***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 This study assessed the effect of a h and held computer-based decision support system ( DSS ) on  antibiotic use and patient outcomes in a critical care unit . DESIGN A DSS containing four types of evidence ( patient microbiology reports , local antibiotic guidelines , unit-specific antibiotic susceptibility data for common bacterial pathogens , and a clinical pulmonary infection score calculator ) was developed and implemented on a  h and held computer  for use in the intensive care unit at a tertiary referral hospital . System impact was assessed in a prospect i ve " before/after " cohort trial lasting 12 months . Outcome measures were defined daily doses ( DDDs ) of antibiotics per 1,000 patient-days , patient length of stay , and mortality . RESULTS The number of admissions , APACHE ( Acute Physiology , Age , and Chronic Health Evaluation ) II and SAPS ( Simplified Acute Physiology Score ) II for patients in preintervention , and intervention ( DSS use ) periods were statistically comparable . The mean patient length of stay and the use of antibiotics in the unit during six months of the DSS use decreased from 7.15 to 6.22 bed-days ( p = 0.02 ) and from 1,767 DDD to 1,458 DDD per 1,000 patient-days ( p = 0.04 ) , respectively , with no change in mortality . The DSS was accessed 674 times during 168 days of the trial . Microbiology reports and antibiotic guidelines were the two most commonly used ( 53 % and 22.5 % , respectively ) types of evidence . The greatest reduction was observed in the use of beta-lactamase-resistant penicillins and vancomycin . CONCLUSION H and held computer-based decision support contributed to a significant reduction in patient length of stay and antibiotic prescribing in a critical care unit A prospect i ve quasi-experimental study was undertaken in 218 patients with suspicion of nosocomial infection hospitalized in a polyvalent ICU where a new electronic device ( GERB ) has been design ed for antibiotic prescriptions . Two GERB-based applications were developed to provide local resistance maps ( LRMs ) and preliminary microbiological reports with therapeutic recommendation ( PMRTRs ) . Both applications used the data in the Laboratory Information System of the Microbiology Department to report on the optimal empiric therapeutic option , based on the most likely susceptibility profile of the microorganisms potentially responsible for infection in patients and taking into account the local epidemiology of the hospital department/unit . LRMs were used for antibiotic prescription in 20.2 % of the patients and PMRTRs in 78.2 % , and active antibiotics against the finally identified bacteria were prescribed in 80.0 % of the former group and 82.4 % of the latter . When neither LMRs nor PMRTRs were considered for empiric treatment prescription , only around 40 % of the antibiotics prescribed were active . Hence , the percentage appropriateness of the empiric antibiotic treatments was significantly higher when LRM or PMRTR guidelines were followed rather than other criteria . LRMs and PMRTRs applications are dynamic , highly accessible , and readily interpreted instruments that contribute to the appropriateness of empiric antibiotic treatments OBJECTIVE Computerized medical decision support tools have been shown to improve the quality of care and have been cited by the Institute of Medicine as one method to reduce pharmaceutical errors . We evaluated the impact of an antiinfective decision support tool in a pediatric intensive care unit ( PICU ) . METHODS We enhanced an existing adult antiinfective management tool by adding and changing medical logic to make it appropriate for pediatric patients . Process and outcomes measures were monitored prospect ively during a 6-month control and a 6-month intervention period . M and atory use of the decision support tool was initiated for all antiinfective orders in a 26-bed PICU during the intervention period . Clinician opinions of the decision support tool were surveyed via question naire . RESULTS The rate of pharmacy interventions for erroneous drug doses declined by 59 % . The rate of anti-infective subtherapeutic patient days decreased by 36 % , and the rate of excessive-dose days declined by 28 % . The number of orders placed per antiinfective course decreased 11.5 % , and the robust estimate of the antiinfective costs per patient decreased 9 % . The type of anti-infectives ordered and the number of