The relationship between hospital and intensive care unit length of stay*

Objectives:To assess variations in case-mix–adjusted hospital and intensive care unit length of stay and to examine the relationship between intensive care unit and hospital stay. Design:Retrospective cohort study. Setting:Sixty-nine intensive and cardiac care units in 23 U.S. hospitals during 2002 to 2008. Patients:Intensive care unit admissions (202,300) who met inclusion criteria. Interventions:None. Measurements and Main Results:We obtained hospital and intensive care unit characteristics and patient demographic, clinical, diagnostic, and physiologic variables, mortality, and lengths of stay. We developed and validated a model to assess case-mix–adjusted hospital stay and modified and updated a previously validated model to assess adjusted intensive care unit stay. We used these models to compare observed and expected hospital and intensive care unit stay for each patient by calculating the observed minus expected length of stay. Mean observed intensive care unit stay was 4.33 days and mean predicted intensive care unit stay was 4.09 days (5.9-hr difference); mean observed hospital stay was 9.93 days and mean predicted hospital stay was 9.52 days (9.7-hr difference). Observed minus expected intensive care unit and hospital length of stay were significantly shorter (p < .01) at one intensive care unit and significantly longer (p < .01) at nine intensive care units. There was a correlation between hospital and intensive care unit observed minus expected length of stay across individuals (R2 = .40), which was much stronger across units (R2 = .76). Conclusions:Case-mix–adjusted benchmarks for hospital and intensive care unit stays reveal substantial differences in unit efficiency. Hospital and intensive care unit stays are strongly correlated at the patient and unit level, suggesting that there are causal factors common to both.

[1]  J. Zimmerman,et al.  A model for identifying patients who may not need intensive care unit admission. , 2010, Journal of critical care.

[2]  W. Knaus,et al.  Reliability of a measure of severity of illness: acute physiology of chronic health evaluation--II. , 1992, Journal of clinical epidemiology.

[3]  J. Kress,et al.  Daily interruption of sedative infusions in critically ill patients undergoing mechanical ventilation. , 2000, The New England journal of medicine.

[4]  Peter Bauer,et al.  Variability in outcome and resource use in intensive care units , 2007, Intensive Care Medicine.

[5]  E F Haponik,et al.  Effect on the duration of mechanical ventilation of identifying patients capable of breathing spontaneously. , 1996, The New England journal of medicine.

[6]  J. Zimmerman,et al.  Intensive care unit length of stay: Benchmarking based on Acute Physiology and Chronic Health Evaluation (APACHE) IV* , 2006, Critical care medicine.

[7]  Andrew A. Kramer,et al.  A predictive model for the early identification of patients at risk for a prolonged intensive care unit length of stay , 2010, BMC Medical Informatics Decis. Mak..

[8]  J. Zimmerman,et al.  The use of benchmarking to identify top performing critical care units: a preliminary assessment of their policies and practices. , 2003, Journal of critical care.

[9]  Sharon Einav,et al.  Intensive care outflow limitation--frequency, etiology, and impact. , 2003, Journal of critical care.

[10]  A J Rotondi,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. , 1999, Chest.

[11]  Graeme K Hart,et al.  Mortality and length-of-stay outcomes, 1993–2003, in the binational Australian and New Zealand intensive care adult patient database* , 2008, Critical care medicine.

[12]  C. Ko,et al.  Variability in Length of Stay After Colorectal Surgery: Assessment of 182 Hospitals in the National Surgical Quality Improvement Program , 2009, Annals of surgery.

[13]  Peter J Pronovost,et al.  Physician staffing patterns and clinical outcomes in critically ill patients: a systematic review. , 2002, JAMA.

[14]  W. Knaus,et al.  The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. , 1991, Chest.

[15]  Wayne S Copes,et al.  A revised method to assess intensive care unit clinical performance and resource utilization* , 2007, Critical care medicine.

[16]  Eduard E Vasilevskis,et al.  Mortality probability model III and simplified acute physiology score II: assessing their value in predicting length of stay and comparison to APACHE IV. , 2009, Chest.

