To help researchers and policymakers identify the best approaches to addressing the concussion epidemic in youth athletics, Mathematica conducted a pilot project to explore the experiences of stakeholders at two high schools that outfitted athletes with head impact sensors.
- Data science and statistics
- Visual analytic production systems
- Data ethnography and life-cycle development
- Research design
- Mixed-methods program evaluation
- Sensor-based data collection
- Health Information Technology and Analytics
- Population Health
- State Health Policy
Andrew Hurwitz has expertise in data analytics, data ethnography, data life-cycle development, research design, mixed-methods program evaluation, sensor-based data collection, and business development.
Hurwitz is currently directing the development of a visual analytics tool to help industries make data-driven decisions about employee workforce readiness as they prepare to return to work. Originally designed for a hospital system, the tool visualizes key data related to COVID-19 symptomology, access to personal protective equipment, and access to ventilators and their components. Previously, Hurwitz directed a project that developed a visual analytics production system that used advanced geospatial technology to visualize commercial claims data in the state of New York. The system allowed stakeholders to conduct analyses by school district, county, and athletic section. He also serves as a deputy director in Mathematica’s Health Analytic Systems and Technology group, focusing on Mathematica’s emerging digital services area, which provides innovative technology and analytic solutions to commercial, state, and foundation clients. Hurwitz provides thought leadership to Mathematica’s data science offering, helping shape how emerging methods in data science will converge with classical evaluation methods. Hurwitz also participates in Health Unit business development, recruiting, and staff development. Among his other projects, Hurwitz served as deputy project director for a Centers for Disease Control and Prevention–funded study that used a randomized trial design to evaluate the effectiveness of an alternative tackling style in youth football. The study used innovative mouthguard sensor technology as its primary outcome measure, detecting the cumulative number of head impacts and their associated linear and rotational acceleration forces. The study involved 36 youth football teams with athletes ranging in age from 6 to 14. A second component of the study used the same mouthguard sensor technology to quantify the impacts received by youth flag football players.
Before joining Mathematica in 2011, Hurwitz held a research position with Rutgers University’s Robert Wood Johnson Medical School. Hurwitz holds a Ph.D. in evaluation, measurement, and statistics from the University of Delaware. His dissertation used experimental design techniques to investigate whether congressional staffers’ endorsements of public programs and policies differ when results from an impact evaluation are presented under frequentist versus Bayesian paradigms.
Examining the Use of Head Impact Sensors in School Sports
Understanding the Risks of Tackling in Youth Football
Using innovative mouth guard sensor technology, Mathematica is conducting a rigorous evaluation over 27 months to measure head impacts in more than 40 youth football teams.