antiinfective doses per patient remained similar , as did the rates of adverse drug events and antibiotic-bacterial susceptibility mismatches . The surveyed clinicians reported that use of the program improved their antiinfective agent choices as well as their awareness of impairments in renal function and reduced the likelihood of adverse drug events . CONCLUSIONS Use of the pediatric antiinfective decision support tool in a PICU was considered beneficial to patient care by the clinicians and reduced the rates of erroneous drug orders , improved therapeutic dosage targets , and was associated with a decreased robust estimate of antiinfective costs per patient . antiinfective agents , decision support systems , drug therapy , medication errors , child , infant The objective of this prospect i ve clinical usage study was to examine the value of the rule based ' Therapeutic Assistant ' integrated into an existing  Patient Data Management System ( PDMS ) in helping to prescribe a initial antibiotic regime in accordance with the requirements of accepted guidelines . A prospect i ve study comparing data before and after the introduction of the ' Therapeutic Assistant ' was carried out . An adequate therapy result ed significantly more often after the introduction of the ' Therapeutic Assistant ' [ p<0.05 ] ; however no difference between the regimes with and without the ' Therapeutic Assistant ' in the period after its introduction could be established . Whether the ' Therapeutic Assistant ' influenced the prescriptions made without it will have to be established in a further study Objective : To evaluate the hospital-wide impact of a st and ardized order set for the management of bacteremic severe sepsis on processes of medical care and patient outcomes . Design : Retrospective , before and after study design . Setting : Barnes-Jewish Hospital , a 1200-bed academic medical center . Patients : Bacteremic patients with severe sepsis ( 200 from the 18-month before period and 200 from the 18-month after period ) . Interventions : Hospital-wide implementation of a st and ardized order set for the management of bacteremic severe sepsis . Measurements and Main Results : A total of 400 patients with bacteremia and severe sepsis were selected at r and om within the specified time periods . Patients in the after group received more intravenous fluids in the first 12 hours after onset of hypotension ( 1627 ± 1862 mL vs. 2054 ± 2237 mL ; p = 0.04 ) and were more likely to receive appropriate initial antibiotic therapy ( 53.0 % vs. 65.5 % , p = 0.01 ) . In-hospital mortality was statistically decreased in the after group ( 55.0 % vs. 39.5 % , p < 0.01 ) , as was the hospital length of stay ( 28.7 ± 30.1 days vs. 22.4 ± 20.9 days ; p = 0.02 ) . Compared with the before group , the after group had reduced occurrence of renal failure ( 49.0 % vs. 36.0 % , p < 0.01 ) , cardiovascular failure ( 70.5 % vs. 57.0 % , p < 0.01 ) , and were less likely to require vasopressors after initial fluid resuscitation ( 68.5 % vs. 52.5 % , p < 0.01 ) . Conclusions : The implementation of a hospital-wide st and ardized order set for the management of bacteremic severe sepsis was associated with greater fluid administration , improved antibiotic therapy , decreased incidence of organ failure , and improved survival OBJECTIVE Antibiotic computerized decision support systems ( CDSSs ) were developed to guide antibiotic decisions , yet prescriptions of CDSS-recommended antibiotics have remained low . Our aim was to identify predictors of patients ' receipt of empiric antibiotic therapies recommended by a CDSS when the prescribing physician had an initial preference for using broad-spectrum antibiotics . METHODS We conducted a prospect i ve cohort study in a 1 500-bed tertiary-care hospital in Singapore . We included all patients admitted from October 1 , 2011 through September 30 , 2012 , who were prescribed piperacillin-tazobactam or carbapenem for empiric therapy and auto-triggered to receive antibiotic recommendations by the in-house antibiotic CDSS . Relevant data on the patient , prescribing and attending physicians were collected via electronic linkages of medical records and administrative data bases . To account for clustering , we used multilevel logistic regression models to explore factors associated with receipt of CDSS-recommended antibiotic therapy . RESULTS One-quarter of the 1 886 patients received CDSS-recommended antibiotics . More patients treated