Using Electronic Health Records to Monitor and Improve Adherence to Medication

Adherence to medication is a serious problem in the United States leading to complications and preventable hospitalizations, particularly for patients with chronic diseases. Interventions have been proposed as a means to improve adherence to medication, but the optimal time to perform an intervention has not been well studied. Electronic health records (EHRs) can be used to monitor patient adherence to medication, providing a source of information to help decide when to perform an intervention. We propose a Markov decision process (MDP) model to determine when to perform adherence-improving interventions based on a patient’s EHR. We consider the tradeoff between the patient’s perspective of maximizing (quality-adjusted) time to first adverse health event and the payer’s perspective of minimizing the cost of interventions, medication, and adverse events. We use our model to evaluate the costs and benefits of implementing an EHR-based active surveillance system for adherence-improving interventions in the context of cardiovascular disease management. We also provide some theoretical insights into the structure of the optimal intervention policy and the influence of health risks and costs on intervention decisions.