Background for readers: I was interested in an Economics PhD for two main reasons: first, the personal learning and growth potential, specifically in terms of asking sharp questions and answering them rigorously is particularly appealing to me. I do this work to some extent at CMS, and the exposure to it (along with learning from the framework of some of my exceptional colleagues) has me craving more. Second, the dedicated research time and opportunity at this point in my life and career is really exciting. I am deeply looking forward to having time carved out just to learn in this way.
I am putting this here for my own sake and also in case it is helpful to anyone thinking about writing their personal statements as they apply to doctoral programs.
The intersection of economics and public health has been a consistent thread throughout my academic and professional career. At a high level, my primary motivations for pursuing a PhD in Economics are twofold: I want to learn how to ask incisive questions and gain the technical expertise to effectively research, evaluate and answer those questions.
As a nontraditional Economics PhD candidate, my professional experience in different roles across industry positions me well to thrive in a rigorous program. At the Centers for Medicare & Medicaid Services (CMS), my current role as a data scientist includes analyzing big data to evaluate programs, creating data visualizations, and presenting the outcomes to various audiences. I have also led the human-centered design of a new internal data system, bridging the gap between the technical and clinical staff. This experience combined with graduate training in statistics and health economics has given me a strong foundation in quantitative analysis and economic modeling.
Before CMS, I worked in innovation at Wellstar, a large nonprofit hospital system in Atlanta, where I evaluated the potential impact of different technology on the patients, providers, and the system as a whole. From supply chain to sustainability to the future of work, the key to the evaluation was modeling out the long-run effects. One example of a sustainability project involved modeling the financial and operational impact of integrating a containerized “vertical farming” system into the Wellstar food supply chain- work that was successfully executed thanks to analysis proving out ROI within two years.
Beyond professional roles, I work pro bono with the Georgia Justice Project (GJP), a local restorative justice nonprofit. My work there has been varied, conducting broad scope analyses of the impact of incarceration on public health outcomes as well as a specific economic impact study of legislation that GJP has helped to pass. In 2023, I was honored to receive a pro bono spotlight from GJP in recognition of my work.
I have a consistent track record of conducting high-impact analysis, both within my work and on my own time. Even through multiple publications and successful professional projects, the output I am proudest of is a 2020 history and analysis of policing in America. That piece combined data from a variety of sources- expenditure and employment data from the US Bureau of Justice Statistics, Census Bureau and World Bank data, and policing data from other federal governments.
Some high-level examples of meaningful work in my professional career include: from graduate school, my first-author paper on systematic review methodology has been cited 399 times, including as recently as November 2024. In Cameroon, I conducted the first epidemiological study of pediatric cancer in the Northwest Region, traveling to the three major hospitals to ingest handwritten medical records as data for an IRB-approved study. During the pandemic, I led the supply chain work to ship 40’ high-cube containers full of personal protective equipment first from the US to China in early 2020 and then back into the US later that summer while navigating the complicated regulatory and tariff environment. At Wellstar, I led the IRB-approved design and installation of using immersive sound as therapy to reduce stress and improve the patient experience for birthing mothers.
However, the work that has been most valuable to me is in my current position as the lead data scientist on the Tribal Health Quality Improvement team within the Quality Improvement and Innovation Group at CMS. My work primarily involves program evaluation, both for public health outcomes and also for economic impact around ROI and costs avoided, to help ensure that high-quality care is being delivered. On the Pine Ridge Indian Reservation in southwestern South Dakota, the life expectancy for men and women is 47 and 52 years, respectively. I feel tremendously honored to be able to work with our partners, both federally and on the ground, to improve outcomes for tribal populations across the country.
Within the scope of applied microeconomics, I am specifically interested in exploring the various effects of access, labor, and equity on healthcare outcomes. Health equity can be defined in a variety of ways; often, it is taken to mean the standard social determinants of health (SDoH) including gender, race, and socioeconomic status. I prefer an expansive view of health equity that often includes SDoH as an underlying variable. I am interested in answering questions like “how does commute modality impact public health outcomes at a population level? Does that vary by geography?” and "why does the incarcerated population in both local jails and state prisons have better mortality rates than the overall US population?”
Public health goes far beyond the large institutions like CMS and CDC —- everything from road design to education access to restorative justice programs are material to the work in this space.
From a more granular perspective, I am particularly interested in the nexus of access, labor, and equity for underserved populations within the umbrella of health economics. For instance, I would love to conduct an analysis on how organized healthcare labor impacts patient outcomes when compared to facilities with non-union staff. To control for heterogeneity of data and for potential confounds including hospital size, demographics of the population served, staff education levels, nurse-to-patient ratios, and more, a fixed effects model might be most appropriate here. This analysis could combine data from a variety of sources, including outcomes from CMS, workforce characteristics from the Bureau of Labor Statistics, facility demographics from the American Hospital Association, and more.
Another broad area for potential analysis is the impact of technology on healthcare access and outcomes, especially outside the four walls of the hospital. The combination of the COVID pandemic along with the generative AI boom has seen a proliferation of healthcare at home capabilities, from remote patient monitoring to telehealth and beyond. As more of these tools receive FDA approval and become available to American patients, there are a variety of first- and second-order effects to examine.
People often interpret improving access for patients as impacting rural areas with either closed or inaccessible hospitals and little to no care in between, but they can also serve medical deserts in urban areas across the country.
My position as a data scientist at CMS gives me a unique perspective on both sourcing this data and evaluating effects. Examining the economic value of the public health impact of these tools and interventions for patients, from New York City to Navajo Nation, can help stakeholders across the spectrum - from policymakers deciding what research and programs to fund to providers on the ground choosing the best care coordination to the individual patients themselves looking to live healthier lives.
My primary motivations behind pursuing a PhD in Economics are having the dedicated time and space to conduct this manner of analysis from data across a variety of sources along with sharpening the analytical and technical skills to ensure that the research is conducted rigorously and accurately. These experiences have only reinforced my commitment to using data and economics to drive social change.
I believe in a future vision of this country where healthcare is a right- where people from any background no longer have to worry deeply about simply accessing and paying for healthcare and can focus on getting and staying healthy, whatever that means to them. I am interested in pursuing an Economics PhD with the objective of asking the right questions and getting rigorous answers to better understand how to work towards fixing American healthcare.
Whether as faculty or in industry, I envision using my career as a platform for connecting the dots between applied microeconomics research and real-world public health impact, empowering patients, providers, and policymakers with the background to build healthier communities.
Empathy for the people I work with and serve is at the core of what I do and would be integral to my approach to a PhD in economics. While I bring a proficiency in statistics, data management, and communication, my greatest strength exists in the connections to people on an interpersonal level. I believe deeply in the power of community and the unbelievable ceiling that collective action has.
When I think about the direction I want my career to take, that sense of fostering community and building relationships is so fundamental to who I am that it would be impossible to leave behind. Whether that is working in academia and building bridges to potential research partners and institutions to enable better, more robust economics work or it is in industry working to make decisions and drive the direction of an organization, that empathy-based, community-driven approach will be part of me wherever I go and whatever I do.
