Mitigating Nonattendance Using Clinic-Resourced Incentives Can Be Mutually Beneficial: A Contingency Management-Inspired Partially Observable Markov Decision Process Model.

ABSTRACT

OBJECTIVES: Nonattendance of appointments in outpatient clinics results in many adverse effects including inefficient use of valuable resources, wasted capacity, increased delays, and gaps in patient care. This research presents a modeling framework for designing positive incentives aimed at decreasing patient nonattendance. METHODS: We develop a partially observable Markov decision process (POMDP) model to identify optimal adaptive reinforcement schedules with which financial incentives are disbursed. The POMDP model is conceptually motivated based on contingency management evidence and practices. We compare the expected net profit and trade-offs for a clinic using data from the literature for a base case and the optimal positive incentive design resulting from the POMDP model. To accommodate a less technical audience, we summarize guidelines for reinforcement schedules from a simplified Markov decision process model. RESULTS: The results of the POMDP model show that a clinic can increase its net profit per recurrent patient while simultaneously increasing patient attendance. An increase in net profit of 6.10% was observed compared with a policy with no positive incentive implemented. Underlying this net profit increase is a favorable trade-off for a clinic in investing in a targeted contingency management-based positive incentive structure and an increase in patient attendance rates. CONCLUSIONS: Through a strategic positive incentive design, the POMDP model results show that principles from contingency management can support decreasing nonattendance rates and improving outpatient clinic efficiency of its appointment capacity, and improved clinic efficiency can offset the costs of contingency management.