Flow diagram of patients into the study. OB indicates obstetric; Neuro, neurological.
Customize your JAMA Network experience by selecting one or more topics from the list below.
Kim MM, Barnato AE, Angus DC, Fleisher LF, Kahn JM. The Effect of Multidisciplinary Care Teams on Intensive Care Unit Mortality. Arch Intern Med. 2010;170(4):369–376. doi:10.1001/archinternmed.2009.521
Copyright 2010 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.2010
Critically ill patients are medically complex and may benefit from a multidisciplinary approach to care.
We conducted a population-based retrospective cohort study of medical patients admitted to Pennsylvania acute care hospitals (N = 169) from July 1, 2004, to June 30, 2006, linking a statewide hospital organizational survey to hospital discharge data. Multivariate logistic regression was used to determine the independent relationship between daily multidisciplinary rounds and 30-day mortality.
A total of 112 hospitals and 107 324 patients were included in the final analysis. Overall 30-day mortality was 18.3%. After adjusting for patient and hospital characteristics, multidisciplinary care was associated with significant reductions in the odds of death (odds ratio [OR], 0.84; 95% confidence interval [CI], 0.76-0.93 [P = .001]). When stratifying by intensivist physician staffing, the lowest odds of death were in intensive care units (ICUs) with high-intensity physician staffing and multidisciplinary care teams (OR, 0.78; 95% CI, 0.68-0.89 [P < .001]), followed by ICUs with low-intensity physician staffing and multidisciplinary care teams (OR, 0.88; 95% CI, 0.79-0.97 [P = .01]), compared with hospitals with low-intensity physician staffing but without multidisciplinary care teams. The effects of multidisciplinary care were consistent across key subgroups including patients with sepsis, patients requiring invasive mechanical ventilation, and patients in the highest quartile of severity of illness.
Daily rounds by a multidisciplinary team are associated with lower mortality among medical ICU patients. The survival benefit of intensivist physician staffing is in part explained by the presence of multidisciplinary teams in high-intensity physician-staffed ICUs.
More than 4 million intensive care unit (ICU) admissions occur annually in the United States.1 These patients are often at high risk of death: mortality for critical illness syndromes such as acute lung injury and sepsis ranges from 25% to 50%, and 20% of Americans die while receiving intensive care services.2-5 One approach to lowering ICU mortality is to optimize the organization of ICU services.6 For example, a large body of literature indicates that the presence of trained intensivist physicians is associated with improved survival,7 leading many policy makers to call for expansion of the intensivist-led model of critical care.8 Unfortunately, there are not enough trained intensivists to meet either current or future demand, and only a minority of ICUs are currently staffed in this manner.9,10
A potential complement to intensivist staffing is a multidisciplinary care model in which physicians, nurses, respiratory therapists, clinical pharmacists, and other staff members provide critical care as a team. A multidisciplinary approach acknowledges the complexities of modern critical care and the important role of communication between health care providers in delivering comprehensive care. Such a model is endorsed by the Society of Critical Care Medicine and the American Association of Critical Care Nurses.11,12 Yet, unlike intensivist physician staffing, little research has systematically evaluated the relationship between multidisciplinary care and outcomes, and there are few data to justify widespread adoption of this approach. Existing studies are generally single center in nature with limited ability to adjust for variations in case-mix or temporal trends between periods.13-15
The objective of our study was to determine the independent effect of multidisciplinary care teams on the mortality of critically ill patients, using a multicenter hospital-level organizational survey and patient-level outcomes data. We also sought to determine the interaction between multidisciplinary care teams and intensivist physician staffing to see if part of the benefit of intensivist staffing could be explained by multidisciplinary care. We hypothesized that multidisciplinary care teams would be associated with improved critical care survival, particularly in settings without high-intensity physician staffing.
We conducted a retrospective cohort study using state discharge data from the Pennsylvania Health Care Cost Containment Council (PHC4). The PHC4 collects clinical and administrative data on all patients discharged from nonfederal hospitals within the Commonwealth of Pennsylvania. All discharges between July 1, 2004, and June 30, 2006, were eligible for the analysis. We excluded pediatric hospitals, rehabilitation hospitals, long-term acute care hospitals, and specialty surgery hospitals. Patient level data were linked to the Pennsylvania Department of Health's death records to obtain each patient's vital status at 30 days after admission. Hospital characteristics were obtained from the hospital-level data file maintained by the PHC4 and the 2005 American Hospital Association Annual Survey.
