***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 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 BACKGROUND Adverse drug-related events are common in the elderly , and inappropriate prescribing is a preventable risk factor . Our objective was to determine whether inappropriate prescribing could be reduced when primary care physicians had computer-based access to information on all prescriptions dispensed and automated alerts for potential prescribing problems . METHODS We r and omly assigned 107 primary care physicians with at least 100 patients aged 66 years and older ( total 12 560 ) to a group receiving computerized decision-making support ( CDS ) or a control group . Physicians in the CDS group had access to information on current and past prescriptions through a dedicated computer link to the provincial seniors ' drug-insurance program . When any of 159 clinical ly relevant prescribing problems were identified by the CDS software , the physician received an alert that identified the nature of the problem , possible consequences and alternative therapy . The rate of initiation and discontinuation of potentially inappropriate prescriptions was assessed over a 13-month period . RESULTS In the 2 months before the study , 31.8 % of the patients in the CDS group and 33.3 % of those in the control group had at least 1 potentially inappropriate prescription . During the study the number of new potentially inappropriate prescriptions per 1000 visits was significantly lower ( 18 % ) in the CDS group than in the control group ( relative rate [ RR ] 0.82 , 95 % confidence interval [ CI ] 0.69 - 0.98 ) , but differences between the groups in the rate of discontinuation of potentially inappropriate prescriptions were significant only for therapeutic duplication by the study physician and another physician ( RR 1.66 , 95 % CI 0.99 - 2.79 ) and drug interactions caused by prescriptions written by the study physician ( RR 2.15 , 95 % CI 0.98 - 4.70 ) . INTERPRETATION Computer-based access to complete drug profiles and alerts about potential prescribing problems reduces the rate of initiation of potentially inappropriate prescriptions but has a more selective effect on the discontinuation of such prescriptions BACKGROUND Medication errors are common , and while most such errors have little potential for harm they cause substantial extra work in hospitals . A small proportion do have the potential to cause injury , and some cause preventable adverse drug events . OBJECTIVE To evaluate the impact of computerized physician order entry ( POE ) with decision support in reducing the number of medication errors . DESIGN Prospect i ve time series analysis , with four periods . SETTING AND PARTICIPANTS All patients admitted to three medical units were studied for seven to ten-week periods in four different years . The baseline period was before implementation of POE , and the remaining three were after . Sophistication of POE increased with each successive period . INTERVENTION Physician order entry with decision support features such as drug allergy and drug-drug interaction warnings . MAIN OUTCOME MEASURE Medication errors , excluding missed dose errors . RESULTS During the study , the non-missed-dose medication error rate fell 81 percent , from 142 per 1,000 patient-days in the baseline period to 26.6 per 1,000 patient-days in the final period ( P < 0.0001 ) . Non-intercepted serious medication errors ( those with the potential to cause injury ) fell 86 percent from baseline to period 3 , the final period ( P = 0.0003 ) . Large differences were seen for all main types of medication errors : dose errors , frequency errors , route errors , substitution errors , and allergies . For example , in the baseline period there were ten allergy errors , but only two in the following three periods combined ( P < 0.0001 ) . CONCLUSIONS Computerized POE substantially decreased the rate of non-missed-dose medication errors . A major reduction in errors was achieved with the initial version of the system , and further reductions were found with addition of decision support features BACKGROUND Physicians frequently need to start antibiotic therapy before the results of bacterial cultures and antibiotic susceptibility tests are available . We developed and evaluated a computerized antibiotic consultant to assist physicians in the selection of appropriate empiric antibiotics . METHODS We used a two-stage r and om- selection study to compare antibiotics suggested by the antibiotic consultant with 482 associated antibiotic susceptibility results and the concurrent antibiotics ordered by physicians . The antibiotics ordered by r and omized physicians were then compared between crossover periods of antibiotic consultant use . RESULTS The antibiotic consultant suggested an antibiotic regimen to which all isolated pathogens were shown to be susceptible for 453 ( 94 % ) of 482 culture results , while physicians ordered an antibiotic regimen to which all isolated pathogens were susceptible for 369 culture results ( 77 % ) ( P < .001 ) . The physicians who prescribed antibiotics to which all pathogens were susceptible did so a mean of 21 hours after the culture specimens were collected . Physicians ordered appropriate antibiotics within 12 hours of the culture collection significantly more often when they had use of the antibiotic consultant than during the period before use ( P < .035 ) . Moreover , 88 % of the physicians stated they would recommend the program to other physicians , 85 % said the program improved their antibiotic selection , and 81 % said they felt use of the program improved patient care . CONCLUSIONS Information from computer-based medical records can be used to help improve physicians ' selection of empiric antibiotics for infections Introduction Medication errors in the intensive care unit ( ICU ) are frequent and lead to attributable patient