My research is driven by a strong commitment to health equity and focuses on access to care in Medicaid, particularly as affected by Medicaid policies and the growing importance of managed care. I conduct theoretically and conceptually informed empirical research via a range of quantitative methods, as well as methodological work that addresses the quality of administrative health care data.
Health care access is at the core of my research program. My prior work addresses the impact of the Medicaid expansion under the Affordable Care Act (ACA). I am particularly interested in the emergency department (ED) as the safety net for Medicaid enrollees. In one working paper, I test the widely shared – but possibly outdated – assumption that EDs are used as a substitute for unavailable primary care. I show that for Medicaid enrollees with primary care treatable conditions, ED visits and primary care are not always substitutes. I plan to further investigate complementarity between primary care and ED care. In another working paper, I demonstrate that while there is some heterogeneity in effects of the expansion on ED use immediately after the expansion (discrete changes), increases in the trend of ED use are consistent across considered states, and that increases are mainly driven by men and younger adult populations.
In addition to conducting empirical research to examine health care access in the changing health policy landscapte, I strive to develop a better conceptual understanding of how people access and use care. My collaborator and mentor Peter Veazie at the University of Rochester and I developed a new conceptual model of health services use. In contrast to the widely used Andersen’s model, our model allows us to empirically differentiate between three roles – motivation potential, sensitivity to need, and sensitivity to access – that an individual characteristic (e.g. age or size of social network) can play in determining one’s use of health care. This conceptually and methodologically innovative work can be used to better understand health care use and inform design of complex interventions and innovative health care delivery systems.
Since health policy research often relies on administrative health care data, I find it important to address the quality of these data. I have published on investigating opioid diagnosis coding in hospitalization data and on correcting opioid overdose death counts in the CDC's all-cause mortality data. In collaboration with Laura Hatfield at Harvard Medical School, I am currently working on methods to address silent missingness in T-MSIS analytic files (TAF) encounter data.
Please feel free to contact me to chat about my work and/or potential collaborations.