***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: Purpose To compare medication administration error rates before and after the provision of educational sessions using either traditional didactic lecture or simulation-based training . Methods A single-center , parallel , controlled , prospect i ve study conducted in adult coronary critical care ( CCU ) and medical intensive care units ( MICU ) . Twenty-four nurses were observed administering medications . Documentation included drug name , dose , route , time and technique during observation and active medication orders in the patient ’s chart . A direct observation method was completed at baseline and repeated twice after the interventions . Data obtained during observation were analyzed for medication administration error rates . Interventions were two types of educational sessions with content developed from baseline medication administration error data : simulation-based training for CCU nurses and a didactic lecture for MICU nurses . Quizzes completed before and after the interventions were used to assess knowledge . Results A total of 880 doses ( 402 CCU , 478 MICU ) were observed . After the simulation-based educational intervention in the CCU , medication administration error rates decreased from 30.8 to 4.0 % ( p < 0.001 ) in the initial post-intervention observation and were sustained in the final post-intervention observation ( 30.8 to 6.2 % ; p < 0.001 ) . The error rate in the MICU after the didactic lecture intervention was not significantly different from the baseline and increased in the final post-intervention observation from 20.8 to 36.7 % ( p = 0.002 ) . Mean quiz scores were significantly improved after education sessions in both ICUs . Conclusions Simulation-based learning provides a significant advantage to patient care through the reduction of medication administration errors compared to lecture style education OBJECTIVE To compare eclampsia and magnesium toxicity management among residents r and omly assigned to lecture or simulation-based education .  STUDY DESIGN Statified by year , residents ( n = 38 ) were r and omly assigned to 3 educational intervention groups : Simulation→Lecture , Simulation , and Lecture . Postintervention simulations were performed for all and scored using st and ardized lists . Maternal , fetal , eclampsia management , and magnesium toxcity scores were assigned . Mann-Whitney U , Wilcoxon rank sum and χ(2 ) tests were used for analysis . RESULTS Postintervention maternal ( 16 and 15 vs 12 ; P < .05 ) and eclampsia ( 19 vs 16 ; P < .05 ) scores were significantly better in simulation based compared with lecture  groups . Postintervention magnesium toxcitiy and fetal scores were not different among groups . Lecture added to simulation did not lead to incremental benefit when eclampsia scores were compared between Simulation→Lecture and Simulation ( 19 vs 19 ; P = nonsignificant ) . CONCLUSION Simulation training is superior to traditional lecture alone for teaching crucial skills for the optimal management of both eclampsia and magnesium toxicity , 2 life-threatening obstetric emergencies Context The use of ratios to express drug concentrations makes dosing calculations confusing and may cause drug errors . Contribution The research ers labeled epinephrine ampules with ratios only ( 1 mL of 1:1000 ) or concentration only ( 1 mg in 1 mL ) and r and omly assigned providers to use one or the other in a simulated anaphylactic arrest . Providers using ratios made many more errors and took longer to give the drug than providers using concentrations . Caution The case was simulated , and in reality , ampules are labeled with both expressions . Implication The use of ratios to express  epinephrine concentration is confusing , and the revision of labeling to express concentration in more clinical ly intuitive ways may reduce errors . The Editors Clinical error and negligence are responsible for disabling injuries in about 1 in 25 hospital admissions ( 1 ) . Most of these injuries are caused by adverse drug events , which prolong hospital stay , increase care costs , and nearly double a patient 's risk for death ( 2 , 3 ) . About one third of adverse drug events occur during drug administration , when interception is unlikely ( 4 ) . The confusion caused by expressing the concentrations of drug solutions in different ways is an important cause of dose errors ( 510 ) . Converting among ratios , percentages , international units , mols , micrograms , and milligrams causes substantial difficulty , especially for less experienced physicians or those most removed from acute care . Epinephrine , lidocaine , heparin , and potassium