Children’s Data Network at the University of Southern California

Jared Parrish, PhD

Member of the Scientific Learning Collaborative

Senior Epidemiologist at the Alaska Department of Health and Social Services

Terry Shaw, PhD

Member of the Scientific Learning Collaborative

Associate Professor at the University of Maryland, School of Social Work

Research Division Director at the Institute for Innovation and Implementation

In the past 10 years, the study of child maltreatment has been revolutionized by the availability of large datasets and improvements in computer technology. These advances have created a new opportunity for researchers and public organizations to join together and improve services for children and families. The DataSMART project will establish a ‘Common Data Structure,’ which can be adopted by participating states, along with a library of cutting edge policy-relevant analysis programs. This will allow any state to use ‘off the shelf’ analytic products to support a truly evidence-based policy approach.

Brett Drake


The Identification of Newborns at High Risk for the Occurrence of Preventable Child Maltreatment Project (SURROUND)

This project, led by Mini Tandon at the WashU School of Medicine, will study and compare the performance of newborn screening for identifying the risk of child maltreatment. This RCT will use record data, birth records, and clinical assessments to improve the targeting of preventive services.

The study will implement long-term support strategies to prevent child abuse, initiated within the health system during the first days of a baby’s life.

John Constantino

Pilot Projects


Permanency and Health Utilization Outcomes for Foster Youth Served in Medical Homes

This project will cross reference health records from two medical homes with state foster care data to assess the prevalence of health needs, ongoing care patterns, and permanency outcomes. This program will be led by Timothy Kutz at the SLU School of Medicine and Katie Plax at the WashU School of Medicine.


A New Administrative Data Linkage Strategy to Investigate CPS Involvement and Birth Trajectories among Substance Affected Mother-Infant Dyads

The objective of this project, led by Emily Putnam-Hornstein and Julia Reddy, is to generate new knowledge about CPS involvement and birth trajectories using five years of linked administrative data. This research will serve as an exploratory analysis and data linkage that can be drawn upon from future studies, projects, and publications.


Assessing the Utility of a Risk- Stratification Model to Increase Equitable Service Connection

In this project led by Claire McNellen and Emily Putnam-Hornstein, researchers will utilize a risk-stratification model to examine service patterns within risk categories to assess differences by racial/ethnic and gender subpopulations. The study also aims to assess differences in community referrals between children and families to better work with agency partners in addressing unmet needs and rectifying inequities in these services.


Advancing the Science on Child Maltreatment and Adult Labor Market Outcomes

Derek Brown aims to conduct a new publishable study on the impacts of child maltreatment and the adult labor market using previously published data. In assessing the state of current literature, this project intends to illuminate the societal burden of child maltreatment and its correlating impacts on the labor market.