Professor Long Gao Associate Professor of Operations and Supply Chain Mgt
"Optimal Payment for Dynamic Treatment Regimes"
Abstract: Dynamic treatment regimes improve health outcomes by tailoring each treatment to a patient's evolving condition, but they also allow providers to learn and game the system over time. How should insurers pay? We study this new class of reimbursement problems, where the provider can privately learn and manipulate the progression of the patient's condition. (i) We characterize the optimal payment policy: it rewards provider honesty with incentive pay and elicits future private information with recursive deferred payment; it internalizes two intertemporal externalities of each treatment; moreover, it admits a simple implementation of risk-adjusted cost-sharing policy. (ii) We show that, ignoring dynamic learning and gaming, the existing payment models may have overestimated the harm of information asymmetry. Using the optimal policy, insurers only need to pay for initial private information; they can exploit provider uncertainty and elicit future private information at no cost. (iii) Our study informs U.S. healthcare payment reform with actionable insights: using two sets of real data, our study also quantifies when and why the optimal policy outperforms the existing ones. By highlighting the critical role of dynamic learning and gaming, this study advances our understanding of healthcare payment theory and practice.
Joint work with Wei Zhang, Frank Chen, and Xinyue Fei.
Bio: Long Gao is an associate professor in UC Riverside. He earned his Ph.D. from Penn State, B.E and M.E. from Tsinghua. His research focuses on the role of dynamic information and incentives in operations management. The central question is what management can achieve, when the information necessary for decision making is dispersed, privately held, and evolving over time. His research is driven by business practices in services, transportation, supply chain, inventory control, salesforce, and healthcare. He has published in journals such as MS, MSOM, and POMS.
Details:
Type: In Person and on Zoom
Time: Friday April 12,2024 from 1:00 to 2:30 PM
Location: Room 2120
Zoom: https://ivey-uwo.zoom.us/j/94250017291?pwd=YXA5djFmeGFLakZCdThBblBmOEJSQT09
Meeting ID: 942 5001 7291
Passcode: 294515
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