Risk adjustment models are traditionally derived from administrative claims. Prescription fill rates—extracted by comparing electronic health record prescriptions and pharmacy claims fills —represent a novel measure of medication adherence and may improve the performance of risk adjustment models. We evaluated the impact of prescription fill rates on claims-based risk adjustment models in predicting both concurrent and prospective costs and utilization.

Background: Risk adjustment models are traditionally derived from administrative claims. Prescription fill rates—extracted by comparing electronic health record prescriptions and pharmacy claims fills —represent a novel measure of medication adherence and may improve the performance of risk adjustment models.

Objective: We evaluated the impact of prescription fill rates on claims-based risk adjustment models in predicting both concurrent and prospective costs and utilization.

Methods: We conducted a retrospective cohort study of 43,097 primary care patients from HealthPartners network between 2011 and 2012. Diagnosis and/or pharmacy claims of 2011 were used to build 3 base models using the Johns Hopkins ACG system, in addition to demographics. Model performances were compared before and after adding 3 types of prescription fill rates: primary 0–7 days, primary 0–30 days, and overall. Overall fill rates utilized all ordered prescriptions from electronic health record while primary fill rates excluded refill orders.