Faculty
Joseph Doyle is the Erwin H. Schell Professor of Management and Applied Economics at the MIT Sloan School of Management.
He studies public economics in the areas of healthcare and child welfare. His healthcare research investigates sources of value and waste to inform policies aimed at improving the quality and cost-effectiveness of the US healthcare system. This includes partnering with large healthcare providers and payers to conduct randomized controlled trials of changes in the ways healthcare is delivered with an emphasis on addressing social determinants of health. He conducts similar investigations into foster care and juvenile justice programs.
Doyle is codirector of the MIT Sloan Initiative for Health Systems Innovation and cochair of the Health Sector of the Jameel Poverty Action Lab.
He holds a BS from Cornell University and a PhD in economics from the University of Chicago.
Doyle, Joseph J. and Anna Aizer. Annual Review of Economics Vol. 10, (2018): 87-108. Download paper.
Doyle, Joseph J., John A. Graves, and Jonathan Gruber. Review of Economics and Statistics Vol. 101, No. 5 (2019): 841-852. Download Paper. Appendix. Press. Working Paper Version.
Finkelstein, Amy, Annetta Zhou, Sarah Taubman, and Joseph J. Doyle. New England Journal of Medicine No. 381 (2020): 151-162.
Breining, Sanni, Joseph J. Doyle, David N. Figlio, Krzysztof Karbowkik, and Jeffrey Roth. Journal of Labor Economics Vol. 38, No. 1 (2020): 95-142. Download Paper. Press.
Doyle, Joseph J., Working Paper. 2019.
Doyle, Joseph J., Sarah Abraham, Laura Feeney, Sarah Reimer, and Amy Finkelstein. PLOS ONE Vol. 14, No. 3 (2019): 1-13.
The study is the first randomized evaluation of the impact of Clinical Decision Support
An economic analytics of health care experiments could save money.
Source: Project Syndicate (Opinion Piece)
"Economists have developed an emerging body of evidence that...may also help to improve delivery and increase uptake of COVID-19 vaccines.”
Source: The New York Times Magazine
“Sometimes if you need answers, you go with natural experiments that aren't potentially as super clean, but we can learn from them.”
Source: Health Data Management (Opinion Piece)
