American Journal of Respiratory and Critical Care Medicine

Rationale: Little is known about the consequences of intensivists’ work schedules, or intensivist continuity of care.

Objectives: To assess the impact of weekend respite for intensivists, with consequent reduction in continuity of care, on them and their patients.

Methods: In five medical intensive care units (ICUs) in four academic hospitals we performed a prospective, cluster-randomized, alternating trial of two intensivist staffing schedules. Daily coverage by a single intensivist in half-month rotations (continuous schedule) was compared with weekday coverage by a single intensivist, with weekend cross-coverage by colleagues (interrupted schedule). We studied consecutive patients admitted to study units, and the intensivists working in four of the participating units.

Measurements and Main Results: The primary patient outcome was ICU length of stay (LOS); we also assessed hospital LOS and mortality rates. The primary intensivist outcome was physician burnout. Analysis was by multivariable regression. A total of 45 intensivists and 1,900 patients participated in the study. Continuity of care differed between schedules (patients with multiple intensivists = 28% under continuous schedule vs. 62% under interrupted scheduling; P < 0.0001). LOS and mortality were nonsignificantly higher under continuous scheduling (ΔICU LOS 0.36 d, P = 0.20; Δhospital LOS 0.34 d, P = 0.71; ICU mortality, odds ratio = 1.43, P = 0.12; hospital mortality, odds ratio = 1.17, P = 0.41). Intensivists experienced significantly higher burnout, work–home life imbalance, and job distress working under the continuous schedule.

Conclusions: Work schedules where intensivists received weekend breaks were better for the physicians and, despite lower continuity of intensivist care, did not worsen outcomes for medical ICU patients.

Clinical trial registered with (NCT01145443).

Scientific Knowledge on the Subject

Little is known about how intensivists’ work schedules, or intensivist continuity of care, impact outcomes for patients or the physicians.

What This Study Adds to the Field

Despite much lower continuity of care, weekend cross-coverage among intensivists improved their well-being without worsening patient outcomes. This information can assist and inform intensivists, hospital administrators, and policymakers in choosing a model for intensivist staffing.

Intensivists play an important role in modern health care; their involvement in the care of critically ill patients results in superior outcomes and cost effectiveness (13). Although the demand for intensive care unit (ICU) care is growing rapidly (4, 5), there is an increasing shortfall of intensivists (6). This is exacerbated when job burnout (7, 8) leads them to cease ICU work before retirement, or to retire early (912). In addition, the high work intensity and hours of intensivists inhibits new physicians from entering the field (13).

Thus, intensivists are a societal resource in increasingly short supply, and it is important to find ways to reduce the burden associated with this career choice. Modified work schedules may reduce burnout, and encourage intensivists to continue ICU work (12, 14). One strategy that might reduce job stress is reducing the number of consecutive days of ICU work by use of cross-covering physicians during weekends. However, cross-coverage decreases continuity of care, creating transitions that could be associated with worse outcomes. Indeed, Petersen and coworkers (15) found that potentially avoidable adverse events were associated with care by cross-covering residents.

The current study was motivated by a single-center pilot study showing that ICU weekend cross-coverage reduced burnout among intensivists without degrading patient outcomes (16, 17). If true, such scheduling would optimize both physician satisfaction and patient outcomes. Therefore, we performed a prospective, cluster-randomized study in five ICUs of two alternate intensivist staffing schedules based on half-month rotations, one where intensivists worked each day of the rotation versus working the weekdays only, with weekend care delivered by equivalently trained partners. Our objective was to determine whether outcomes for patients and intensivists differed between these staffing schedules. Some of the results of the current study has been previously reported in the form of an abstract (18).

Study Sites

The study was prospectively performed in five medical ICUs in four academic hospitals in the United States. All were 12- to 15-bed, closed-model ICUs, with multidisciplinary care teams including an internist board certified in critical care medicine (intensivist), internal medicine residents, and an ICU fellow. Intensivist group size varied from 6–19 members. Intensivists rounded daily with the multidisciplinary teams, were in the ICU or nearby throughout daytime hours every day, and took call overnight from home, returning to the ICU at their discretion. Internal medicine residents, in rotation, were continuously present overnight in the ICU. ICU fellows were present during the day and took home call overnight. Before the study, intensivists in all five ICUs attended in rotations of 14 days or a half-month; during the study, each site continued these schedules, which for simplicity we refer to as “half-month” rotations. All the sites had protocols for sedation and ventilator weaning, and all but one had computerized order entry. The size and structure of these units is similar to what has been described for high-intensity ICUs in the United States (19).

