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.

翻译：参与激励是阻碍临床试验开展的常见问题。我们将此问题构建为一种非标准化的探索-利用权衡：试验方希望尽可能均匀地探索治疗方案，而每位患者更偏好“利用”即选择看似最优的治疗方案。我们通过利用试验方与患者之间的信息不对称来激励参与。在对抗性生成的结局假设下（这是临床试验的标准目标），我们以最坏情况下的估计误差衡量统计性能。我们获得了该目标下的近最优解：一个具有特定保证的激励相容机制，以及任何激励相容机制几乎无法超越的不可行性结果。我们的结论可扩展至异质性主体场景。