HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:
Guest Access | Sign In via User Name/Password

This Article Abstract Full Text (PDF) Free Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Add to My Personal Article Archive Download to citation manager Citing Articles Citing Articles via ISI Web of Science (6) Citing Articles via Google Scholar Google Scholar Articles by Dara, S. I. Articles by Afessa, B. Search for Related Content PubMed PubMed Citation Articles by Dara, S. I. Articles by Afessa, B.

Intensivist-to-Bed Ratio^*

Association With Outcomes in the Medical ICU

^* From the Division of Pulmonary and Critical Care Medicine, Mayo Clinic College of Medicine, Rochester, MN.

Correspondence to: Bekele Afessa, MD, Mayo Clinic, 200 First St SW, Rochester, MN 55905; e-mail: afessa.bekele{at}mayo.edu

	Abstract

TOP Abstract Introduction Materials and Methods Results Discussion Conclusions References

 
Objective: With an increasing number of critical care beds, a shortage of critical care physicians, and pressure from purchasers, there is a need to define the optimal intensivist-to-ICU bed ratio. The objective of this study was to determine if there are any associations between the intensivist-to-ICU bed ratio and the outcome of patients admitted to the medical ICU.

Design: Retrospective cohort study.

Setting: A tertiary care medical center.

Patients: All critically ill patients admitted to a medical ICU between December 8, 2001, and July 14, 2003.

Interventions: None.

Measurements: Demographics, APACHE (acute physiology and chronic health evaluation) III-predicted mortality, ICU length of stay (LOS), hospital LOS, and ICU and hospital mortality rates. Four time periods based on intensivist-to-ICU bed ratios of 1:7.5, 1:9.5, 1:12, and 1:15 were identified. Regression analyses were performed to develop customized models to predict ICU and hospital LOS and mortality. The ICU LOS ratio, defined as the ratio of the observed to predicted LOS, and standardized mortality ratio (SMR) were calculated for each of the four periods.

Results: A total of 2,492 patients were included in the study. There was no difference in the severity of illness at the time of ICU admission among the four periods. The mean ICU LOS ratio was longer for an intensivist-to-ICU bed ratio of 1:15 compared to the other periods. The ICU and hospital SMR did not differ significantly among the four periods.

Conclusion: Differences in intensivist-to-ICU bed ratios, ranging from 1:7.5 to 1:15, were not associated with differences in ICU or hospital mortality. However, a ratio of 1:15 was associated with increased ICU LOS.

Key Words: acute physiology and chronic health evaluation III • hospital mortality • ICU • length of stay • outcome study • personnel staffing

	Introduction

TOP Abstract Introduction Materials and Methods Results Discussion Conclusions References

 
Over the last 2 decades, health-care expenditures in the United States have increased, resulting in a 4.5-fold increase per year when adjusted for inflation and population growth.¹ Approximately 0.56% of the US gross domestic product is consumed in the ICU.² At academic health centers, critical care utilizes between 10% and 20% of all beds and between 20% and 30% of the hospital budget.³ Despite the recent decrease in the number of acute care hospital beds, the number of ICU beds have increased.² In view of the high and rising cost of health-care delivery, increasing attention has been paid to minimizing costs while maintaining quality.⁴⁵ Accordingly, efforts have been devoted to the organizational and managerial aspects of care that promote efficient use of scarce resources.⁶

The mortality and morbidity rates associated with ICU admission remain high⁷ and vary widely among institutions.⁸⁹ After adjusting for case-mix, this variation may be related to differences in ICU structure and care processes.¹⁰ To improve the quality of care in ICUs, it is necessary to understand how ICU structures and care processes are related to clinical and economic outcome.¹¹ The various components of ICU structure and care process that have been studied include the number of ICU beds,¹² ICU workload,¹³ ICU expansion,¹⁴ and staffing by intensivist.¹⁵ The implementation of a full-time intensivist staffing a nonrural US adult ICU is estimated to save 162,000 lives annually.¹⁶ However, there are scarce data on the relationship between intensivist-to-ICU bed ratio and clinical outcomes.

In this study, we tested the hypothesis that the intensivist-to-ICU bed ratio influences patient outcome. The primary objective of this study was to assess the effect of intensivist-to-ICU bed ratio on ICU performance as measured by ICU and hospital mortality and length of stay (LOS).¹⁷ Our secondary objective was to determine the effect of expansion of a medical ICU on severity of illness.

