Among CVRM patients , the results tended towards a beneficial effect of CDSS , but only LDL-c target attainment in diabetes patients reached statistical significance .
Prompting , integration into the electronical health record , patient empowerment , and medication support were related to more effective CVRM .
Conclusion We did not find a clear clinical benefit from CDSS in cardiovascular risk factor levels and target attainment .
Some features of CDSS seem more promising than others .
Clinical relevance of CDSS in CVRM might additionally be sought in the improvement of shared decision making and patient empowerment
Background Cardiovascular risk management ( CVRM ) is notoriously difficult because of multi-morbidity and the different phenotypes and severities of cardiovascular disease .
Computerized decision support systems ( CDSS ) enable the clinician to integrate the latest scientific evidence and patient information into tailored strategies .
The effect on cardiovascular risk factor management is yet to be confirmed .
Randomized controlled trial of an informatics-based intervention to increase statin prescription for secondary prevention of coronary disease
OBJECTIVE : Suboptimal treatment of hyperlipidemia in patients with coronary artery disease ( CAD ) is well documented . We report the impact of a computer-assisted physician-directed intervention to improve secondary prevention of hyperlipidemia . DESIGN AND SETTING : Two hundred thirty-five patients under the care of 14 primary care physicians in an academically affiliated practice with an electronic health record were enrolled in this proof-of-concept physician-blinded r and omized , controlled trial . Each patient with CAD or risk equivalent above National Cholesterol Education Program-recommended low-density lipoprotein ( LDL ) treatment goal for greater than 6 months was r and omized , stratified by physician and baseline LDL . Physicians received a single e-mail per intervention patient . E-mails were visit independent , provided decision support , and facilitated “ one-click ” order writing . MEASUREMENTS : The primary outcomes were changes in hyperlipidemia prescriptions , time to prescription change , and changes in LDL levels . The time spent using the system was assessed among intervention patients . RESULTS : A greater proportion of intervention patients had prescription changes at 1 month ( 15.3 % vs 2 % , P=.001 ) and 1 year ( 24.6 % vs 17.1 % , P=.14 ) . The median interval to first medication adjustment occurred earlier among intervention patients ( 0 vs 7.1 months , P=.005 ) . Among patients with baseline LDLs > 130 mg/dL , the first postintervention LDLs were substantially lower in the intervention group ( 119.0 vs 138.0 mg/dL , P=.04 ) . Physician processing time was under 60 seconds per e-mail . CONCLUSION : A visit-independent disease management tool result ed in significant improvement in secondary prevention of hyperlipidemia at 1-month postintervention and showed a trend toward improvement at 1 year
Among CVRM patients , the results tended towards a beneficial effect of CDSS , but only LDL-c target attainment in diabetes patients reached statistical significance .
Prompting , integration into the electronical health record , patient empowerment , and medication support were related to more effective CVRM .
Conclusion We did not find a clear clinical benefit from CDSS in cardiovascular risk factor levels and target attainment .
Some features of CDSS seem more promising than others .
Clinical relevance of CDSS in CVRM might additionally be sought in the improvement of shared decision making and patient empowerment
Background Cardiovascular risk management ( CVRM ) is notoriously difficult because of multi-morbidity and the different phenotypes and severities of cardiovascular disease .
Computerized decision support systems ( CDSS ) enable the clinician to integrate the latest scientific evidence and patient information into tailored strategies .
The effect on cardiovascular risk factor management is yet to be confirmed .