for pneumonia ( 33.2 % ) than sepsis ( 12.1 % ) and urinary tract infections ( 7.1 % ) received CDSS-recommended antibiotic therapies . The prescribing physician - but not the attending physician or clinical specialty - accounted for some ( 13.3 % ) of the variation . Prior hospitalization ( odds ratio [ OR ] 1.32 , 95 % CI , 1.01 - 1.71 ) , presumed pneumonia ( OR 6.77 , 95 % CI , 3.28 - 13.99 ) , intensive care unit ( ICU ) admission ( OR 0.38 , 95 % CI , 0.21 - 0.66 ) , and renal impairment ( OR 0.70 , 95 % CI , 0.52 - 0.93 ) were factors associated with patients ' receipt of CDSS-recommended antibiotic therapies . CONCLUSIONS We observed that ICU admission and renal impairment were negative predictors of patients ' receipt of CDSS-recommended antibiotic therapies . Patients admitted to ICU and those with renal impairment might have more complex clinical conditions that require a physician 's assessment in addition to antibiotic CDSS Electronic clinical decision support systems ( CDSS ) have been hailed for their potential to improve clinical outcomes . Using a pretest/posttest design , an Internet-based CDSS design ed to optimize antimicrobial prescribing was pilot tested for community-acquired pneumonia in 5 rural hospitals in southwestern Idaho . An antimicrobial management team was created in each hospital to address clinicians ’ perception of excessive time required for direct use of the CDSS . In pooled hospital data , agreement with CDSS recommendations improved to a statistically significant level . However , inspection of data at the individual hospital level demonstrated that almost all improvement occurred in a single hospital . Failure in the other hospitals appeared to be primarily a consequence of organizational and cultural barriers . These barriers are discussed to underst and keys for successful future implementation of CDSS in rural hospitals , drawing on experience with cultural barriers from other industries , specifically aviation OBJECTIVES Antibiotic stewardship is important , but the ideal strategy for providing stewardship in a hospital setting is unknown . A practical , sustainable and transferable strategy is needed . This study evaluates the impact of a novel computerized antimicrobial approval system on antibiotic-prescribing behaviour in a hospital . Effects on drug consumption , antibiotic resistance patterns of local bacteria and patient outcomes were monitored . METHODS The study was conducted at a tertiary referral teaching hospital in Melbourne , Australia . The system was deployed in January 2005 and guided the use of 28 restricted antimicrobials .  Data were collected over 7 years : 5 years before and 2 years after deployment . Uptake of the system was evaluated using an in-built audit trail . Drug utilization was prospect ively monitored using pharmacy data ( as defined daily doses per 1000 bed-days ) and analysed via time-series analysis with segmental linear regression . Antibiograms of local bacteria were prospect ively evaluated . In-hospital mortality and length of stay for patients with Gram-negative bacteraemia were also reported . RESULTS Between 250 and 300 approvals were registered per month during 2006 . The gradients in the use of third- and fourth-generation cephalosporins ( + 0.52 , -0.05 , -0.39 ; P < 0.01 ) , glycopeptides ( + 0.27 , -0.53 ; P = 0.09 ) , carbapenems ( + 0.12 , -0.24 ; P = 0.21 ) , aminoglycosides ( + 0.15 , -0.27 ; P < 0.01 ) and quinolones ( + 0.76 , + 0.11 ; P = 0.08 ) all fell after deployment , while extended-spectrum penicillin use increased . Trends in increased susceptibility of Staphylococcus aureus to methicillin and improved susceptibility of Pseudomonas spp . to many antibiotics were observed . No increase in adverse outcomes for patients with Gram-negative bacteraemia was observed . CONCLUSIONS The system was successfully adopted and significant changes in antimicrobial usage were demonstrated STUDY OBJECTIVE Despite evidence that guideline adherence improves clinical outcomes , management of pneumonia patients varies in emergency departments ( EDs 
    Output:
    
CDS was associated with lower antibiotic utilisation , increased compliance with antibiotic guidelines and reductions in antimicrobial resistance .
Conflicting effects of CDS on length of stay , antibiotic costs and system uptake were also noted .
CDS has the potential to improve the adequacy of antibiotic coverage and marginally decrease mortality in hospital-related setting