morbidity and mortality , increased length of ICU stay and substantial extra costs . We investigated if the introduction of a computerized ICU system ( Centricity Critical Care Clinisoft , GE Healthcare ) reduced the incidence and severity of  medication prescription errors  (  MPEs  ) . Methods A prospect i ve trial was conducted in a  paper-based unit ( PB-U ) versus a computerized unit ( C-U ) in a 22-bed ICU of a tertiary university hospital . Every medication order and medication prescription error was vali date d by a clinical pharmacist . The registration of different classes of MPE was done according to the National Coordinating Council for Medication Error Reporting and Prevention guidelines . An independent panel evaluated the severity of MPEs . We identified three groups : minor MPEs ( no potential to cause harm ) ; intercepted MPEs ( potential to cause harm but intercepted on time ) ; and serious MPEs ( non-intercepted potential adverse drug events ( ADE ) or ADEs , being MPEs with potential to cause , or actually causing , patient harm ) . Results The C-U and the PB-U each contained 80 patient-days , and a total of 2,510 medication prescriptions were evaluated . The clinical pharmacist identified 375 MPEs . The incidence of MPEs was significantly lower in the C-U compared with the PB-U ( 44/1286 ( 3.4 % ) versus 331/1224 ( 27.0 % ) ; P < 0.001 ) . There were significantly less minor MPEs in the C-U than in the PB-U ( 9 versus 225 ; P < 0.001 ) . Intercepted MPEs were also lower in the C-U ( 12 versus 46 ; P < 0.001 ) , as well as the non-intercepted potential ADEs ( 21 versus 48 ; P < 0.001 ) . There was also a reduction of ADEs ( 2 in the C-U versus 12 in the PB-U ; P < 0.01 ) . No fatal errors occurred . The most frequent drug classes involved were cardiovascular medication and antibiotics in both groups . Patients with renal failure experienced less dosing errors in the C-U versus the PB-U ( 12 versus 35 serious MPEs ; P < 0.001 ) . Conclusion The ICU computerization , including the medication order entry , result ed in a significant decrease in the occurrence and severity of medication errors in the ICU Introduction The study aim ed to compare the impact of computerised physician order entry ( CPOE ) without decision support with h and -written prescribing ( HWP ) on the frequency , type and outcome of medication errors ( MEs ) in the intensive care unit . Methods Details of MEs were collected before , and at several time points after , the change from HWP to CPOE . The study was conducted in a London teaching hospital 's 22-bedded general ICU . The sampling periods were 28 weeks before and 2 , 10 , 25 and 37 weeks after introduction of CPOE . The unit pharmacist prospect ively recorded details of MEs and the total number of drugs prescribed daily during the data collection periods , during the course of his normal chart review . Results The total proportion of MEs was significantly lower with CPOE ( 117 errors from 2429 prescriptions , 4.8 % ) than with HWP ( 69 errors from 1036 prescriptions , 6.7 % ) ( p < 0.04 ) . The proportion of errors reduced with time following the introduction of CPOE ( p < 0.001 ) . Two errors with CPOE led to patient harm requiring an increase in length of stay and , if administered , three prescriptions with CPOE could potentially have led to permanent harm or death . Differences in the types of error between systems were noted . There was a reduction in major/moderate patient outcomes with CPOE when non-intercepted and intercepted errors were combined ( p = 0.01 ) . The mean baseline APACHE II score did not differ significantly between the HWP and the CPOE periods ( 19.4 versus 20.0 , respectively , p = 0.71 ) . Conclusion Introduction of CPOE was associated with a reduction in the proportion of MEs and an improvement in the overall patient outcome score ( if intercepted errors were included ) . Moderate and major errors , however , remain a significant concern with CPOE CONTEXT Adverse drug events ( ADEs ) are a significant and costly cause of injury during hospitalization . OBJECTIVES To evaluate the efficacy of 2 interventions for preventing nonintercepted serious medication errors , defined as those that either result ed in or had potential to result in an ADE and were not intercepted before reaching the patient . DESIGN Before-after comparison between phase 1 ( baseline ) and phase 2 ( after intervention was implemented ) and , within phase 2 , a r and omized comparison between physician computer order entry ( POE ) and the combination of POE plus a team intervention . SETTING Large tertiary care hospital . PARTICIPANTS For the comparison of phase 1 and 2 , all patients admitted to a stratified r and om sample of 6 medical and surgical units in a tertiary care hospital over a 6-month period , and for the r and omized comparison during phase 2 , all patients admitted to the same units and 2 r and omly selected additional units over a subsequent 9-month period . INTERVENTIONS A physician computer order entry system ( POE ) for all units and a team-based intervention that included changing the role of pharmacists , implemented for half the units . MAIN OUTCOME MEASURE Nonintercepted serious medication errors . RESULTS Comparing identical units between phases 1 and 2 , nonintercepted serious medication errors decreased 55 % , from 10.7 events per 1000 patient-days to 4.86 events per 1000 ( P=.01 ) . The decline occurred for all stages of the medication-use process . Preventable ADEs declined 17 % from 4.69 to 3.88 ( P=.37 ) , while nonintercepted potential ADEs declined 84 % from 5.99 to 0.98 per 1000 patient-days ( P=.002 ) . When POE-only was compared with the POE plus team intervention combined , the team intervention conferred no additional benefit over PO 
    Output:
    
Concluding , it seems that electronic prescribing can reduce the risk for medication errors and ADE .