***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 
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    Input: Context Studies of  resident work-hour restrictions and patient outcomes  have had design limitations and inconsistent findings . Contribution This study compared changes in the rates of 7 clinical measures over a 2-year period for patients discharged from a teaching service that followed the ACGME work-hour rules to changes for patients discharged from a nonteaching hospitalist service . Favorable changes in rates of intensive care unit utilization , discharge to home or a rehabilitation facility , and pharmacist interventions to prevent drug error were more marked in the teaching service than in the hospitalist service . Caution Without a direct comparison of teaching services with and without restricted hours , this study has similar design limitations as those of previous studies . The Editors Work-hour regulations , implemented in July 2003 by the Accreditation Council for Graduate Medical Education ( ACGME ) ( 1 ) , have reportedly reduced housestaff fatigue ( 2 ) , but often at the cost of increased transfers of patient care among residents ( 3 ) . Each transfer of care requires the communication of patient information from the departing clinician to the arriving clinician . If this sign-out is performed imperfectly , with misunderst and ing or loss of information , harm to patients may result ( 412 ) . These risks of increased h and offs may mitigate the expected benefits of reduced housestaff fatigue , result ing in an uncertain net result for patients . Literature on the impact of work-hour limits on patient outcomes is conflicting and has been hampered by small sample sizes , few clinical outcomes , and design limitations ( 13 ) . Only 3 studies have included a control group to account for temporal trends in quality improvement ( 1416 ) . No study of the new ACGME regulations has included patients in an internal medicine ward , a high-volume group of complex patients . Given the expense of this policy change ( 17 ) , its broad effects on residency programs and residents ( 2 ) , the statement by the ACGME that improving patient care was a major impetus for the regulations ( 18 ) , and the lack of conclusive study before its wholesale enactment ( 13 ) , the impact of the new work-hour regulations on patient outcomes is critical to evaluate . R and omized trials are not feasible because the change was m and ated simultaneously for all residency programs . A simple comparison of patient outcomes in different years is subject to bias , however , because of changes in practice and quality of care over time . Lack of control for these temporal trends in outcomes is perhaps the most important limitation of most previous studies . To avoid this problem , we compared changes over time in outcomes of 2 cohorts at the same hospital , one cared for by housestaff ( teaching service ) and the other by hospitalists ( nonteaching service ) . This approach allowed us to evaluate the association of work-hour regulations with changes in a broad range of outcomes for internal medicine in patients while controlling for temporal trends by using a concurrent control group of similar patients whose caregivers were not directly affected by work-hour regulations . Methods We conducted a retrospective cohort study at YaleNew Haven Hospital , comparing outcomes before and after work-hour regulations in medical patients receiving care by housestaff and those receiving care by hospitalists . Patients were assigned to the  teaching or nonteaching services  on the basis of time of day . Each day , admitted patients were first assigned to teaching teams until the team caps were reached , regardless of severity of illness . All subsequent admissions for the day were assigned to the nonteaching service . This policy was consistent throughout the study . Of note , patients transferred out of the intensive care unit ( ICU ) were usually assigned to teaching teams . Transfers between teaching and nonteaching services were unusual . Teaching System before Work-Hour Regulation A team comprised 1 resident ( postgraduate year 2 or 3 ) and 2 interns . Before 1 July 2003 , the resident and 1 intern remained in the hospital overnight on call every fourth day , during which they cared for their own patients and briefly for those of 1 other team . A resident on night-float service arrived at 8 p.m. to assume care of the patients not on the on-call intern 's team . On days when no one from the team was on call , interns signed their patients out to a different team 's on-call intern , who then relinquished them to the resident on night-float service at 8 p.m. Over 4 weekdays , a patient typically experienced 8 transfers of care .  