I am currently a Better Government Lab Pre-doctoral Research Fellow at Georgetown University’s McCourt School of Public Policy, where I work with Don Moynihan, Pamela Herd, and Sebastian Jilke conducting administrative burdens research with the U.S. Social Security Administration and the U.S. General Services Administration’s Office of Evaluation Sciences. I am also a PhD Candidate in Political Science and an NSF Graduate Research Fellow at the University of Iowa.
My research focuses on using innovative methodological techniques to understand political determinants of access to health care and social welfare resources in the U.S. Specifically, I am interested in the role of policy design, administrative burdens, and street level bureaucrats play in disconnects between what a policy’s goals are and how the program actually performs. One way of quantifying this potential disconnect is program eligibility to program enrollment, often called take-up. This is a particularly relevant measure for health and social policies, but also for other policy areas like election administration.
My dissertation looks at how states’ decisions regarding administrative burden in Medicaid affect take-up in that state, and how this relationship may be moderated by state and local policy contexts. I use multilevel regression, imputation, and post-stratification to calculate a novel, nationwide dataset of Medicaid take-up, and I also compile a novel database of state’s Medicaid administrative measure and state Medicaid program design features. I was recently awarded the American Political Science Association’s 2022 Paul Volcker Award Junior Scholar Award for Public Administration for this dissertation research.
My larger research agenda encompasses state and local politics, bureaucratic politics, public administration, social inequality, and policy diffusion. My co-authored work on state variation in access to affordable contraception has been featured by The Washington Post, The Economist, The Gender Policy Report and PBS News Hour. I also work with several research teams to study policy diffusion and 1) understand how and why certain types of policies spread the way they do and 2) better use network analysis methods to study dynamics of policy diffusion.
Prior to graduate school, I received my BA in Public Policy and U.S. and Global Health from the University of North Carolina at Chapel Hill, and I also have an MS in Health Informatics from the University of Iowa. I am passionate about using big data and data science tools to create research that can inform more equitable policymaking and policy implementation, and I am passionate about teaching the next generation of researchers and policymakers to do the same.
- 2022 Paul Volcker Junior Scholar Award, American Political Science Association (APSA)
- 2021 Tom Carsey Scholar, State Politics and Policy Section (APSA)
- National Science Foundation, Graduate Research Fellowship ($138,000)
- University of Iowa, Quantitative Training Scholarship ($4,000)
- University of Iowa, Iowa Recruitment Fellowship ($30,000)
- How County Context Affects Medicaid Enrollment. Public Management Research Meeting - DC Area. Panel Presentation. 2022
- What makes a Leader? A Role Analysis of Latent Diffusion Networks. (with Scott Lacombe) American Political Science Association Conference. Panel Presentation. 2022
- Inaccessible by Design? Medicaid and the Politics of Administrative Burden. State Politics and Policy Conference. Poster Presentation. 2022.
- Kreitzer, R., Smith, C.W. Saunders, T., & Kane, K. (forthcoming) Prevalent but Not Inevitable: Mapping Contraception Deserts across the American States. Contraception
- Kreitzer, R., Smith, C.W. Kane, K. & Saunders, T. (2022) Contraception Deserts: The Effects of Title X Rule Changes on Access to Reproductive Healthcare Resources. Politics and Gender
- Kreitzer, R., Smith, C.W. Kane, K. & Saunders, T. (2021) Affordable, but Inaccessible: Using the Two- Step Floating Catchment Area Method to Measure Policy Accessibility in the U.S. Journal of Health Politics, Policy, and Law [Selected News Coverage: Washington Post, PBS News Hour, the Economist. 2nd most downloaded paper in Journal of Health Politics, Policy and Law 2021.]
In my dissertation, I explore the interactive effects of state and local context, policy design, and administrative burden on policy take-up. Existing literature examines these individually, while I look at their combined effects. I demonstrate there is wide variation in how states design their Medicaid policies and the administrative burdens for enrolling. Since policy design and administrative burdens are not necessarily both dictated by state legislatures, they may not be as congruent as one would expect. If a state has a generous Medicaid policy (e.g. they offer more benefits than federally required and have expanded under the ACA), one may expect them to have relatively high take-up. However, if that generous policy is paired with high administrative burden, take-up may actually be low. On the flipside, there may be high take-up in a historically conservative state with restrictive policy design yet a simple application process and easily navigable and state Medicaid website. I argue state and local context can play a moderating role in the effect of policy design and administrative burden on take-up. The resources people and communities have to overcome burdens, the concentration of disadvantage, and the demand, or need, for these policy resources varies widely between and within states. I was recently awarded the Paul Volcker Junior Scholar Award for this research from the American Political Science Association.
In my first chapter, I demonstrate how Medicaid enrollment varies at the county-level and how concentrated disadvantage impedes enrollment using multilevel modelling. In counties with high proportions of people living below the federal poverty level, Medicaid enrollment is lower than in more mixed income counties. This negative effect is exacerbated (i.e. enrollment is even lower) in counties that are both poor and racially segregated. In my second chapter, I develop a method for measuring Medicaid take-up. Existing research on Medicaid take-up only looks at a snapshot in time, a single state, a small set of states, or a single eligibility group (e.g. pregnant women, childless adults, those over 65, etc.). I measure take-up monthly for all states and all eligible groups. I use multilevel regression, imputation, and post-stratification (MRP) to estimate how many people are likely eligible based on criteria that vary by state and by eligibility group. Then, I use those estimates and monthly administrative enrollment data to calculate take-up. In subsequent chapters, I develop measures of administrative burden and policy design for state Medicaid programs and use these measures to test the interactive effects of policy design, administrative burden, and state/local context on take-up. The first empirical chapter is completed, and I am nearly finished with data collection and fitting the MRP models for the remaining chapters.