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 .
Implementing clinical guidelines in the treatment of diabetes mellitus in general practice. Evaluation of effort, process, and patient outcome related to implementation of a computer-based decision support system.
OBJECTIVES To evaluate the implementation of clinical guidelines for diabetes mellitus in general practice with a specific computer-based clinical decision support system ( CDSS ) as part of the intervention . METHODS R and omized study with health center as unit . General practice in Sør- and Nord-Trøndelag counties in Norway , 380,000 inhabitants . Seventeen health centers with 24 doctors and 499 patients with diabetes mellitus were in the intervention group and 12 health centers with 29 doctors and 535 patients were in the control group . Main outcome measures were group differences in fractions of patients without registration s ( process evaluation ) and mean group differences for the same variables ( patient outcome evaluation ) . RESULTS Statistically significant group differences were experienced for fractions of patients without registration of cigarette smoking ( intervention group , 82.6 % ; control group 94.5 % ) , body mass index ( 78.2 % vs. 93.0 % ) , and sufficient registration s for calculation of risk score for myocardial infa rct ion ( 91.1 % vs. 98.3 % ) ; all during 18 months . Large center variations were shown for all variables . The only statistically significant group difference was -2.3 mm Hg ( 95 % CI , -3.8 , -0.8 ) in diastolic blood pressure in favor of the intervention group . Statistically insignificant differences in favor of the intervention group were HbA1c , -0.1 % ( 95 % CI , -0.4 , 0.1 ) , systolic blood pressure , -1.2 mm Hg ( 95 % CI , -4.4 , 2.0 ) . Statistically insignificant differences in favor of the control group were fractions of smokers , + 3.0 % ( 95 % CI , -4.0 , 10.0 ) , body mass index , + 0.3 kg/m2 ( 95 % CI , -0.8 , 1.4 ) , risk score in female + 0.1 ( 95 % CI , -5.1 , 5.2 ) , and risk score in male + 2.6 ( 95 % CI , -14.2 , 19.5 ) . CONCLUSIONS Implementation of clinical guidelines for diabetes mellitus in general practice , by means of a CDSS and several procedures for implementation , did not result in a clinical ly significant change in doctors ' behavior or in patient outcome
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 .