chloride are frequently associated with drug error ( 11 ) . It may be no coincidence that the strengths of these drug solutions are typically expressed in ratios , percentages , international units , and millimols , respectively . Any physician could be confronted with a patient in cardiac arrest or anaphylaxis , in whom the consequences of a dosing error are grave . In an emergency , dose calculation must be easy . Despite widespread concern expressed over many years ( 58 , 12 ) , ampule labels have changed little , possibly because research in this field has relied on surveys and question naires , which rank unfavorably in the hierarchy of evidence -based medicine . We evaluated the effect of ampule labeling on  physicians ' clinical performance in a simulated critical incident in a r and omized , single-blinded , controlled trial . We r and omly assigned providers to receive an ampule of epinephrine labeled as 1 mg in 1 mL or as 1 mL of 1:1000 , and presented them with a scenario requiring the acute management of a child with anaphylaxis . A pediatric case was chosen because participants would be less likely to know the epinephrine dose and more likely to have to consult a resuscitation protocol and calculate the dose . We then measured the quantity of  epinephrine  administered and the time taken to give it . Methods The study received institutional ethical approval . The scenario was enacted by using a pediatric mannequin in the hospital 's high-fidelity patient simulator center ( Human Patient Simulator , Medical Education Technologies , Sarasota , Florida ) , which was configured as a rural emergency room . Hospital-affiliated physicians in our institution without pediatric experience volunteered to participate without payment . The Appendix shows the volunteers ' briefing . Scenario Participants were asked to manage the case of a 5-year-old child with known peanut allergy who is brought in for care after peanut exposure . The patient simulator was programmed to mimic development of acute anaphylaxis with hypotension profound enough to warrant 0.12 mg of intramuscular epinephrine , according to the protocol ( 13 ) . Participants needed to calculate the correct volume of epinephrine  to administer ( 0.12 mL ) by using the ampule label to which they were r and omly assigned ( mass concentration only [ 1 mg in 1 mL ] or ratio only [ 1 mL of 1:1000 ] ) . The trial ampules were made to resemble real epinephrine ampules in every way except this labeling change . The protocol stated that the dose required was 0.12 mg without referring to ratios or volumes ( Appendix Figure ) . An actor playing a nurse was available to provide help ; participating physicians also had access to a pharmacopeia , calculator , paper , and pencil . Participants who requested other epinephrine presentations were told that none were available . Appendix Figure . Protocol for determining the dose of epinephrine . IM = intramuscular ; IV = intravenous . Data Collection We recorded the participants ' age , seniority , specialty , and sex . Audiovisual recordings of the scenarios were made . Investigators who were blinded to each participant 's r and omization status subsequently recorded the dose of epinephrine administered and the time taken for it to be given . Statistical Analysis Power calculations indicated that 14 participants were required in each group to achieve a significance level of 5 % and study power of 80 % . This was based on observations from another study that suggested differences of 50 % in the probability of a dose error and 20 seconds in dose administration time between the groups ( 14 ) . A r and omization sequence of 28 unsorted nonunique numbers ranging from 0 to 1 was generated online ( Research R and omizer , Social Psychology Network ; available at www.r and omizer.org ) and implemented by a research er who was not involved in data collection . We assessed the effect of ampule labeling on the accuracy of the epinephrine dose by using logistic regression , in which the dependent variable was dose given and was categorized as within 10 % of the correct 120-g dose ( considered acceptable because of the practical difficulty of measuring a very small volume in a 1-mL syringe ) or more than 10 % ( dose error ) , and by using linear regression , in which the dependent variable was the absolute value of dose error ( dose given minus target dose ) . We initially fitted the logistic model with ampule labeling and provider characteristics ( age , seniority , specialty , and sex ) as independent variables . However , there was no association between provider characteristics and dosing errors , and inclusion of provider variables only