Teaching System after Work-Hour Regulation On 1 July 2003 , the teaching service schedule was reorganized to better comply with work-hour limitations . There was no transition period . Residents no longer stayed overnight ; they were replaced by nocturnalistsnonresident physicians who did the work of the night resident . This position was filled by 2 hospitalists and a large pool of moonlighting fellows . In addition , a resident on day-float service was instituted to assist with postcall care of patients so that the postcall team could leave by noon . This reorganization added 1 extra transfer of care every 4 days and increased discontinuity because of the large number of rotating nocturnalists , the new resident on day-float service , and the absence of an on-call primary resident at night . The average patient had approximately 2 physicians added to the care team ; patients with long lengths of stay saw a much greater increase . However , these changes also increased the average clinical experience of those supervising nighttime patient care because all nocturnalists had completed residency . Intermittent checks of time cards completed by housestaff showed that average weekly hours were within the 80-hour limits . No physician extenders were added to reduce housestaff workload , and housestaff on the wards was not extended beyond the addition of the resident on day-float service . Nonteaching System The nonteaching service did not change after work-hour regulation . The primary hospitalist team for each patient ( comprising a physician and 1 or more physician assistants ) was present during the day . Each night , including weekends , night staff was present in the hospital for coverage of the nonteaching service . Night physicians attempted to maintain continuity by covering the same patients each night , but this was not universally achieved . Day staff signed out directly to night staff every day of the week . Over 4 days , a patient typically experienced 8 transfers of care . In the year after work-hour regulations were enacted , the nonteaching service increased in both volume and number of providers , such that the number of patients per provider remained similar . ( The Appendix contains full details of work schedules before and after work-hour regulation on both services . ) Data Sources We obtained administrative cl aims data for all patients discharged from the medical wards between 1 July 2002 and 30 June 2004 , excluding patients discharged from HIV and oncology wards , which were restricted to teaching service teams . We derived medication error data from 2 data bases kept by the hospital pharmacy . One contained all automatically generated warnings of drugdrug combinations with potential for harm . The interaction list was dynamic : 53 % of the interactions ( 323 of 615 ) were added on or after 1 July 2003 . The other pharmacy data base recorded all direct interventions made by pharmacy staff . Pharmacists themselves generated each intervention and categorized the intent of the intervention . For this study , we restricted the data base to include only those interventions made to prevent an adverse event . Independent Variables Patients were stratified into the teaching or nonteaching cohorts on the basis of their team assignment at discharge . The unit of analysis was hospitalization ; patients admitted more than once could be included in more than 1 cohort . We collected data on age , sex , race or ethnicity , insurance status , and admission source for each patient . To account for variability in case mix over time , we grouped the principal diagnosis codes into 259 clinical ly similar diagnosis categories by using the Clinical Classifications Software categorization ( 19 ) and then constructed a case-mix variable that included the most common or severe 21 diagnoses plus 1 for all other diagnoses . We used the International Classification of Diseases , Ninth Revision , Clinical Modification ( ICD-9-CM ) , secondary diagnosis codes to assign a risk severity score to each patient by using the Deyo adaptation of the Charlson comorbidity index ( 20 , 21 ) . Analyses using the Elixhauser method of comorbidity adjustment yielded similar results ( 22 ) . Dependent Variables Outcome measures were ICU stay , length of hospital stay , discharge disposition , 30-day readmission rate to YaleNew Haven Hospital , pharmacist interventions to prevent adverse events , and  drugdrug interactions . We dichotomized discharge disposition as discharge to home or rehabilitation facility versus discharge elsewhere ( including death ) , and we included only patients admitted from home or through the emergency department for analysis of this outcome . We also evaluated in-hospital death , but this was an exploratory analysis because of the small number of events . Statistical Analysis Because this was a retrospective , single-center study , our sample size was determined by hospital volume . We compared patients ' characteristics and outcomes before and after work-hour regulation within each group and between groups by using chi-square tests for categorical variables and t tests for continuous variables . We used the generalized linear model for length of stay , which has a long right tail . After testing several link functions and distributional assumptions , we found that a distribution with a logarithmic link ( regression ) best fit the data . For pharmacy interventions and medication interactions , we constructed BACKGROUND Long work hours and work shifts of an extended duration ( > or = 24 hours ) remain a hallmark of medical education in the United States . Yet their effect on health and safety has not been evaluated with the use of