I'm an applied health economist and an Assistant Professor at Tulane University. My research uses quasi-experimental methods and real world data ( such as claims, EMR, and clearing warehouse data ) to examine inefficiencies in the US healthcare sector.
My research has looked into the intended and unintended consequences of federal and state policies on healthcare utilizations and health, as an example, I have looked at:
How Medicare's FFS price decisions affect innovation in kidney dialysis.
How Hospital Readmission Penalties change the way hospitals care for patients.
This work extends to investigations into the marginal benefit of medical technologies and whether reimbursement schemes reflect the value from these technologies.. For example I have looked at:
the marginal health benefit from opioids, outpatient care, CT scans, and preterm prevention drugs . These investigations are used to inform how we should decide the price of such medical tools and who should get which treatment.
Prior to the pandemic, I tackled the largest public health crisis in the US (the opioid epidemic) and I have looked at:
My work on the opioid epidemic is summarized by Vox, Brookings Institute and the Cato Institute. My ongoing work on the opioid epidemic includes looking at racial disparities in maternal drug testing.
During the Covid-19 outbreak, I studied its impact. I looked at:
Part of executing this research involves finding appropriate real world data, suited for the question and context. I have a keen interest in novel uses of healthcare data. I have used Medicare claims, commercial claims, death data from obituaries, claims clearing warehouse data, electronic health records, genome linked EMR data and more. And so, I am naturally interested in data linkages and interoperability.
If you want to talk about research ideas or healthcare data your can email me at firstname.lastname@example.org.