	Materials and Methods

TOP Abstract Introduction Materials and Methods Results Discussion Conclusions References

 
Subjects and Setting
This retrospective study was performed in a medical ICU of a tertiary medical center in Rochester, MN. The medical ICU served predominantly adult medical patients. There were separate ICUs for adults presenting with primarily cardiac, neurologic, surgical, and trauma-related disorders and pediatric patients. There was no intermediate care unit for medical patients during the study period. However, patients with long-term ventilator requirements were cared for in a separate ventilator-dependent unit. Before April 1, 2002, the medical ICU consisted of 15 beds and was staffed by one critical care-trained consultant physician (intensivist-to-bed ratio, 1:15), three critical care fellows, and four third-year and four first-year internal medicine residents. The triage responsibilities rested with the consultant. However, the third-year resident would be the first to triage patients admitted from the floor. All patients admitted to the medical ICU were assigned a co-primary service. However, the ICU team, not the co-primary service, made all patient-management decisions during ICU stays. A team consisting of a fellow, a third-year resident, and a first-year resident took in-house call at night, providing 24-h coverage.

On April 1, 2002, the medical ICU underwent the first of a series of changes. Two ICU teams were created. Each team was led by a critical care physician (intensivist-to-bed ratio, 1:7.5) and consisted of two fellows, two third-year, and two first-year internal medicine residents. On August 7, 2002, the medical ICU bed capacity was expanded to 19 beds (intensivist-to-bed ratio, 1:9.5). Patients were assigned to one of the internal medicine services at the time of transfer from the ICU rather than at admission to the ICU. The ICU service obtained the majority of its specialty consultations from the appropriate consultation services, whereas this function had been provided by the co-primary service previously. The final phase of reorganization was completed on December 18, 2002, with the expansion of the medical ICU bed capacity to 24 beds (intensivist-to-bed ratio, 1:12).

Other than the change in the intensivist-to-bed ratio, the role of the attending intensivist did not undergo any major change. The intensivists were responsible for the supervision of delivery of all care in the ICU. During the day, they made rounds at least twice daily, supervised all invasive procedures, wrote daily progress notes, and supervised educational activities for residents and fellows. The intensivists did not stay in-house at night; however, they were available by telephone for all admissions and would come to the ICU when needed. During the study period, some of the other staffing practices remained constant: the nurse-to-patient ratio, which was maintained at 1:1 to 1:2, and the resident rotation through the medical ICU, which was maintained for 4 to 5 weeks.

If the medical ICU was full at any time during the study periods, patients were admitted to a surgical ICU that had 20 beds and was staffed by intensivists with a background in anesthesia. The medical ICU team did not have any responsibility for the care of these patients.

We identified patients who were admitted to the medical ICU between December 8, 2001, and July 14, 2003. The period between December 8, 2001, and March 31, 2002, was labeled period 1 (intensivist-to-bed ratio, 1:15). The period between April 1, 2002, and August 6, 2002, was labeled period 2 (intensivist-to-bed ratio, 1:7.5). Period 3 (intensivist-to-bed ratio, 1: 9.5) was from August 7, 2002, to December 17, 2002. Period 4 (intensivist-to-bed ratio, 1:12) was from December 18, 2002, to July 14, 2003.

Measurements
We collected information on demographics, admission source, admission diagnosis, intensity of care, observed ICU mortality, ICU LOS (days), observed hospital mortality, hospital LOS (days), ICU occupancy rate, and ICU readmission. The first ICU day APACHE (acute physiology and chronic health evaluation) III scores and predicted mortality rates were calculated as described in the literature.¹⁸

A total of 2,525 patients were admitted to the medical ICU during the study period. We excluded 33 patients because of a lack of research authorization or incomplete data. This study was approved by the institutional review board of our institution.

Statistical Analysis
Continuous variables are reported as mean with SD if parametric and as median with interquartile range (IQR) if nonparametric. Categorical variables are reported as proportions. To determine difference across the four periods, we used analysis of variance, Kruskal-Wallis test, and ² tests. We used Student t test, Mann-Whitney U test, ², and Fisher Exact Test for comparisons between two groups.