Data on ICU care models were obtained from a cross-sectional, mixed-mode organizational survey of Pennsylvania hospitals.16 The survey was conducted between June 1, 2005, and May 31, 2006, and completed by each hospital's chief nursing officer. A total of 118 hospitals completed the survey (69.8%). Four hospitals completed the survey but did not respond to questions about ICU care models, resulting in 114 hospitals with complete responses. Responding and nonresponding hospitals were similar in bed size, community size, teaching status, and other key characteristics.16 All questions about ICU structure and organization were specific to the hospital's single ICU that treats the majority of adult, noncardiac, nonsurgical patients. Consequently, this analysis was restricted to medical patients and the single ICU in each hospital that primarily served those patients, typically either a medical or mixed medical-surgical ICU.
We identified patients admitted to an ICU using revenue codes specific to intensive care. We excluded patients younger than 18 years at the time of admission and patients in hospitals who did not fully respond to the survey. In addition, because we only had organizational data on the single, primary noncardiac nonsurgical ICU at each hospital, we excluded patients with a primary cardiac, surgical, or neurological diagnosis as defined by International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) discharge codes and discharge diagnosis related groups. Because the discharge data do not specify the actual admission ICU, for hospitals with more than 1 ICU (27.7% of total) it is possible that some excluded patients were actually admitted to the ICU of interest. To evaluate for possible selection bias, we compared the mortality of excluded patients in hospitals with the different types of multidisciplinary care models described in the following subsection.
The primary exposure of interest was each hospital's response to the question: “Does the ICU have daily multidisciplinary ICU rounds consisting of the physician, nurse, and other health care professionals (eg, social worker, respiratory therapist, pharmacist)?” This response was coded as either yes or no. Each study ICU operated under a single care model. We did not have more detailed information on the exact components of the multidisciplinary team or the training of the physician that directed rounds. The secondary exposure of interest was each ICU's physician staffing model. Physician staffing models were reported in the survey as no intensivist, optional intensivist consult, mandatory intensivist consult, and primary intensivist management. These groups were further categorized into high-intensity (mandatory consult or primary intensivist management) and low-intensity (optional intensivist consult or no intensivist) physician staffing, according to prior reports.7
We also sought to evaluate the relationship between multidisciplinary care and intensivist physician staffing with respect to their effect on mortality. We created the following 4 groups of hospitals based on their combination of multidisciplinary care and physician staffing models: (1) low-intensity staffing without multidisciplinary care teams; (2) low-intensity staffing with multidisciplinary care teams; (3) high-intensity staffing with multidisciplinary care teams; and (4) high-intensity staffing without multidisciplinary care teams. We excluded hospitals in the last group (high-intensity staffing without multidisciplinary care teams) because there were not enough hospitals to accurately estimate outcomes in that category.
The primary outcome variable was mortality within 30 days of hospital admission. We controlled for potential confounding variables that could be related to the multidisciplinary care teams, physician staffing model, and mortality. Risk-adjustment variables were selected a priori and included age, sex, admission source (emergency department, interhospital transfer, or direct), chronic conditions as defined by Elixhauser comorbidities modeled as indicator covariates, ventilation status on admission as defined by ICD-9-CM procedure codes, primary diagnosis as defined by ICD-9-CM diagnosis codes, hospital teaching status as determined by each hospital's resident to bed ratio (nonteaching status: ratio, 0; small teaching: ratio, >0 to 0.2; large teaching status: ratio, >0.2), ICU type (medical, mixed medical-surgical, or mixed medical-coronary), region of Pennsylvania as defined by the PHC4, and each hospital's mean annual admission volume.17-20 We further controlled for severity of illness using the MediQual Atlas probability of in-hospital death, a validated risk-adjustment tool for hospitalized patients using key clinical and demographic variables measured on admission.21 Reported areas under the curve for MediQual Atlas mortality prediction in medical patients range from 0.837 to 0.874, which are comparable to other common ICU risk-adjustment systems.22,23 The MediQual Atlas score is automatically calculated by PHC4 on patients admitted to Pennsylvania hospitals but may be absent due to missing clinical data.
