Exploration and Incentivizing Participation in Clinical Trials

Participation incentives a well-known issue inhibiting clinical trials. We frame this issue as a non-standard exploration-exploitation tradeoff: the trial would like to explore as uniformly as possible, whereas each patient prefers "exploitation", i.e., treatments that seem best. We incentivize participation by leveraging information asymmetry between the trial and the patients. We measure statistical performance via worst-case estimation error under adversarially generated outcomes, a standard objective for clinical trials. We obtain a near-optimal solution in terms of this objective: an incentive-compatible mechanism with a particular guarantee, and a nearly matching impossibility result for any incentive-compatible mechanism. Our results extend to heterogeneous agents.