Background: Heart failure is common and associated with considerable morbidity and cost, yet physician adherence to treatment guidelines is suboptimal. We conducted a randomized controlled study to determine if adding symptom information to evidence-based, computer-generated care suggestions would affect treatment decisions among primary care physicians caring for outpatients with heart failure at two Veterans Affairs medical centers.
Methods: Physicians were randomly assigned to receive either care suggestions generated with electronic medical record data and symptom data obtained from questionnaires mailed to patients within 2 weeks of scheduled outpatient visits (intervention group) or suggestions generated with electronic medical record data alone (control group). Patients had to have a diagnosis of heart failure and objective evidence of left ventricular systolic dysfunction. We assessed physician adherence to heart failure guidelines, as well as patients' New York Heart Association (NYHA) class, quality of life, satisfaction with care, hospitalizations, and outpatient visits, at 6 and 12 months after enrollment.
Results: Patients in the intervention (n = 355) and control (n = 365) groups were similar at baseline. At 12 months, there were no significant differences in adherence to care suggestions between physicians in the intervention and control groups (33% vs. 30%, P = 0.4). There were also no significant changes in NYHA class (P = 0.1) and quality-of-life measures (P >0.1), as well as no differences in the number of outpatient visits between intervention and control patients (6.7 vs. 7.1 visits, P = 0.48). Intervention patients were more satisfied with their physicians (P = 0.02) and primary care visit (P = 0.02), but had more all-cause hospitalizations at 6 months (1.5 vs. 0.7 hospitalizations, P = 0.0002) and 12 months (2.3 vs. 1.7 hospitalizations, P = 0.05).
Conclusion: Adding symptom information to computer-generated care suggestions for patients with heart failure did not affect physician treatment decisions or improve patient outcomes.