The study was conducted from July 2005 to September 2006. All sites received local Institutional Review Board approvals, with a waiver of consent. This study was registered (Clinical Identifier NCT01145443).


We compared two intensivist staffing schedules. In the continuous schedule (CS), a single intensivist was responsible every day of the half-month rotation. In the interrupted schedule (IS), a single intensivist was responsible Mondays to Fridays of the half-month, but each weekend was cross-covered by a different intensivist from the same pool of intensivist partners. Weekend-covering intensivists could have other non-ICU clinical responsibilities during the weekdays, but not over the weekends they covered the ICU. In both schedules intensivists took call overnight from home. The nature and details of hand-offs between intensivists were not proscribed, and left to usual local practice.

Each site conducted the study for 9 months divided into three equal phases; thus, each ICU alternated twice between the two staffing schedules (see Figure E1 in the online supplement) Sites were randomized between CS-IS-CS and IS-CS-IS patterns. Originally, seven ICUs agreed to participate and were randomized; however, two sites withdrew before beginning the study, but after it started at other sites. As a result, only the smallest of the five participating ICUs was randomized to CS for two of three study phases.

No other changes in ICU organization were made during the study. We assessed adherence to the assigned staffing schedule as the proportion of study days or half-month rotations in which a schedule deviation occurred, and the number of different intensivists who participated in care during each half-month rotation.

Participants and Data Collection

All patients admitted to participating ICUs during the study period were eligible for analysis. Sites prospectively collected data on all eligible patients. For clarity of interpretation, we excluded patients whose ICU admission included time under both staffing schedules. To avoid bias in mortality rates, repeat ICU admissions were excluded.

The physician participants were the primary intensivists on each half-month ICU rotation during the study. Using paper surveys provided 24–72 hours after each rotation ended, they identified their demographic information. Job burnout, job stress, and work–home life imbalance were measured using scales derived from the National Study of the Changing Workforce, a survey of United States workers performed by the Families and Work Institute, and formerly by the U.S. Department of Labor (20, 21). Intensivists providing weekend cross-coverage were not surveyed.

Study Outcomes

The two primary outcomes were defined a priori. The primary intensivist outcome was job burnout score; secondary outcomes were job stress and work–home life imbalance. The primary patient outcome was ICU length of stay (LOS); secondary outcomes were hospital LOS, ICU mortality, and hospital mortality.

Statistical Analyses

Sample size calculation, based on a single-center pilot study (17), indicated that 4,280 patients were needed to show an 8-hour difference in ICU LOS, with 80% power and a P value of 0.05. However, as discussed previously, only five of the original seven ICUs finally participated in the study.

Because cluster-randomization often lacks the excellent balancing between groups seen in individual-level randomization (22), we decided a priori that our primary analysis would be adjusted comparisons of outcomes using multivariable regression. We used logistic regression for mortality rates, median regression for LOS (23), and linear regression for intensivist job variables. Covariates included patient demographics, pre-ICU location, type and severity of acute illness, ICU workload on the day of admission, study site, and study phase. Demographics were age; sex; and race (categorized into white, African-American, and others). Pre-ICU location was categorized into the emergency department, other inpatient areas of the same hospital, outside hospitals, and other sources. ICU admission diagnosis was coded into eight categories: (1) respiratory, (2) cardiovascular, (3) gastrointestinal, (4) neurologic, (5) renal, (6) sepsis, (7) toxic and metabolic, and (8) miscellaneous. Severity of acute illness was measured by three parameters. First, the Glasgow Coma Scale (GCS) score (24), divided into categories: 3, 4–7, 8–13, 14, and 15. Second was the simplified acute physiology score (SAPS II) (25) excluding its age and neurologic components (ReducedSAPS), because those were separately included in the regressions. Both GCS and ReducedSAPS were taken, as usual, as the worst value in the initial 24 hours in the ICU. The third severity measure was whether the patient required invasive mechanical ventilation during the initial 24 hours in ICU (26). Two measures of ICU workload on the day of ICU admission were the number of patients admitted, and the daily census, averaged over four equally spaced times throughout the day. To assess for nonlinear relationships, continuous variables were represented as restricted cubic splines (23). We calculated standard errors via bootstrapping with 1,000 replications for median regression, and the robust sandwich estimator for logistic regression (27).