To estimate the predicted ICU LOS for each patient, we used a multivariate linear regression model as previously described.¹⁹ The independent variables entered in this model were APACHE III-predicted hospital mortality rate, observed hospital mortality, the interaction between APACHE III predicted hospital mortality rate and observed hospital mortality, admission source, and intensity of treatment. Actual ICU LOS > 40 days was truncated at 40 days.⁸ The weighted ICU LOS was calculated by assigning a value of 4 to the first ICU day and values of 2.5 to each subsequent ICU day.¹⁷ We calculated the ratio of actual to predicted weighted ICU LOS.¹⁹ A low ratio indicated good performance.¹⁹ A similar model was created for hospital LOS. Actual hospital LOS > 40 days was also truncated at 40 days. Weighted hospital LOS was calculated by assigning a values of 4 to the first ICU day, 2.5 to each subsequent ICU day, and 1 to each subsequent hospital day.

To estimate the customized predicted hospital mortality for each patient, we used a previously described model.¹⁹ The independent variables in this model were APACHE-III predicted mortality, admission source, and intensity of treatment. Standardized mortality ratio (SMR) was calculated as the ratio of the actual to predicted mortality rate²⁰ and was reported with its 95% confidence interval (CI). An SMR < 1 indicates good performance, and an SMR > 1 indicates poor performance.²⁰ A similar model was created for ICU mortality.

To determine if the intensivist-to-bed ratio is an independent variable associated with ICU or hospital mortality after controlling for other factors that impact on patient outcome, logistic regression analyses were performed with intensivist-to-bed ratio, APACHE III-predicted mortality, admission source, and intensity of treatment as independent variables. We used statistical software (Version 13.0; SPSS; Chicago, IL; and JMP Version 5.1.2; SAS Institute; Cary, NC) analysis; p < 0.05 was considered statistically significant.

	Results

TOP Abstract Introduction Materials and Methods Results Discussion Conclusions References

 
Two thousand four hundred ninety-two patients were included in the study. The mean (± SD) age was 62.3 ± 19 years, and 49.3% of the patients were female. The emergency department was the most common source of admission to the ICU (45.9%), followed by the ward (32.2%). The median APACHE III score on day 1 of admission to the ICU was 56 (IQR, 38 to 75). The ICU and hospital mortality rates were 11.9% and 19.3%, respectively. The median observed ICU LOS was 1.5 days (IQR, 0.8 to 3.1). The median hospital LOS was 6.6 days (IQR, 3.1 to 14.5). The mean predicted ICU mortality rate was 13.2 ± 20.2%. The mean predicted hospital mortality rate was 21.1 ± 24.4%.

The baseline characteristics of the study population are shown in Table 1 . There were no statistically significant differences in the severity of illness, measured by the APACHE III scores and predicted hospital mortality rates, and ICU readmission between the four periods. The emergency department remained the single-largest source of admission to the ICU during each period. There were no statistically significant differences in the ICU admission source among the four periods (p = 0.131) [Table 2 ]. Based on the APACHE III database, the daily bed occupancies were 13.0, 12.2, 13.8, and 15.4 during periods 1, 2, 3, and 4, respectively. This results in intensivist-to-patient ratios of 1:13, 1:6.1, 1:6.9 and 1:7.7 for periods 1, 2, 3, and 4, respectively.

	Discussion

TOP Abstract Introduction Materials and Methods Results Discussion Conclusions References

Our first finding is that the severity of illness at the time of ICU admission among the four periods did not differ significantly. This suggests that the increased ICU bed capacity from 15 to 24 beds did not result in a lower threshold for admission to the ICU.

The second important finding is the lack of significant difference in hospital and ICU mortality rates across the different ICU periods. This suggests that even after case-mix adjustment, an intensivist-to-bed ratio varying between 1:7.5 and 1:15 does not influence survival status at hospital discharge. Since the medical ICU was staffed with fellows and residents 24 h/d during all of the study periods, the absence of survival differences is not a surprising finding.

The third finding is the association of longer ICU LOS with an ICU staffing of 15 beds, compared to higher intensivist-to-ICU bed ratios. The absence of statistically significant differences in the hospital LOS among the study periods suggests that earlier transfers from medical ICU to the floor during the later periods of the study may account for the difference in the ICU LOS.