[17]  Sean M. O'Brien,et al.  Predictors of prolonged length of stay after lobectomy for lung cancer: a Society of Thoracic Surgeons General Thoracic Surgery Database risk-adjustment model. , 2008, The Annals of thoracic surgery.

[18]  Richard Heijink,et al.  Benchmarking and reducing length of stay in Dutch hospitals , 2008, BMC health services research.

[19]  G. Mcgwin,et al.  The financial impact of delayed discharge at a level I trauma center. , 2005, The Journal of trauma.

[20]  Douglas W. Wilmore,et al.  Evidence-Based Surgical Care and the Evolution of Fast-Track Surgery , 2008, Annals of surgery.

[21]  J. Garnacho-Montero,et al.  Effect of critical illness polyneuropathy on the withdrawal from mechanical ventilation and the length of stay in septic patients* , 2005, Critical care medicine.

[22]  W. Knaus,et al.  Evaluation of acute physiology and chronic health evaluation III predictions of hospital mortality in an independent database. , 1998, Critical care medicine.

[23]  Stanley Lemeshow,et al.  Early indicators of prolonged intensive care unit stay: Impact of illness severity, physician staffing, and pre–intensive care unit length of stay , 2003, Critical care medicine.

[24]  T. Huynh,et al.  Wasted Hospital Days Impair the Value of Length-of-Stay Variables in the Quality Assessment of Trauma Care , 2009, The American surgeon.

[25]  W. Knaus,et al.  Variations in Mortality and Length of Stay in Intensive Care Units , 1993, Annals of Internal Medicine.

[26]  J. Zimmerman,et al.  Acute Physiology and Chronic Health Evaluation (APACHE) IV: Hospital mortality assessment for today’s critically ill patients* , 2006, Critical care medicine.

[27]  Harvey Goldstein,et al.  Multilevel modelling of medical data , 2002, Statistics in medicine.

[28]  Kaveh G Shojania,et al.  The impact of adverse events in the intensive care unit on hospital mortality and length of stay , 2008, BMC health services research.

[29]  L. Cooper,et al.  Medicare intensive care unit use: Analysis of incidence, cost, and payment* , 2004, Critical care medicine.

[30]  G. Cooper,et al.  Severity-adjusted mortality and length of stay in teaching and nonteaching hospitals. Results of a regional study. , 1998, JAMA.

[31]  S. Lemeshow,et al.  Length of Stay Data as a Guide to Hospital Economic Performance for ICU Patients , 2003, Medical care.

[32]  M. Niskanen.  Resource use and postoperative outcome: basic elements in benchmarking , 2009, Current opinion in critical care.

[33]  James Deddens,et al.  Variation in outcomes in Veterans Affairs intensive care units with a computerized severity measure* , 2005, Critical care medicine.

[34]  M. Buntin,et al.  Access to postacute rehabilitation. , 2007, Archives of physical medicine and rehabilitation.

[35]  T. Williams,et al.  Delayed discharges from an adult intensive care unit. , 2004, Australian health review : a publication of the Australian Hospital Association.

[36]  E. Blackstone,et al.  Using Society of Thoracic Surgeons risk models for risk-adjusting cardiac surgery results. , 2010, The Annals of thoracic surgery.

[37]  W. Knaus,et al.  Intensive care unit length of stay: Recent changes and future challenges , 2000, Critical care medicine.

[38]  A J Rotondi,et al.  Are readmissions to the intensive care unit a useful measure of hospital performance? , 1999, Medical care.

[39]  Minna Niskanen,et al.  Case-mix-adjusted length of stay and mortality in 23 Finnish ICUs , 2009, Intensive Care Medicine.

[40]  G. Clermont,et al.  Growth of intensive care unit resource use and its estimated cost in Medicare* , 2008, Critical care medicine.

[41]  REMOTE ICU CARE CORRELATES WITH REDUCED HEALTH SYSTEM MORTALITY AND LENGTH OF STAY OUTCOMES , 2007 .