We analyzed intensivist survey variables using general estimating equations to account for individual intensivists completing multiple surveys, adjusted for study site and the two workload measures on the day of ICU admission.

Unless indicated, values are mean ± SD, or proportions. Unadjusted comparisons between groups used unpaired t test, Mann-Whitney U test, Fisher exact test, or Pearson chi-square test. Logistic models were assessed using the C statistic and the Hosmer-Lemeshow goodness-of-fit test (28). P values less than 0.05 were considered statistically significant. All analyses were done using Stata 11.0 (StataCorp, College Station, TX).

Study Cohort and Protocol Adherence

One of the five participating ICUs did not participate in the physician survey. During the study, 91 half-month rotations were completed, including 37 (40.7%) under continuous staffing. Because randomization occurred before dropout of two ICUs, the proportion of patients on each schedule was unbalanced (Table 1). Forty-five intensivists participated in the study; of the 39 intensivists who completed surveys, 12 cared for patients under CS only, 14 under IS only, and 13 under both staffing schedules.


DistributionInterrupted Staffing ScheduleContinuous Staffing ScheduleP Value
N (%)1,129 (59.4)771 (40.6)
Site, %<0.001
 Hospital A, ICU136.932.0
 Hospital B, ICU210.86.1
 Hospital C, ICU39.325.7
 Hospital D, ICU422.317.5
 Hospital D, ICU520.718.7
Study phase, %<0.001
Any weekend days in ICU, %
Number of weekend days in ICU (mean ± SD)1.6 ± 2.01.6 ± 1.70.83
Admitted in second half of half-month rotation, %50.952.50.51
Single intensivist during entire ICU stay, %37.971.5<0.0001
Number of intensivists during ICU stay
 Mean ± SD2.0 ± 1.21.3 ± 0.6
 Median (IQR)2 (1, 2)1 (1, 2)<0.0001

Definition of abbreviations: ICU = intensive care unit; IQR = interquartile range.

Over 1,361 study days, 97.1% were staffed according to the assigned schedule, including 93.3% of weekend days. Total or weekend day adherence did not differ between the two schedules (all days, 97.6% CS vs. 96.6% IS, P = 0.32; weekend days, 93.5% CS vs. 93.1% IS, P = 0.93). Of 92 half-month rotations, 71 (78%) were staffed according to assignment over the entire interval (74% IS vs. 84% CS, P = 0.26). The median number of intensivists per half-month rotation differed between the two staffing models (CS = 1 and IS = 3; P = 0.0001).

After exclusions (see Figure E2) there were 1,900 admissions analyzed for patient outcomes, of which 40.6% were treated under CS. The two groups were similar regarding weekend days in ICU, and admission during the first versus second half of the half-month intensivist rotations (Table 1). Continuity of care was higher under CS, with 72% of patients having a single intensivist caring for them during their entire ICU stay under CS, versus 38% under IS (P < 0.0001) (Table 1).

Patient Characteristics and Outcomes

Admitting diagnosis, pre-ICU location, and both workload measures differed slightly, but significantly, by staffing schedule (Table 2).


CharacteristicInterrupted Staffing ScheduleContinuous Staffing ScheduleP Value
Age56.5 ± 1755.7 ± 16.90.33
Sex, % males54.354.50.96
Race, %0.31
Pre-ICU location, %0.026
 Emergency department46.947.2
 Elsewhere in same hospital27.722.4
 Other hospital21.826.1
 Other sources3.54.3
ICU admission diagnosis group, %0.017
 Toxic or metabolic8.38.0
Glasgow Coma Scale score12.6 ± 3.712.8 ± 3.70.31
Mechanical ventilation on Day 1, %48.2049.70.54
SAPS II score39.5 ± 17.040.1 ± 17.70.49
ICU admissions on ICU admission day2.9 ± 1.42.7 ± 1.30.05
ICU census on ICU admission day9.7 ± 2.410.0 ± 2.50.01
Mortality rate, %
Length of stay, d, median (IQR)
 ICU2.42 (1.23–5.79)2.86 (1.40–6.06)0.10
 Hospital7.48 (3.75–15.56)7.56 (3.92–15.05)0.68

Definition of abbreviations: ICU = intensive care unit; IQR = interquartile range; SAPS = simplified acute physiology score.