vali date d measures . METHODS We conducted a prospect i ve nationwide , Web-based survey in which 2737 residents in their first postgraduate year ( interns ) completed 17,003 monthly reports that provided detailed information about work hours , work shifts of an extended duration , documented motor vehicle crashes , near-miss incidents , and incidents involving involuntary sleeping . RESULTS The odds ratios for reporting a motor vehicle crash and for reporting a near-miss incident after an extended work shift , as compared with a shift that was not of extended duration , were 2.3 ( 95 percent confidence interval , 1.6 to 3.3 ) and 5.9 ( 95 percent confidence interval , 5.4 to 6.3 ) , respectively . In a prospect i ve analysis , every extended work shift that was scheduled in a month increased the monthly risk of a motor vehicle crash by 9.1 percent ( 95 percent confidence interval , 3.4 to 14.7 percent ) and increased the monthly risk of a crash during the commute from work by 16.2 percent ( 95 percent confidence interval , 7.8 to 24.7 percent ) . In months in which interns worked five or more extended shifts , the risk that they would fall asleep while driving or while stopped in traffic was significantly increased ( odds ratios , 2.39 [ 95 percent confidence interval , 2.31 to 2.46 ] and 3.69 [ 95 percent confidence interval , 3.60 to 3.77 ] , respectively ) . CONCLUSIONS Extended- duration work shifts , which are currently sanctioned by the Accreditation Council for Graduate Medical Education , pose safety hazards for interns . These results have implication s for medical residency programs , which routinely schedule physicians to work more than 24 consecutive hours OBJECTIVES To inform the debate over whether human sleep can be chronically reduced without consequences , we conducted a dose-response chronic sleep restriction experiment in which waking neurobehavioral and sleep physiological functions were monitored and compared to those for total sleep deprivation . DESIGN The chronic sleep restriction experiment involved r and omization to one of three sleep doses ( 4 h , 6 h , or 8 h time in bed per night ) , which were maintained for 14 consecutive days . The total sleep deprivation experiment involved 3 nights without sleep ( 0 h time in bed ) . Each study also involved 3 baseline ( pre-deprivation ) days and 3 recovery days . SETTING Both experiments were conducted under st and ardized laboratory conditions with continuous behavioral , physiological and medical monitoring . PARTICIPANTS A total of n = 48 healthy adults ( ages 21 - 38 ) participated in the experiments . INTERVENTIONS Noctumal sleep periods were restricted to 8 h , 6 h or 4 h per day for 14 days , or to 0 h for 3 days . All other sleep was prohibited . RESULTS Chronic restriction of sleep periods to 4 h or 6 h per night over 14 consecutive days result ed in significant cumulative , dose-dependent deficits in cognitive performance on all tasks . Subjective sleepiness ratings showed an acute response to sleep restriction but only small further increases on subsequent days , and did not significantly differentiate the 6 h and 4 h conditions . Polysomnographic variables and delta power in the non-REM sleep EEG-a putative marker of sleep homeostasis -- displayed an acute response to sleep restriction with negligible further changes across the 14 restricted nights . Comparison of chronic sleep restriction to total sleep deprivation showed that the latter result ed in disproportionately large waking neurobehavioral and sleep delta power responses relative to how much sleep was lost . A statistical model revealed that , regardless of the mode of sleep deprivation , lapses in behavioral alertness were near-linearly related to the cumulative duration of wakefulness in excess of 15.84 h ( s.e . 0.73 h ) . CONCLUSIONS Since chronic restriction of sleep to 6 h or less per night produced cognitive performance deficits equivalent to up to 2 nights of total sleep deprivation , it appears that even relatively moderate sleep restriction can seriously impair waking neurobehavioral functions in healthy adults . Sleepiness ratings suggest that subjects were largely unaware of these increasing cognitive deficits , which may explain why the impact of chronic sleep restriction on waking cognitive functions is often assumed to be benign . Physiological sleep responses to chronic restriction did not mirror waking neurobehavioral responses , but cumulative wakefulness in excess of a 15.84 h predicted performance lapses across all four experimental conditions . This suggests that sleep debt is perhaps best understood as result ing in additional wakefulness that has a neurobiological " cost " which accumulates over time CONTEXT Sleep deprivation is associated with increased risk of serious medical errors and motor vehicle crashes among interns . The Accreditation Council for Graduate Medical Education ( ACGME ) introduced duty-hour st and ards in  
    Output:
    
Studies evaluating the impact of these regulations on resident physicians have generated conflicting reports on patient outcomes , demonstrating only a modest increase in sleep duration for resident physicians , along with negative perceptions regarding their education .