C-B4-03: Promoting Adherence to Improve Effectiveness of Cardiovascular Disease Therapies (PATIENT): Implementing a Medication Adherence Intervention Using Health Information Technology

concordance between these scores when both measures could be computed. Results: We identified 122,270 eligible patients. Of these, 59.7% (n=73,023) had sufficient data to calculate the lab-based risk score and 88.1% (102,795) clinic-based risk score. Neither score could be calculated for 14.5% (n=17,732). The most common reason for not being able to calculate was missing data on cholesterol. Using the laboratory-based score only, we found 12.9% of the population were at high risk (risk >20%), 24.5% moderate risk (10-20%), and 62.6% low risk (<10%). For those with both risk scores (n=71,280), the lab-based risk score was lower than the clinic-based score for 84.3% of patients (60,060/71,280). The lab-based score was 3.1% lower on average, but the two risk scores were within ±5% for 77.0% of patients (54,874/71,280). The risk scores differed by more than 10% for only 8.7% of patients (n=6236), and in most cases (6098 of 6236), the clinic-based score was higher. Conclusion: Electronic data can be used to classify CVD risk for most adults age 30-74. Risk scores based on BMI tend to estimate risk as higher than scores based on laboratory data. However, the risk scores do not differ by more than 5% for most patients.