Mathematica conducted a 10-year evaluation of the Ticket to Work (TTW) program, a major initiative of the Social Security Administration to increase disability beneficiaries' employment and reduce their dependence on benefits.
- Health care financing and insurance
- Medicaid and Medicare
- Program evaluation
- Data analytics and measure development
- Data Analytics
- Care Delivery Systems
- Employment and Income Support
- State Health Policy
Su Liu focuses on access, cost and quality issues for programs serving vulnerable populations, such as low-income individuals, the elderly, persons with disabilities, and the uninsured in the United States.
Liu plays key roles in federally and state-funded research projects, including analysis of the Medicare Advantage stabilization fund, studies of transition events in health insurance coverage, and technical assistance for states' coverage expansion initiatives. She has contributed to the development of quantitative measures of participation in state Medicaid buy-in programs, refining techniques to integrate administrative data from multiple agencies to track employment and health expenditures for adults with disabilities. For Mathematica’s large-scale evaluation of the Ticket to Work (TTW) program, she monitored implementation and effectiveness of initiatives authorized by TTW and the Work Incentives Improvement Act.
Prior to Liu’s tenure at Mathematica from 2003 to 2010, she held positions at the University of California, AARP, and the International Institute of Applied System Analysis in Austria. Before rejoining Mathematica in 2015, she was also a faculty member at the School of Public Health and Primary Care at the Chinese University of Hong Kong and a visiting scholar at the University of Oxford’s Health Economics Research Centre. She has a Ph.D. in economics from the University of California, Irvine.
Evaluation of the Ticket to Work Program
Providing Business Analytics and Data Quality Development for Medicaid and CHIP Business Information Solutions (MACBIS)
This initiative is building an infrastructure for robust data analytics, and integrating and aligning federal and state data sources, to support data-driven policy decisions about Medicaid and CHIP policy and programs.
New Approaches for Medicaid: The 1115 Demonstration Evaluation
Mathematica's evaluation of Medicaid Section 1115 waiver demonstrations, approximately 40 in number, seeks to assess the implementation and outcomes of four different types of innovations and help CMCS shift toward data-driven decision making for future waiver approvals.
Medicaid Buy-In Program
The Medicaid Buy-In program allows adults with disabilities to earn more than would otherwise be possible and still have Medicaid coverage. In return, participants “buy into” the Medicaid program, typically by paying premiums based on income. To assist CMS in monitoring the program, Mathematica has developed...