Unadjusted LOS in ICU or hospital did not differ between the two intensivist schedules (Table 2). On multivariable analysis, GCS, use of mechanical ventilation on ICU Day 1, ReducedSAPS, ICU admission diagnosis, pre-ICU location, and ICU stay including any weekend time were significantly associated with both ICU and hospital LOS. Also, study site was associated with ICU LOS. After adjustment for covariates, the staffing schedule was not associated with differences in ICU or hospital LOS (Table 3, Table E1).


Continuous Compared with Interrupted Schedule
ParameterPoint Estimate95% Confidence IntervalP Value
ICU length of stay, median difference, d0.36−0.19 to 0.900.20
Hospital length of stay, median difference, d0.34−1.43 to 2.120.71
ICU mortality, odds ratio1.430.91 to 2.240.12
Hospital mortality, odds ratio1.170.80 to 1.720.41

Definition of abbreviation: ICU = intensive care unit.

Unadjusted ICU mortality was higher under continuous intensivist staffing; however, unadjusted hospital mortality was not statistically different (Table 2). In multivariable analysis, age, GCS, mechanical ventilation, ReducedSAPS, admission diagnosis, and pre-ICU location were significant covariates. After adjustment there were no significant differences in ICU or hospital mortality between the two staffing schedules (Table 3, Table E2). The ICU and hospital mortality models exhibited good discrimination (C statistic 0.860 and 0.832, respectively) and calibration (Hosmer-Lemeshow goodness-of-fit P values 0.53 and 0.27, respectively).

In addition, we performed two types of sensitivity analyses for these four regression models. First, we included two variables addressing exposure to the intervention: whether the ICU stay included any weekend days, and ICU admission during the first versus second half of the half-month rotation. Second, we included only the 1,275 patients whose ICU time included any weekend days. In both of these subsidiary analyses, as in the main analyses, there were no significant differences between the two intensivist staffing models for LOS or mortality rates.

Physician Outcomes

Thirty-nine intensivists completed surveys after 69 half-month rotations, with 29 (42%) from physicians doing continuous staffing. Two-thirds of physicians submitted surveys from working under a single schedule type (IS or CS), whereas one-third were surveyed after both. The intensivists surveyed were predominantly male (76%), married (87%), with children living at home (68%). On average, they were 41 ± 6 years old, had been in independent practice for 8 ± 6 years, and in their current jobs for 5 ± 5 years. Family and job characteristics for physicians responding to surveys did not differ between staffing schedules. Unadjusted survey responses demonstrated higher burnout and work–home life imbalance under continuous staffing. After adjustment and clustering by physician, intensivists working continuously for half-month rotations had significantly higher burnout, work–home life imbalance, and job distress than did those working with weekend cross-coverage (Table 4, Table E3).


ParameterInterrupted ScheduleContinuous ScheduleP Value
Burnout, raw value (range 5–25)12.35 ± 4.5415.40 ± 4.460.007
 Adjusted difference, mean (95% CI)2.77 (0.97–4.58)0.003
Work-home life imbalance, raw value (range 2–10)5.60 ± 1.816.72 ± 2.240.024
 Adjusted difference, mean (95% CI)1.02 (0.10–1.93)0.029
Job distress, raw value (range 6–30)13.36 ± 3.4014.64 ± 4.090.16
 Adjusted difference, mean (95% CI)1.52 (0.83–2.22)<0.0001

Definition of abbreviation: CI = confidence interval. Differences are continuous minus interrupted schedule values.

Although ICUs exist to serve the needs of critically ill patients, there are other stake-holders in how they are run, including intensivists (29). This is of growing relevance, because intensivists are in increasingly short supply (6), but suffer from substantial job distress (7, 8) that reduces their numbers through premature attrition (9), and by driving trainees away from the field (13). Accordingly, it is important to find ways to reduce the burdens associated with this career choice, while not adversely affecting the patients. Changing the way intensivists organize themselves to provide ICU care is one of the most apparent modifiable features of ICU structure. Assessing the consequences of changes in ICU structures and processes mandates no less rigorous study than is expected for the technical aspects of care (30).

Our study of intensivists working in ICUs in half-month rotations compared limiting them to 5 consecutive days of ICU responsibility, versus working every day of the half-month. Despite much lower continuity of care with weekend cross-coverage, the interrupted schedule staffing model was better for the intensivists and was not associated with worse outcomes for patients. Although this finding challenges conventional wisdom, it does not contradict existing knowledge. Research showing better outcomes with higher intensity of intensivist involvement has not addressed continuity of care (1). Studies demonstrating problems related to signovers, a consequence of discontinuity of care, have used subjective assessment of outcomes, or surrogate outcomes, and did not study ICU care (15, 31). Indeed, a study of inpatient medical ward care found no differences in objectively measured outcomes associated with a staffing intervention that produced substantially different levels of staff physician continuity over weekends (32).

