Tailored Financial Incentives to Fight Medical Non-Persistence in Therapeutic Treatment: A Behavioral Economic Engineering Approach

Wednesday, June 15, 2016: 10:15 AM
401 (Fisher-Bennett Hall)

Author(s): Behnud Mir Djawadi; René Fahr; Florian Turk

Discussant: Emmanuel F Drabo

Objectives:  The development and design of financial incentive schemes as a sustainable and cost-effective intervention strategy to foster effectiveness of medical interventions remains a significant challenge in health care delivery.

Methods:  Based on the findings of the conceptual model of medical non-persistence we test three different financial incentive schemes. These incentives are derived upon concepts of behavioral economics, in particular mental accounting, prospect theory and choice bracketing, and incorporated into deposit, copayment and bonus schemes. We conduct randomized laboratory experiments to evaluate the performance and effectiveness of each incentive scheme on persistence behavior under controlled conditions. Participants in the experiment are students remunerated according to their performance in the experiment.



Results:  We find that financial incentive schemes based on the principles of prospect theory significantly improve treatment persistence compared to the situation where there are no incentives at all. This finding implies that the simple but smart re-allocation of co-payments and co-payment support between the treatment initiation phase and treatment maintenance phase represents an effective way of promoting persistence behavior.

Conclusions:   This study delivers first applications of behavioral interventions based on theoretical foundation. Using the method of experimental economics the study serves as a first proof of concept of a scalable way to design, calibrate and test the effectiveness of financial incentives on behavioral change. This approach is inevitable for broad application in real world as it minimizes the need for patient research while clarifying the impact of interventions under controlled conditions before these interventions get implemented in the field.