***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: OBJECTIVE Many hospitals utilize antimicrobial management teams ( AMTs ) to improve patient care . However , most function with minimal computer support . We evaluated the effectiveness and cost-effectiveness of a computerized clinical decision support system for the management of antimicrobial utilization . DESIGN A r and omized controlled trial in adult in patients between May 10 and August 3 , 2004 . Antimicrobial utilization was managed by an existing AMT using the system in the intervention arm and without the system in the control arm . The system was developed to alert the AMT of potentially inadequate antimicrobial therapy . MEASUREMENTS Outcomes assessed were hospital antimicrobial expenditures , mortality , length of hospitalization , and time spent managing antimicrobial utilization . RESULTS The AMT intervened on 359 ( 16 % ) of 2,237 patients in the intervention arm and 180 ( 8 % ) of 2,270 in the control arm , while spending approximately one hour less each day on the intervention arm . Hospital antimicrobial expenditures were $ 285,812 in the intervention arm and $ 370,006 in the control arm , for a savings of $ 84,194 ( 23 % ) , or $ 37.64 per patient . No significant difference was observed in mortality ( 3.26 % vs. 2.95 % , p = 0.55 ) or length of hospitalization ( 3.84 vs. 3.99 days , p = 0.38 ) . CONCLUSION Use of the system facilitated the management of antimicrobial utilization by allowing the AMT to intervene on more patients receiving inadequate antimicrobial therapy and to achieve substantial time and cost savings for the hospital . This is the first study that demonstrates in a patient-r and omized controlled trial that computerized clinical decision support systems can improve existing antimicrobial management programs OBJECTIVE : Asthma continues to be 1 of the most common chronic diseases of childhood and affects ∼6 million US children . Although National Asthma Education Prevention Program guidelines exist and are widely accepted , previous studies have demonstrated poor clinician adherence across a variety of population s. We sought to determine if clinical decision support ( CDS ) embedded in an electronic health record ( EHR ) would improve clinician adherence to national asthma guidelines in the primary care setting . METHODS : We conducted a prospect i ve cluster-r and omized trial in 12 primary care sites over a 1-year period . Practice s were stratified for analysis according to whether the site was urban or suburban . Children aged 0 to 18 years with persistent asthma were identified by International Classification of Diseases , Ninth Revision codes for asthma . The 6 intervention- practice sites had CDS alerts imbedded in the EHR . Outcomes of interest were the proportion of children with at least 1 prescription for controller medication , an up-to- date asthma care plan , and the performance of office-based spirometry . RESULTS : Increases in the number of prescriptions for controller medications , over time , was 6 % greater ( P = .006 ) and 3 % greater for spirometry ( P = .04 ) in the intervention urban practice s. Filing an up-to- date asthma care plan improved 14 % ( P = .03 ) and spirometry improved 6 % ( P = .003 ) in the suburban practice s with the intervention . CONCLUSION : In our study , using a cluster-r and omized trial design , CDS in the EHR , at the point of care , improved clinician compliance with National Asthma Education Prevention Program guidelines BACKGROUND Primary care physicians ( PCPs ) care for most non-dialysis-dependent patients with chronic kidney disease ( CKD ) . Studies suggest that PCPs may deliver suboptimal CKD care . One means to improve PCP treatment of CKD is clinical decision support systems ( CDSSs ) . STUDY DESIGN Cluster-r and omized controlled trial . SETTING & PARTICIPANTS 30 PCPs in a university-based outpatient general internal medicine practice and their 248 patients with moderate to advanced CKD who had not been referred to a nephrologist . INTERVENTION 2 CKD educational sessions were held for PCPs in both arms . The 15 intervention-arm PCPs also received real-time automated electronic medical record alerts for patients with estimated glomerular filtration rates < 45 mL/min/1.73 m(2 ) recommending renal referral and urine albumin quantification if not done within the prior year . OUTCOMES Primary outcome was referral to a nephrologist ; secondary outcomes were albuminuria/proteinuria assessment , CKD documentation , optimal blood pressure ( ie , < 130/80 mm Hg ) , and use of renoprotective medications . RESULTS The intervention and control arms did not differ in renal referrals ( 9.7 % vs 16.5 % , respectively ; between-group difference , -6.8 % ; 95 % CI , -15.5 % to 1.8 % ; P = 0.1 ) or proteinuria assessment s ( 39.3 % vs 30.1 % , respectively ; between-group difference , 9.2 % ; 95 % CI , -2.7 % to 21.1 % ; P = 0.1 ) . For intervention and control patients without a baseline proteinuria assessment , 27.7 % versus 16.3 % , respectively , had one at follow-up ( P = 0.06 ) . After controlling for clustering , these findings were largely unchanged and no significant differences were apparent between groups . LIMITATIONS Small single-center university-based practice , use of a passive CDSS that required PCPs to trigger the electronic order set . CONCLUSIONS PCPs were willing to partake in a r and omized trial of a CDSS to improve outpatient CKD care . Although CDSSs may have potential , larger studies are needed to further explore how best to deploy them to enhance CKD care BACKGROUND Computerized decision support systems ( CDSSs ) are believed to enhance patient care and reduce healthcare costs ; however the current evidence is limited and the cost-effectiveness remains unknown . OBJECTIVE To estimate the long-term cost-effectiveness of a CDSS linked to evidence -based treatment recommendations for type 2 diabetes . METHODS Using the Ontario Diabetes Economic Model , changes in factors ( eg , HbA1c ) from a r and omized controlled trial were used to estimate cost-effectiveness . The cost of implementation , development , and maintenance of the core data set , and projected diabetes-related complications were included . The base case assumed a 1-year treatment effect , 5 % discount rate , and 40-year time horizon . Univariate , one-way sensitivity analyses were carried out by altering different parameter values . The perspective was the Ontario Ministry of Health and costs were in 2010 Canadian dollars . RESULTS The cost of implementing the intervention was $ 483,699 . The one-year intervention reduced HbA1c by 0.2 and systolic blood pressure by 3.95 mm Hg , but increased body mass index by 0.02 kg/m² , result ing in a relative risk reduction of 14 % in the occurrence of amputation . The model estimated that the intervention result ed in an additional 0.0117 quality -adjusted life year ; the incremental cost-effectiveness ratio was $ 160,845 per quality -adjusted life-year . CONCLUSION The web-based prototype decision support system slightly improved short-term risk factors . The model predicted moderate improvements in long-term health outcomes . This disease management program will need to develop considerable efficiencies in terms of costs and processes or improved effectiveness to be considered a cost-effective intervention for treating patients with type 2 diabetes 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 Abstract Objectives : To investigate the effect of a computer based clinical decision support system and a risk chart on absolute cardiovascular risk , blood pressure , and prescribing of cardiovascular drugs in hypertensive patients . Design : Cluster r and omised controlled trial . Setting : 27 general practice s in Avon . Participants : 614 patients aged between 60 and 79 years with high blood pressure . Interventions : Patients were r and omised to computer based clinical decision support system plus cardiovascular risk chart ; cardiovascular risk chart alone ; or usual care . Main outcome measures : Percentage of patients in each group with a five year cardiovascular risk≥10 % , systolic blood pressure , diastolic blood pressure , prescribing of cardiovascular drugs . Results : Patients in the computer based clinical decision support system and chart only groups were no more likely to have cardiovascular risk reduced to below 10 % than patients receiving usual care . Patients in the computer based clinical decision support group were more likely to have a cardiovascular risk≥10 % than chart only patients , odds ratio 2.3 ( 95 % confidence interval 1.1 to 4.8 ) . The chart only group had significantly lower systolic blood pressure compared with the usual care group ( difference in means−4.6 mm Hg ( 95 % confidence interval−8.4 to−0.8 ) . Reduction of diastolic blood pressure did not differ between the three groups . The chart only group were twice as likely to be prescribed two classes of cardiovascular drugs and over three times as likely to be prescribed three or more classes of drugs compared with the other groups . Conclusions : The computer based clinical decision support system did not confer any benefit in absolute risk reduction or blood pressure control and requires further development and evaluation before use in clinical care can be recommended . Use of chart guidelines are associated with a potentially important reduction in systolic blood pressure BACKGROUND Computerized decision support systems ( CDSSs ) linked with electronic medical records ( EMRs ) are promoted as an effective means of improving patient care . However , very few high- quality studies are set in routine , community-based clinical care , and no consistent evidence of an effect on patient outcomes has been found . METHODS A r and omized controlled trial among EMR-using primary care practice s in Ontario , Canada . Patients 55 years or older with previous vascular events , diabetes mellitus , hypertension , or hypercholesterolemia were r and omized to the Computerization of Medical Practice s for the Enhancement of Therapeutic Effectiveness ( COMPETE III ) CDSS intervention or to usual care . The intervention included personally tailored electronic vascular risk monitoring and treatment advice shared between the physician and patient , risk calculation , and a clinical re source . The primary outcome was a composite score of 8 recommended process outcomes at 1 year . Data collectors were blinded to group allocation . Analysis used the intention-to-treat principle with multiple imputation for missing data . RESULTS We r and omized and included in the analysis 1102 patients in 49 community-based physician practice s ( 53.4 % female ; mean age , 69.1 years ; 28.0 % with a previous vascular event ) . The intervention group ( 545 [ 49.5 % ] ) had a significantly greater improvement in mean process composite , with a difference of 4.70 ( P < .001 ) on a 27-point scale . Intervention patients had significantly higher odds of rating their continuity of care ( 4.18 ; P < .001 ) and their ability to improve their vascular health ( 3.07 ; P < .001 ) as improved . Despite this improvement , the clinical outcomes -vascular events , clinical variables , and quality of life-were not improved . CONCLUSION Despite favorable review s and important improvements in the complex processes required to reduce vascular risk , clinical outcomes remain unchanged BACKGROUND Decision-support information technology is often adopted to improve clinical decision making , but it is rarely rigorously evaluated . Congress m and ated the evaluation of Problem-Knowledge Couplers ( PKC Corp , Burlington , Vt ) , a decision-support tool proposed for the Department of Defense 's new health information network . METHODS This was a patient-level r and omized trial conducted at 2 military practice s. A total of 936 patients were allocated to the intervention group  
    Output:
    
We observed differences for costs and health service utilization , although these were often small in magnitude .
Across clinical setting s , new generation CDSSs integrated with EHRs do not affect mortality and might moderately improve morbidity outcomes