We compared descriptive statistics for hospitals and patients by care model group using the χ2 test or the t test, as appropriate. To determine the independent effect of multidisciplinary care and high-intensity physician staffing on 30-day mortality, we created patient-level multivariate logistic regression models controlling for potential confounders described in the preceding subsection. We modeled categorical variables using indicator covariates and continuous variables using quadratic splines. We created 3 separate models: a model with multidisciplinary care teams alone (model 1), a model with physician staffing alone (model 2), and a model with the grouped multidisciplinary care team/physician staffing variable (model 3). The last model was designed to evaluate the interaction between high-intensity physician staffing and multidisciplinary care, given that we could not control for both in a single multivariate model. In all models we used generalized estimating equations with robust Huber-White confidence intervals (CIs) to account for potential clustering within hospitals.24 We assessed model discrimination using the C statistic. We also performed 3 prospectively defined subgroup analyses to examine the effects of staffing models on high-risk patients. Subgroups of interest were patients in the top quartile of the MediQual Atlas score, patients receiving invasive mechanical ventilation as defined by ICD-9-CM procedure code, and patients with severe sepsis as defined using previously validated criteria.2,25
To account for missing MediQual Atlas scores we performed multiple imputation using Markov Chain Monte Carlo simulation, creating 10 imputed data sets and combing regression results according to a previously described method.26,27 We also performed a sensitivity analysis, dropping patients with missing MediQual Atlas scores under the assumption that the data are missing completely at random (ie, purely for administrative rather than clinical reasons).28 We analyzed only the complete cases for the subgroup of patients in the highest quartile of MediQual Atlas score.
The multiple imputation was performed with SAS 9.2 (SAS Institute Inc, Cary, North Carolina). Other statistical analyses were performed with Stata 10.0 (StataCorp, College Station, Texas). All tests were 2 tailed, and P ≤ .05 was considered significant. This research was approved by the institutional review boards of the University of Pennsylvania and the University of Pittsburgh.
A total of 471 112 patients were admitted to Pennsylvania hospital ICUs during the study period (Figure). We excluded 55 hospitals with survey nonresponse or incomplete response, and 2 hospitals with high-intensity physician staffing and no multidisciplinary care teams. The further exclusion of patients with nonmedical diagnoses resulted in 112 hospitals and 107 324 patients in the final analysis. The care model in the ICU of interest was low-intensity staffing + no multidisciplinary care in 54 hospitals (48.2%); low-intensity staffing and multidisciplinary care in 36 hospitals (32.1%); and high-intensity staffing + multidisciplinary care in 22 hospitals (19.6%). Among excluded patients, mortality was similar between the different staffing groups (low-intensity staffing + no multidisciplinary care, 8.0%; and low-intensity staffing + multidisciplinary care, 9.3%; and high-intensity staffing + multidisciplinary care, 8.7%).
Hospital characteristics are given in Table 1. High-intensity physician staffing and multidisciplinary care teams were more common in teaching hospitals and hospitals with critical care fellowships. High-intensity physician staffing and multidisciplinary care teams were also more common in large hospitals and hospitals with a high volume of annual admissions. In hospitals with high-intensity staffing, the ICU of interest tended to be a medical specialty ICU, compared with hospitals with low-intensity staffing, where the ICU of interest tended to be a mixed medical-surgical or mixed medical-cardiac ICU. High-intensity physician-staffed ICUs also tended to be larger than low-intensity staffed ICUs.
Patient demographics were generally similar between groups (Table 2). Patients in ICUs with high-intensity physician staffing and multidisciplinary care were more likely to require mechanical ventilation, were more likely to carry a diagnosis of sepsis, and had a higher probability of in-hospital death. Accordingly, unadjusted in-hospital mortality was higher in ICUs with high-intensity physician staffing and multidisciplinary care teams (16.4%) compared with hospitals with low-intensity staffing and multidisciplinary care teams (13.9%) and low-intensity staffing without multidisciplinary care teams (11.2%).
