Active Research

Last Update: August 2023
Working Paper:  SSRN Link
Award: Decision Science Institute, Doctoral Showcase "Best Paper" (runner-up)

Methods:  Our empirical analysis combines observations from healthcare clinics across several US states, anonymized cellphone mobility data, COVID-19 severity measures, and stay-at-home orders. A Lasso-based procedure selects instruments and generates county-level measures of individual mobility, and a random forest forecast validates the insights of our descriptive approach for traffic prediction.
Conclusion: Combining observations from multiple sources allows us to evaluate how traffic to healthcare clinics changed with willingness to travel, stay-at-home orders, and other signals of environmental safety. During our study period, though patients exercised discretion in some negative ways (e.g., foregoing care), patients also shouldered some of the burden of their own wellness. In studying patient discretion, we characterize powerful predictors of healthcare traffic, we suggest how our findings might generalize post-COVID, and we encourage researchers to continue exploring the role of patient discretion in the co-production of wellness.