H. Gilutz, L. Novack, P. Shvartzman, J. Zelingher, D.Y. Bonneh, Y. Henkin, M. Maislos, R. Peleg, Z. Liss, G. Rabinowitz, D. Vardy, D. Zahger, R. Ilia,
N. Leibermann and A. Porath
Background: Dyslipidemia remains underdiagnosed and undertreated in patients with coronary artery disease. The Computer-based Clinical Decision Support System provides an opportunity to close these gaps.
Objectives: To study the impact of computerized intervention on secondary prevention of CAD.
Methods: The CDSS was programmed to automatically detect patients with CAD and to evaluate the availability of an updated lipoprotein profile and treatment with lipid-lowering drugs. The program produced automatic computer-generated monitoring and treatment recommendations. Adjusted primary clinics were randomly assigned to intervention (n=56) or standard care arms (n=56). Reminders were mailed to the primary medical teams in the intervention arm every 4 months updating them with current lipid levels and recommendations for further treatment. Compliance and lipid levels were monitored. The study group comprised all patients with CAD who were alive at least 3 months after hospitalization.
Results: Follow-up was available for 7448 patients with CAD (median 19.8 months, range 6–36 months). Overall, 51.7% of patients were adequately screened, and 55.7% of patients were compliant with treatment recommended to lower lipid level. A significant decrease in low density lipoprotein levels was observed in both arms, but was more pronounced in the intervention arm: 121.9 ± 34.2 vs. 124.3 ± 34.6 mg/dl (P < 0.02). A significantly lower rate of cardiac rehospitalizations was documented in patients who were adequately treated with lipid-lowering drugs, 37% vs. 40.9% (P < 0.001).
Conclusions: This initial assessment of our data represent a real-world snapshot where physicians and CAD patients often do not adhere to clinical guidelines, presenting a major obstacle to implementing effective secondary prevention. Our automatic computerized reminders system substantially facilitates adherence to guidelines and supports wide-range implementation.