ICU LOS has been evaluated and used as a surrogate marker of cost of care and ICU performance.¹⁷ Multiple factors affect LOS.⁸¹⁷²¹ Case-mix plays a major role in length of stay in an ICU patient population.¹⁷ After adjusting for factors that affect the length of ICU stay in our patient population¹⁹ in multivariate analysis, the association remained significant. Does this association between ICU LOS and intensivist-to-bed ratio represent cause and effect? It is theoretically conceivable. The demands on the mental and physical skills of an intensivist responsible for 15 ICU beds relative to an intensivist responsible for 7.5 beds may be higher. One estimate shows that an intensivist is confronted with 1,000 pieces of information on each patient every day.²² A previous study²³ suggests that the greater the number of patients and the more intermittent the contact with a physician, the higher are the chances of confusion and error. This leads us to speculate that the increased LOS may have been partly the result of more errors and insufficient time for adequate supervision of all procedures.¹³

Previous studies have discussed the reasons of improved outcome with staffing ICUs with intensivists. These include increased likelihood of care decisions being made in a timely manner,⁶ decrease in complications of invasive monitoring²⁴ and invasive treatment,²⁵ improved patient and family satisfaction,²⁴ better end-of-life care,²¹ and improved interdisciplinary coordination.²⁶ We believe that within an ICU staffed by an intensivist, as the number of beds increases, we may see the above mentioned beneficial effects to a lesser extent. This may have played a role in prolonging the ICU LOS with lower intensivist-to-bed ratios.

In addition to the staffing, there can be other confounding factors that may have impact on outcome and not measured in the current study. A change in practice is one of such confounding factors. However, the only new practice protocol that was introduced during the study periods was a low tidal volume protocol for acute lung injury and ARDS.²⁷ This protocol was implemented toward the middle of the last study period (March 2003). Analysis of patients with acute lung injury and ARDS from March to June 2003 showed a compliance rate of 48% with the protocol. However, the hospital mortality rate and ICU LOS were not different among the protocol and nonprotocol groups.²⁷ Furthermore, during study periods 1 and 2 of our study, each patient was assigned a co-primary service. Change in co-primary services and appropriateness and speed of consultations and seasonal variations can also influence the outcomes we measured, independent of the ICU staffing.

As ICU staffing was changed during the different study periods, we chose to relate outcomes to intensivist-to-bed ratio. Although the intensivist-to-patient ratio showed a parallel trend to intensivist-to-bed ratio in the current study, changes in bed occupancy rates could have resulted in different results. However, the current physician staffing patterns are usually not responsive to fluctuations in intensivist-to-patient ratio, in contrast to staffing patterns of some other ICU personnel. For example, while a nurse-to-patient ratio of 1:1 or 1:2 is maintained in many ICUs, there is usually a fixed number of intensivists per ICU. As such, intensivist-to-bed ratio may be of some interest to decision makers as they decide on physician staffing requirements of ICUs of various sizes.

Although we did not come across any study investigating our particular question, our findings expand on previously published studies. Kelley et al¹⁴ described their experience with expansion of a medical ICU together with increased staff support, after construction of a separate cardiac care unit. They did not find a difference in severity of illness (APACHE II score), readmission rate, hospital mortality, or ICU LOS after an increase in the ICU bed capacity. However they did not describe intensivist-to-ICU bed ratios and if any differences in patient outcome were found by changes in this ratio.

Other studies²¹²⁴ have shown that involvement of a full-time ICU physician reduces ICU LOS. A logical next question would be, does an intensivist staffing a 6-bed ICU reduces ICU LOS to the same extent as an intensivist staffing a 24-bed ICU? Our observational study suggests that the intensivist-to-bed ratio may influence the ICU LOS. This has important implications for organization and delivery of critical care services. There are about 6,000 ICUs in the United States,¹⁵ with the number of beds varying between 6 and 24.¹⁷ Technological, demographic, and social forces are likely to lead to an increased volume of intensive care in the future.²⁸ As the number of adequately trained critical care physicians lags behind,²⁹ the increase in number of ICU beds in this country,² the question of intensivist-to-ICU bed ratio will need to be addressed. No intervention in the past 3 decades has been shown to have more impact on patient mortality in the ICU than organizing the ICU service.³⁰ The critical care professionals have been promoting a model of critical care that provides a coordinated team of experts trained in critical care and dedicated to the ICU patients.³¹³² And now with the arrival of mandate from private purchasers like The Leapfrog Group (www.leapfroggroup.org) for full-time intensivist staffing,³¹ this question will need to be carefully considered.³³

This study has several limitations. It has a retrospective design and reflects the experience of a single tertiary care institution, limiting its applicability to other medical centers. In addition to intensivists, our medical ICU was staffed by fellows and residents throughout the study period. Since many ICUs do not have 24 h/d coverage by critical care fellows, the optimal intensivist-to-ICU bed ratios are likely to vary among institutions.