In the primary analysis all multivariate models had C statistic values of 0.85 or greater. Controlling for hospital and patient characteristics and accounting for clustering by center, but not accounting for intensivist staffing, multidisciplinary care teams were associated with a 16% reduction in the odds of death (odds ratio [OR], 0.84; 95% CI, 0.76-0.93 [P = .001]) (Table 3). High-intensity physician staffing alone was associated with a similar reduction in the odds of death (OR, 0.84; 95% CI, 0.75-09.4 [P = .002]). When we simultaneously evaluated multidisciplinary care teams and high-intensity physician staffing in a stratified model, the lowest odds of death were in ICUs with both high-intensity physician staffing and multidisciplinary care teams (OR, 0.78; 95% CI, 0.68-0.89 [P < .001]), followed by ICUs with multidisciplinary care teams and low-intensity physician staffing (OR, 0.88; 95% CI, 0.79-0.97 [P = .01]), compared with hospitals without either multidisciplinary care teams or low-intensity staffing.
In the subgroup analyses, C statistic values ranged from 0.71 to 0.78. Results were similar in the 3 planned subgroup analyses, with significant mortality reductions observed with multidisciplinary care teams and high-intensity physician staffing in patients with sepsis, patients requiring mechanical ventilation, and patients in the highest quartile of severity of illness (Table 4). Odds ratios from the complete case analyses excluding the 21 038 patients with missing MediQual Atlas scores (19.6% of total) scores were all within 0.01 of the ORs from the multiple imputation analyses, with similar 95% CIs.
In a large population-based sample of hospitals, daily rounds by a multidisciplinary care team were independently associated with lower mortality in ICU patients. In a stratified model that included intensivist physician staffing, multidisciplinary care was associated with a significant mortality reduction in ICUs with low-intensity physician staffing, conveying a decreased risk of death that approached, but did not equal, ICUs with high-intensity physician staffing. These results suggest that in hospitals without high-intensity physician staffing multidisciplinary rounds are likely to improve patient outcomes.
Several mechanisms may explain these findings. Multidisciplinary rounds may facilitate implementation of best clinical practices such as evidence-based treatments for acute lung injury, sepsis, and prevention of ICU complications.29-31 Pharmacist participation on rounds is associated with fewer adverse drug events32 and alone may be associated with lower mortality among ICU patients.33 Multidisciplinary rounds may also improve communication between health care providers.34 Communication may facilitate implementation of respiratory therapy and nurse-driven protocols for weaning and sedation, which can reduce duration of mechanical ventilation and shorten ICU length of stay.35,36
Our findings have important implications for the organization of critical care services. First, this study provides empirical evidence to support a multidisciplinary model of critical care. Based on these results and expert opinion voiced in consensus guidelines, it is reasonable for hospitals to implement routine multidisciplinary rounds when staffing capabilities allow.11 In addition, our results provide insight into ways to improve mortality in ICUs without intensivist physician staffing. Workforce analyses suggest that there are not enough intensivists to meet demand, and as a consequence only a minority of ICUs in the United States are staffed by trained intensivists.9,10 Directors of ICUs report that lack of enough trained of intensivists is a key barrier to implementing an intensivist model of care.37 Our study shows that hospitals without the ability to implement high-intensity physician staffing can still achieve significant mortality reductions by implementing a multidisciplinary, team-based approach.
Our results also confirm prior studies showing that high-intensity physician staffing lowers mortality in the ICU. Several cohort studies indicate that intensivist-led critical care is associated with improved outcomes in the ICU.7,38,39 The benefit of intensivists was recently called into question by a study suggesting higher mortality in ICUs staffed by intensivists.40 Although the causes of this discrepant finding are unknown, possibilities include the self-selected nature of hospitals in the cohort, selective referral of high-risk patients to intensivists, and use of in-hospital rather than 30-day mortality, which can lead to discharge bias.41-43 We demonstrate a benefit from intensivist staffing in a population-based cohort of hospitals consistent with prior reports. In addition, our study expands the literature on intensivist staffing by demonstrating a potential mechanism for the effect. Despite the wealth of literature on intensivist physician staffing, few studies are directed at understanding how intensivists achieve superior outcomes.44 Our results show that the benefit of intensivists is due, at least in part, to the multidisciplinary care models typically found in intensivist-led ICUs.
