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 effect of computer reminders on GPs' prescribing behaviour: A cluster-randomised trial
OBJECTIVE It is difficult to control drug-prescribing behaviour in general practice , despite the development and distribution of guidelines . The purpose of this study was to assess the effect on drug-prescribing behaviour of implementing prescribing guidelines by means of a reactive computer reminder system ( CRS ) . DESIGN Cluster-r and omised controlled trial with an incomplete block design in the south of the Netherl and s : 25 GPs ( 7 GP practice s ) received reminders about antibiotics and asthma/ COPD prescriptions , 28 GPs ( 7 GP practice s ) received reminders about cholesterol prescriptions . Prescription guidelines were integrated into the computerised GP information system . MEASUREMENTS Both performance indicators and prescription volumes were calculated as the main outcome measures . Next to individual volume measure , sum scores were constructed on the volume measures per drug group ( antibiotics , asthma/ COPD and cholesterol ) . RESULTS Variation between GPs turned out to be larger and more skewed than expected . No differences between groups were found for indicators and volumes related to recommendations advocating certain drugs . Although there was a tendency towards clinical ly relevant results for prescription volumes that were supposed to drop , the difference in sum score between the groups was not significant . For antibiotic prescriptions that were supposed to drop , the sum score for the intervention group was 28.2 ( 95 % CI : 20.8 - 44.5 ) prescriptions per 1000 patients per GP , while this was 39.7 ( 95 % CI : 29.7 - 64.1 ) for the control group ( p 0.2 ) . For prescriptions asthma/ COPD that were supposed to drop , the sum score for the intervention group was 1.1 ( 95 % CI : 0.6 - 2.6 ) prescriptions per 1000 patients per GP , while this was 2.2 ( 95 % CI : 1.4 - 4.3 ) for the control group ( p 0.1 ) . On three specific recommendations ( on quinolones for cystitis , corticosteroids for CPOD , and antibiotics for acute sore throat ) significant differences were found . CONCLUSIONS This study turned out to be underpowered due to high inter doctor variation in prescribing behaviour . Nevertheless , computerised reminders sometimes have a favourable effect on restricting certain drugs that are not or no longer indicated in general practice
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 .