We used hospital mortality as an end point of patient outcome. This end point does not account for other important aspects of quality of critical care such as long-term mortality and functional outcomes.²⁰

The major benefit of lower physician-to-patient ratio appears to be the decreased LOS, as there was no significant change in mortality. This may have been due to the early transfer of patients from the ICU instead of changes in the overall quality of care. Although lower LOS may lead to lower costs, it is also conceivable that the benefits may be offset by cost of increased number of intensivists to provide such coverage. Such economic evaluations should be the focus of future studies.

	Conclusions

TOP Abstract Introduction Materials and Methods Results Discussion Conclusions References

 
This retrospective observational study suggests that an ICU with an intensivist staffing of 15 beds is associated with prolonged ICU LOS compared to higher staffing ratios, without affecting ICU or hospital mortality. Further research is needed to find if this applies to other ICUs in tertiary care medical centers as well as to nonteaching, community based ICUs.

	Footnotes

 
Abbreviations: APACHE = acute physiology and chronic health evaluation; CI = confidence interval; IQR = interquartile range; LOS = length of stay; SMR = standardized mortality ratio

Received for publication October 12, 2004. Accepted for publication January 7, 2005.

	References

TOP Abstract Introduction Materials and Methods Results Discussion Conclusions References

 

1. Bloomfield, EL (2003) The impact of economics on changing medical technology with reference to critical care medicine in the United States. Anesth Analg 96,418-425[Free Full Text]
2. Halpern, NA, Pastores, SM, Greenstein, RJ Critical care medicine in the United States 1985–2000: an analysis of bed numbers, use, and costs. Crit Care Med 2004;32,1254-1259[CrossRef][ISI][Medline]
3. Bekes, CE, Dellinger, RP, Brooks, D, et al Critical care medicine as a distinct product line with substantial financial profitability: the role of business planning. Crit Care Med 2004;32,1207-1214[CrossRef][ISI][Medline]
4. Peters, SG, Farmer, JC Con: Is the tele-intensive care unit ready for prime time? Crit Care Med 2004;32,288-290[CrossRef][ISI][Medline]
5. Burchardi, H, Moerer, O Twenty-four hour presence of physicians in the ICU. Crit Care 2001;5,131-137[CrossRef][ISI][Medline]
6. Multz, AS, Chalfin, DB, Samson, IM, et al A "closed" medical intensive care unit (MICU) improves resource utilization when compared with an "open" MICU. Am J Respir Crit Care Med 1998;157,1468-1473
7. Carmel, S, Rowan, K Variation in intensive care unit outcomes: a search for the evidence on organizational factors. Curr Opin Crit Care 2001;7,284-296[CrossRef][Medline]
8. Knaus, WA, Wagner, DP, Zimmerman, JE, et al Variations in mortality and length of stay in intensive care units. Ann Intern Med 1993;118,753-761[Abstract/Free Full Text]
9. Zimmerman, JE, Shortell, SM, Rousseau, DM, et al Improving intensive care: observations based on organizational case studies in nine intensive care units: a prospective, multicenter study. Crit Care Med 1993;21,1443-1451[ISI][Medline]
10. Pronovost, PJ, Jenckes, MW, Dorman, T, et al Organizational characteristics of intensive care units related to outcomes of abdominal aortic surgery. JAMA 1999;281,1310-1317[Abstract/Free Full Text]
11. Pollack, MM, Katz, RW, Ruttimann, UE, et al Improving the outcome and efficiency of intensive care: the impact of an intensivist. Crit Care Med 1988;16,11-17[ISI][Medline]
12. Pollack, MM, Cuerdon, TT, Patel, KM, et al Impact of quality-of-care factors on pediatric intensive care unit mortality. JAMA 1994;272,941-946[Abstract]
13. Tarnow-Mordi, WO, Hau, C, Warden, A, et al Hospital mortality in relation to staff workload: a 4-year study in an adult intensive-care unit. Lancet 2000;356,185-189[CrossRef][ISI][Medline]
14. Kelley, MA, Nachamkin, DC, Escarce, JJ, et al Expansion of the medical intensive care unit: clinical consequences in a large urban hospital. Crit Care Med 1990;18,945-949[ISI][Medline]