We did not have detailed information about the characteristics of the multidisciplinary team, such as team size, the training and experience of the physician leading the team, or the exact ancillary staff members comprising the team. Given the wording of our questionnaire, we expected that at a minimum the multidisciplinary teams included the primary physician, the bedside nurse, and at least 1 other health care provider. Still, although our study provides empirical support for a multidisciplinary approach to care, we are unable to identify either specific attributes of the multidisciplinary team or an optimal team size that may be associated with improved outcomes. Questions remain about how medical teams function, and even what defines a medical team in practice. These topics are important areas for future research. We also do not know the ideal role of the physician in multidisciplinary rounds. In some ICUs a single intensivist-trained physician may direct rounds on all ICU patients, while in others multiple physicians of varying backgrounds may lead rounds on their patients at different times. Each of these organizational styles would meet our definition of multidisciplinary rounds. Future work should empirically examine the benefits and limitations of these different care models.
Our analysis has several limitations. First, we only had data on care models at a single ICU at each hospital—the ICU primarily providing care to nonsurgical, noncardiac patients. We excluded patients unlikely to have received care in that ICU. These results do not necessarily generalize to surgical, cardiac, and neurological patients, or to specialty ICUs serving those populations. Because the PHC4 discharge data do not specify exactly in which ICU the patient received care, in hospitals with more than 1 ICU it is possible that we excluded some patients who received care in the ICU of interest and included some patients who did not. The finding that mortality was similar among excluded patients in each group suggests that any misclassification bias would be minimal. Second, we did not have organizational data on 55 hospitals that not fully complete our survey. Although survey respondents were similar to nonrespondents, response bias cannot be ruled out. Finally, we were unable to observe the effects of high-intensity physician staffing models without multidisciplinary care teams owing to a low number of hospitals in this category. We cannot comment on whether multidisciplinary care teams improve outcomes within high-intensity physician-staffed ICUs.
With the aging of the population, demand for critical care is certain to rise in the coming years. Evidence-based strategies on how to best organize and manage ICUs are needed.45 We demonstrate that daily rounds by a multidisciplinary care team are associated with lower mortality in the ICU. Clinicians, hospital administrators, and policy makers can use these results to help optimally organize critical care services and potentially improve outcomes for critically ill patients in hospitals where intensivist staffing is not available.
Correspondence: Jeremy M. Kahn, MD, MSc, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, 723 Blockley Hall, 423 Guardian Dr, Philadelphia, PA 19104 (email@example.com).
Accepted for Publication: November 9, 2009.
Author Contributions: Dr Kahn had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Kim, Barnato, Angus, Fleisher, and Kahn. Acquisition of data: Barnato and Kahn. Analysis and interpretation of data: Kim, Barnato, and Kahn. Drafting of the manuscript: Kim and Angus. Critical revision of the manuscript for important intellectual content: Barnato, Angus, Fleisher, and Kahn. Statistical analysis: Kim and Kahn. Obtained funding: Barnato, Fleisher, and Kahn. Administrative, technical, and material support: Barnato, Angus, and Kahn. Study supervision: Kahn.
Financial Disclosure: None reported.
Funding/Support: This work was funded by grant K08AG21921 from the National Institute on Aging (Dr Barnato) and grant K23HL082650 from the National Heart, Lung, and Blood Institute (Dr Kahn), National Institutes of Health, and a grant from the Leonard Davis Institute of Health Economics (Dr Kahn).
Role of the Sponsors: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.
Disclaimer: The following statement is provided and required by the Pennsylvania Health Care Cost Containment Council (PHC4): The PHC4 has provided these data in an effort to further the PHC4's mission of educating the public and containing health care costs in Pennsylvania. The PHC4, its agents and staff, have made no representation, guarantee, or warranty, expressed or implied, that the data—financial-, patient-, payer-, and physician-specific information—are error free or that the use of the data will avoid differences of opinion or interpretation or disputes with those who use published reports or purchased data. The PHC4, its agents and staff, will bear no responsibility or liability for the results of the analysis or consequences of its use.
Previous Presentation: This work was presented in abstract form at the Seventh World Congress on Health Economics; July 14, 2009; Beijing, China.