An Analysis of Incentive Schemes for Participant Retention in Clinical Studies

Participant retention is one of the significant issues faced by clinical studies. This paper analyzes the economic impact of combining two mechanisms (monetary payments to participants and effort exerted during a clinical study) observed in practice to improve retention. Various factors, such as expected health benefits, logistics expenses, and inconvenience during the study, impact retention rate. However, the determination of monetary payments is ad-hoc in practice. Further, an economic analysis of the two mechanisms for improving retention in clinical studies is absent. Given an incentive scheme, under full information and information asymmetry regarding participants’ characteristics, we model the problem of identifying optimal payment and effort to improve retention for a clinical study using a non-linear integer program. We propose polynomial-time algorithms to solve the problem under full information for a participant-specific linear payment scheme and two commonly observed incentive schemes: Fixed Payment (FP) and Logistics Reimbursement (RE). We also provide exact methods to solve the problem under information asymmetry for the FP and RE schemes. We conduct a comprehensive computational study to gain insights into the relative performance of these schemes. Under full information, the participant-specific scheme can reduce the retention cost by about 47% on average compared to that under the RE and FP schemes. Information asymmetry causes the RE scheme to be more favorable than the FP scheme in a wider variety of clinical studies. Further, the value of acquiring participants’ characteristics information is significant under the FP scheme compared to that under the RE scheme. Given the participant population and study characteristics under full information and information asymmetry, our analysis enables a clinical study to identify an optimum incentive scheme, monetary payment, and effort level, for improving retention. Further, our analysis also allows clinical studies to assess budget requirements to improve retention and adapt the incentive payments to IRB guidelines if any