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 .
Development and Validation of a Computer Application to Aid the Physician's Decision-Making Process at the Start of and during Treatment with Insulin in Type 2 Diabetes: A Randomized and Controlled Trial
Background : Achieving optimum blood glucose control in patients with type 2 diabetes mellitus ( T2DM ) is difficult . Some primary care physicians ( PCPs ) delay the start of insulin use because of the uncertainty in intensifying insulin therapy . The objective was to develop and vali date a computer application ( CA ) that helps PCPs to make decisions about insulin therapy in order to achieve a significant improvement in glycated hemoglobin ( HbA1c ) . Methods : This was a cluster-r and omized clinical trial . Fourteen primary care centers ( PCCs ) in Madrid with 66 PCPs and 697 T2DM patients on insulin therapy were r and omly divided into two groups of seven PCCs each . In the intervention group , seven PCCs included 39 PCPs and 365 T2DM patients on insulin therapy . These PCPs were free to use the CA . A further seven PCCs were assigned to the control group with 27 PCPs and 332 T2DM patients on insulin therapy . The control group did not use the CA . The duration of the trial was 18 months to vali date the CA . The outcome was a change in HbA1c from baseline . Results : In the intervention group , the final HbA1c was 7.19 % ( st and ard deviation [ SD ] ± 0.93 ) , with a difference from the start of −0.69 % ( p = .001 ) . In the control group , it was 7.71 % ( SD ± 1.37 ) , with a difference from the start of −0.09 % ( p not significant ) . Conclusions : This CA helps to improve HbA1c figures of T2DM patients with insulin when it is used by PCPs to make decisions when starting , continuing , or changing insulin and its dosage
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 .