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 .
Effectiveness of a Multicomponent Quality Improvement Strategy to Improve Achievement of Diabetes Care Goals: A Randomized, Controlled Trial.
BACKGROUND Achievement of diabetes care goals is suboptimal globally . Diabetes-focused quality improvement ( QI ) is effective but remains untested in South Asia . OBJECTIVE To compare the effect of a multicomponent QI strategy versus usual care on cardiometabolic profiles in patients with poorly controlled diabetes . DESIGN Parallel , open-label , pragmatic r and omized , controlled trial . ( Clinical Trials.gov : NCT01212328 ) . SETTING Diabetes clinics in India and Pakistan . PATIENTS 1146 patients ( 575 in the intervention group and 571 in the usual care group ) with type 2 diabetes and poor cardiometabolic profiles ( glycated hemoglobin [ HbA1c ] level ≥8 % plus systolic blood pressure [ BP ] ≥140 mm Hg and /or low-density lipoprotein cholesterol [ LDLc ] level ≥130 mg/dL ) .  INTERVENTION Multicomponent QI strategy comprising nonphysician care coordinators and decision-support electronic health records . MEASUREMENTS Proportions achieving HbA1c level less than 7 % plus BP less than 130/80 mm Hg and /or LDLc level less than 100 mg/dL ( primary outcome ) ; mean risk factor reductions , health-related quality of life ( HRQL ) , and treatment satisfaction ( secondary outcomes ) . RESULTS Baseline characteristics were similar between groups . Median diabetes duration was 7.0 years ; 6.8 % and 39.4 % of participants had preexisting cardiovascular and microvascular disease , respectively ; mean HbA1c level was 9.9 % ; mean BP was 143.3/81.7 mm Hg ; and mean LDLc level was 122.4 mg/dL. Over a median of 28 months , a greater percentage of intervention participants achieved the primary outcome ( 18.2 % vs. 8.1 % ; relative risk , 2.24 [ 95 % CI , 1.71 to 2.92 ] ) . Compared with usual care , intervention participants achieved larger reductions in HbA1c level ( -0.50 % [ CI , -0.69 % to -0.32 % ] ) , systolic BP ( -4.04 mm Hg [ CI , -5.85 to -2.22 mm Hg ] ) , diastolic BP ( -2.03 mm Hg [ CI , -3.00 to -1.05 mm Hg ] ) , and LDLc level ( -7.86 mg/dL [ CI , -10.90 to -4.81 mg/dL ] ) and reported higher HRQL and treatment satisfaction . LIMITATION Findings were confined to urban specialist diabetes clinics . CONCLUSION Multicomponent QI improves achievement of diabetes care goals , even in re source -challenged clinics . PRIMARY FUNDING SOURCE National Heart , Lung , and Blood Institute and UnitedHealth Group
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 .