appeared to inflate the estimate of the risk for error with labeling . Therefore , ampule labeling is the only independent variable in the final model reported here . We included ampule labeling and provider characteristics ( age , seniority , specialty , and sex ) as independent variables in the linear model . We also used linear regression to assess the effect of ampule labeling ( independent variable ) on the time taken to administer epinephrine  ( dependent variable ) . Goodness-of-fit of the models was confirmed by examination of deviance residuals ( logistic model ) and st and ardized residuals ( regression models ) . We performed all analyses by using the R 2.2.1 statistical package ( 15 ) . Role of the Funding Source The Association of Anaesthetists of Great Britain and Irel and provided funding but had no role in study design , conduct , or analysis , or the decision to su bmi t the manuscript for publication . Results Twenty-eight physicians consented to participate , and 14 were r and omly allocated to each group . All completed their scenario . Their median age was 32.0 years ( interquartile range [ IQR ] , 8.5 years ) and their median time in practice since graduating was 6.0 years ( IQR , 6.5 years ) . Fifteen ( 53.6 % ) physicians had a background in critical care , 7 ( 25.0 % ) in internal medicine , and 6 ( 21.4 % ) in surgery . Sixteen ( 57.1 % ) were men and 12 were women . Demographic characteristics did not statistically significantly differ between the groups . Nine of the 14 physicians ( 64.3 % ) who were given the ratio-labeled ampules asked for an alternative , but no physician in the mass concentration group did so ( P < 0.001 , Fisher exact test ) . One participant from each group ( 8.3 % ) did not consult the protocol . The Appendix Table shows the dose given by each provider and time taken to administer it . Appendix Table .  Epinephrine Administration  , by Individual Providers * Dose of Epinephrine Administered Eleven of 14 ( 79 % ) providers in the mass concentration group calculated a dose within 10 % of that recommended by the protocol , compared with 2 ( 14 % ) in the ratio group ( P = 0.009 , chi-square test ) . All participants who gave the wrong dose of epinephrine  gave too much ; 1 participant gave 1 mg . The median dose given by providers using mass concentration was 122.5 g ( IQR , 120.0 to 125.0 g ) compared with 250.0 g ( IQR , 250.0 to 500.0 g ) for those using ratios ( P = 0.003 ) ( Figure ) . The risk for dose error was greater among providers using ratios ( odds ratio for error , 13.4 [ 95 % CI , 2.2 to 81.7 ] ) . Providers using ratio labels gave more epinephrine  ( adjusted mean , 213 g above target dose [ CI , 76.4 to 350.1 g ] ; P = 0.003 ) than those using mass concentration labels . Provider characteristics ( age , seniority , specialty , and sex ) were not associated with dosing errors ( data not shown ) . Figure . Dose and timing of epinephrine administration . Top . Dose of epinephrine . Bars indicate median doses ( 122.5 g [ IQR , 120.0 to 125.0 g ] in the mass concentration group vs. 250.0 g [ IQR , 250.0 to 500.0 g ] in the ratio group ; P = 0.003 ) ; 120 g was the correct dose . The adjusted mean difference in dose made by the ratio group was 213 g ( 95 % CI , 76.4 to 350.1 g ) greater than the 120-g target dose . Bottom . Time taken to give epinephrine . Bars indicate median times ( 35.5 seconds [ IQR , 27.0 to 65.0 seconds ] in the mass concentration group vs. 130.0 seconds [ IQR , 112.0 to 171.0 seconds ] in the ratio group ; P < 0.001 ) . The adjusted mean time was 91.0 seconds ( CI , 61.0 to 122.1 seconds ) greater in the ratio than in the mass concentration group . Time Taken to Administer  Epinephrine Physicians using ampules labeled with mass concentration calculated and administered the dose more quickly than those receiving epinephrine labeled as 1 mL of 1:1000 ( Figure ) . The median time taken to administer epinephrine  for the mass concentration group was 35.5 seconds ( IQR , 27.0 to 65.0 seconds ) compared with 130.0 seconds ( IQR , 112 WHAT IS KNOWN AND OBJECTIVE Medication errors ( ME ) in oncology are known to cause 
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Few demonstrated that simulation was more effective than didactic learning in reducing ME .
The performance of these programs depends on their ability to reflect reality and on professional guidance .
Properly regulated simulation is a good way to train staff in events that happen only exceptionally , as well as in st and ard daily activities .
By integrating human factors , simulation seems to be effective in preventing iatrogenic risk related to ME , if the program is well design ed