Reducing Cardiovascular Risk in Adults With Serious Mental Illness Using an Electronic Medical Record-based Clinical Decision Support

After entry of blood pressure data at all primary care visits, relevant electronic health record data were automatically extracted, encrypted and processed through Web-based clinical algorithms that determined if the patient met intervention eligibility criteria. In intervention clinics, the rooming staff received a best practice alert and printed patient and primary care provider versions of the clinical decision support that identified evidence-based treatment options for any uncontrolled cardiovascular risk factors and prioritized treatment recommendations based on potential cardiovascular risk reduction. Cardiovascular risk factors addressed in study participants were control of lipids, blood pressure, weight, tobacco, glucose and appropriate aspirin use. In control clinics, rooming staff did not receive a best practice alert and patients and primary care providers did not receive and were not able to access the clinical decision support.