The U.S. Department of Labor is collaborating with Mathematica and ideas42 to apply behavioral science principles to selected programs. Studies suggest that relatively modest changes to program materials, forms, or procedures can generate substantial improvements in program outcomes and performance.
Our predictive models provide real-time, actionable information to optimize program performance. These models can be deployed in operational workflow systems to allocate staff resources to tasks with the highest priority or potential gain. We continually evaluate model results and incorporate insights into the design process to improve and optimize the models and identify new areas of investigation.
Behavioral Interventions for Labor-Related Programs
Rapid-Cycle Tech Evaluations Accelerate Decisionmaking
This project involves developing, field testing, and disseminating easy-to-use evaluation resources, via a web-based, interactive toolkit, to expedite low-cost, quick-turnaround evaluations using rapid-cycle evaluation approaches.
Measuring Program Access, Trends, and Impacts for Nutrition Assistance Programs
Mathematica provided quick response analyses, preparing the 2013 Supplemental Nutrition Assistance Program Quality Control (SNAP QC) data file and QC Minimodel, and producing reports on the characteristics of SNAP households and national and state SNAP participation rates.
Supporting Quality and Efficiency in Medicare With Value-Based Payment Modification and Physician Feedback Reports
To support the Centers for Medicare & Medicaid Services Physician Value program, we provided technical support in the development and implementation of a value-based payment modifier, conducting research analyses, supporting performance measure development, and responding to inquiries from recipients...