Results were inconsistent for changes in CVD risk factors such as systolic and diastolic blood pressure , total and low-density lipoprotein cholesterol , and hemoglobin A1C levels .
CONCLUSIONS CDSSs are effective in improving clinician practice s related to screening and other preventive care services , clinical tests , and treatments .
CONTEXT Clinical decision support systems ( CDSSs ) can help clinicians assess cardiovascular disease ( CVD ) risk and manage CVD risk factors by providing tailored assessment s and treatment recommendations based on individual patient data .
The goal of this systematic review was to examine the effectiveness of CDSSs in improving screening for CVD risk factors , practice s for CVD-related preventive care services such as clinical tests and prescribed treatments , and management of CVD risk factors .
The Vermont Diabetes Information System: A Cluster Randomized Trial of a Population Based Decision Support System
BACKGROUND Optimal care for patients with diabetes is difficult to achieve in clinical practice . OBJECTIVE To evaluate the impact of a registry and decision support system on processes of care , and physiologic control . PARTICIPANTS R and omized trial with clustering at the practice level , involving 7,412 adults with diabetes in 64 primary care practice s in the Northeast . INTERVENTIONS Provider decision support ( reminders for overdue diabetes tests , alerts regarding abnormal results , and quarterly population reports with peer comparisons ) and patient decision support ( reminders and alerts ) . MEASUREMENTS AND MAIN RESULTS Process and physiologic outcomes were evaluated in all subjects . Functional status was evaluated in a r and om patient sample via question naire . We used multiple logistic regression to quantify the effect , adjusting for clustering and potential confounders . Intervention subjects were significantly more likely to receive guideline -appropriate testing for cholesterol ( OR = 1.39 ; [ 95%CI 1.07 , 1.80 ] P = 0.012 ) , creatinine ( OR = 1.40 ; [ 95%CI 1.06 , 1.84 ] P = 0.018 ) , and proteinuria ( OR = 1.74 ; [ 95%CI 1.13 , 1.69 ] P = 0.012 ) , but not A1C ( OR = 1.17 ; [ 95 % CI 0.80 , 1.72 ] P = 0.43 ) . Rates of control of A1C and LDL cholesterol were similar in the two groups . There were no differences in blood pressure , body mass index , or functional status . CONCLUSIONS A chronic disease registry and decision support system based on easily obtainable laboratory data was feasible and acceptable to patients and providers . This system improved the process of laboratory monitoring in primary care , but not physiologic control
Results were inconsistent for changes in CVD risk factors such as systolic and diastolic blood pressure , total and low-density lipoprotein cholesterol , and hemoglobin A1C levels .
CONCLUSIONS CDSSs are effective in improving clinician practice s related to screening and other preventive care services , clinical tests , and treatments .
CONTEXT Clinical decision support systems ( CDSSs ) can help clinicians assess cardiovascular disease ( CVD ) risk and manage CVD risk factors by providing tailored assessment s and treatment recommendations based on individual patient data .
The goal of this systematic review was to examine the effectiveness of CDSSs in improving screening for CVD risk factors , practice s for CVD-related preventive care services such as clinical tests and prescribed treatments , and management of CVD risk factors .