15. Pronovost, PJ, Angus, DC, Dorman, T, et al Physician staffing patterns and clinical outcomes in critically ill patients: a systematic review. JAMA 2002;288,2151-2162[Abstract/Free Full Text]
16. Rollins, G ICU care management by intensivists reduces mortality and length of stay. Rep Med Guidel Outcomes Res 2002;13,5-7
17. Rapoport, J, Teres, D, Zhao, Y, et al Length of stay data as a guide to hospital economic performance for ICU patients. Med Care 2003;41,386-397[CrossRef][ISI][Medline]
18. Knaus, WA, Wagner, DP, Draper, EA, et al The APACHE III prognostic system: risk prediction of hospital mortality for critically ill hospitalized adults. Chest 1991;100,1619-1636[Medline]
19. Finkielman, JD, Morales, J, Peters, SG, et al Mortality rate and length of stay of patients admitted to the intensive care unit in July. Crit Care Med 2004;32,1161-1165[CrossRef][ISI][Medline]
20. Sirio, CA, Shepardson, LB, Rotondi, AJ, et al Community-wide assessment of intensive care outcomes using a physiologically based prognostic measure: implications for critical care delivery from Cleveland Health Quality Choice. Chest 1999;115,793-801[Abstract/Free Full Text]
21. Higgins, TL, McGee, WT, Steingrub, JS, et al Early indicators of prolonged intensive care unit stay: impact of illness severity, physician staffing, and pre-intensive care unit length of stay. Crit Care Med 2003;31,45-51[CrossRef][ISI][Medline]
22. Morris, AH Developing and implementing computerized protocols for standardization of clinical decisions. Ann Intern Med 2000;132,373-383[Abstract/Free Full Text]
23. Donchin, Y, Gopher, D, Olin, M, et al A look into the nature and causes of human errors in the intensive care unit. 1995. Qual Saf Health Care 2003;12,143-147[Abstract/Free Full Text]
24. Carson, SS, Stocking, C, Podsadecki, T, et al Effects of organizational change in the medical intensive care unit of a teaching hospital: a comparison of "open" and "closed" formats. JAMA 1996;276,322-328[Abstract]
25. Cohen, IL, Bari, N, Strosberg, MA, et al Reduction of duration and cost of mechanical ventilation in an intensive care unit by use of a ventilatory management team. Crit Care Med 1991;19,1278-1284[ISI][Medline]
26. Manthous, CA, Amoateng-Adjepong, Y, al-Kharrat, T, et al Effects of a medical intensivist on patient care in a community teaching hospital. Mayo Clin Proc 1997;72,391-399[ISI][Medline]
27. Holets, S, Dara, SI, Gajic, O, et al Compliance and outcomes of ventilator management guidelines for patients with acute lung injury. Proc Am Thorac Soc 2005;2(suppl)in press
28. Shortell, SM, Zimmerman, JE, Rousseau, DM, et al The performance of intensive care units: does good management make a difference? Med Care 1994;32,508-525[ISI][Medline]
29. Angus, DC, Kelley, MA, Schmitz, RJ, et al Caring for the critically ill patient: current and projected workforce requirements for care of the critically ill and patients with pulmonary disease: can we meet the requirements of an aging population? JAMA 2000;284,2762-2770[Abstract/Free Full Text]
30. Parker, MM Critical care: you are the future. Crit Care Med 2004;32,1097-1099[CrossRef][ISI][Medline]
31. Pronovost, PJ, Needham, DM, Waters, H, et al Intensive care unit physician staffing: financial modeling of the Leapfrog standard. Crit Care Med 2004;32,1247-1253[CrossRef][ISI][Medline]
32. Brilli, RJ, Spevetz, A, Branson, RD, et al Critical care delivery in the intensive care unit: defining clinical roles and the best practice model. Crit Care Med 2001;29,2007-2019[CrossRef][ISI][Medline]
33. Kelley, MA, Angus, D, Chalfin, DB, et al The critical care crisis in the United States: a report from the profession. Chest 2004;125,1514-1517[Free Full Text]

This Article Abstract Full Text (PDF) Free Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Add to My Personal Article Archive Download to citation manager Citing Articles Citing Articles via ISI Web of Science (6) Citing Articles via Google Scholar Google Scholar Articles by Dara, S. I. Articles by Afessa, B. Search for Related Content PubMed PubMed Citation Articles by Dara, S. I. Articles by Afessa, B.