Because of dropout of two randomized ICUs, and lower than expected ICU admission rates, our final patient sample size was only 44% of that derived from our power calculation. Thus, the null findings on patient outcomes (Table 3) could be caused by inadequate sample size. However, the findings of the current study are similar to those of a prior single-center pilot study (16, 17). The point estimates from both studies showed patients had longer LOS and higher mortality rates when intensivists worked without a break; although not statistically significant in either study, the consistency of these findings raises the possibility that continuous intensivist staffing might be worse for patients, which our study could not discern because it was inadequately powered. Thus, although our study does not eliminate the possibility of better patient outcomes under intensivist staffing schedules with fewer consecutive days of ICU work, and concomitantly lower continuity of care, it does provide good evidence that such staffing is not worse for the patients.

Plausible explanations exist for better outcomes with cross-covered intensivist staffing. Less physician burnout may directly improve outcomes. Job burnout among physicians is associated with errors (33, 34). Factors known to increase job stress, such as workload and work duration, are associated with worse patient outcomes (35, 36). In addition, a “fresh pair of eyes” might see clinical problems in new ways that improve outcomes.

Our study has additional limitations. First, we did not measure handoff adequacy or patient safety events that might mediate effects of our intervention. Second, this study was performed in academic ICUs with the daily presence of intensivists and multidisciplinary teams, and these results may not generalize to other practice environments. For example, the results could be different regarding continuity among nonintensivists in ICUs that are “open” or have low-intensity intensivist staffing (1). In addition, multidisciplinary teams or around-the-clock presence of housestaff in these ICUs may have limited detrimental effects of reduced intensivist continuity of care. Third, we did not assess other outcomes that might differ between the two staffing schedules, including those for cross-covering intensivists; satisfaction and perceptions of patients, families, and nurses; delays in family counseling or end-of-life decision making; volume of diagnostic testing; and complications or costs of care. Finally, we do not know how many ICUs use half-month or 2-week rotations, and we cannot directly apply our findings to other models of intensivist staffing. Although a bibliographic search did not identify any surveys assessing the duration of intensivists’ rotations, presently the participating ICUs continue to use the same rotations. This final limitation, relating to generalizability, is a problem inherent to all studies of healthcare organization (i.e., they are tied to the specific structures being studied). However, we believe that our findings can be interpreted as speaking more generally to notions related to continuity of intensivist care. Additional rigorously performed studies are needed to clarify the optimal way to organize ICU care, including intensivist staffing.

Our study's strengths are a multicenter design with an alternating intervention and rigorous analytical methods. Adherence to the staffing schedules was excellent, providing a distinct contrast in intensivist continuity. The alternating design obviates weaknesses of historical controls inherent in before versus after studies that comprise most previous literature on organization elements in health care.

We report a randomized, multicenter trial of intensivist scheduling in ICUs. Although attention to the potential for errors with handoffs (37, 38) has produced calls to maintain continuity of care (39, 40), we found that weekend cross-coverage for intensivists reduced their job stress and was not associated with harm to patients. This information is relevant to ICU clinicians, hospital administrators, and policymakers.

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Correspondence and requests for reprints should be addressed to Allan Garland, M.D., M.A, Winnipeg Health Sciences Center, 820 Sherbrook Street, Room GF-222, Winnipeg, MB, R3A 1R9 Canada. E-mail:

Author contributions: Conception and design, N.A.A., K.M.W., J.H., S.P.H., M.R., E.W., and A.G. Acquisition of data: N.A.A., K.M.W., J.H., S.P.H., and A.G. Analysis and interpretation of data, N.A.A., G.S.P., J.M.O., and A.G. Drafting of the manuscript, N.A.A., J.M.O., and A.G. Critical revision of the manuscript for intellectual content, N.A.A., K.M.W., J.H., S.P.H., J.M.O., G.S.P., M.R., E.W., and A.G. Statistical analysis, N.A.A., G.S.P., J.M.O., and A.G. Administrative, technical, or material support, K.M.W., J.H., S.P.H., and A.G. Supervision, N.A.A., S.P.H., K.M.W., J.H., and A.G.

This article has an online supplement, which is accessible from this issue's table of contents at

Originally Published in Press as DOI: 10.1164/rccm.201103-0555OC on June 30, 2011

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