Association Among ICU Congestion, ICU Admission Decision, and Patient Outcomes. (Vats)

Kim SH, et al. Association Among ICU Congestion, ICU Admission Decision, and Patient Outcomes. Crit Care Med. 2016 Oct;44(10):1814-21.

OBJECTIVES: To employ automated bed data to examine whether ICU occupancy influences ICU admission decisions and patient outcomes.

DESIGN: Retrospective study using an instrumental variable to remove biases from unobserved differences in illness severity for patients admitted to ICU.

SETTING: Fifteen hospitals in an integrated healthcare delivery system in California.

PATIENTS: Seventy thousand one hundred thirty-three episodes involving patients admitted via emergency departments to a medical service over a 1-year period between 2008 and 2009.


MEASUREMENTS AND MAIN RESULTS: A third of patients admitted via emergency department to a medical service were admitted under high ICU congestion (more than 90% of beds occupied). High ICU congestion was associated with a 9% lower likelihood of ICU admission for patients defined as eligible for ICU admission. We further found strong associations between ICU admission and patient outcomes, with a 32% lower likelihood of hospital readmission if the first inpatient unit was an ICU. Similarly, hospital length of stay decreased by 33% and likelihood of transfer to ICU from other units-including ICU readmission if the first unit was an ICU-decreased by 73%.

CONCLUSIONS: High ICU congestion is associated with a lower likelihood of ICU admission, which has important operational implications and can affect patient outcomes. By taking advantage of our ability to identify a subset of patients whose ICU admission decisions are affected by congestion, we found that, if congestion were not a barrier and more eligible patients were admitted to ICU, this hospital system could save approximately 7.5 hospital readmissions and 253.8 hospital days per year. These findings could help inform future capacity planning and staffing decisions.

Analysis of Unplanned Intensive Care Unit Admissions in Postoperative Pediatric Patients. (Sirignano)

Landry EK, et al. Analysis of Unplanned Intensive Care Unit Admissions in Postoperative Pediatric Patients. J Intensive Care Med. 2016 Aug 15. [Epub ahead of print]

BACKGROUND: Currently, there are only a few retrospective, single-institution studies that have addressed the prevalence and risk factors associated with unplanned admissions to the pediatric intensive care unit (ICU) after surgery. Based on the limited amount of studies, it appears that airway and respiratory complications put a child at increased risk for unplanned ICU admission. A more extensive and diverse analysis of unplanned postoperative admissions to the ICU is needed to address risk factors that have yet to be revealed by the current literature.

AIM: To establish a rate of unplanned postoperative ICU admissions in pediatric patients using a large, multi-institution data set and to further characterize the associated risk factors.

METHODS: Data from the National Anesthesia Clinical Outcomes Registry were analyzed. We recorded the overall risk of unplanned postoperative ICU admission in patients younger than 18 years and performed univariate and multivariate logistic regression analysis to identify the associated patient, surgical, and anesthetic-related characteristics.

RESULTS: Of the 324 818 cases analyzed, 211 reported an unexpected ICU admission. There was an increased likelihood of unplanned postoperative ICU in infants (age <1 year) and children who were classified as American Society of Anesthesiologists physical status classification of III or IV. Likewise, longer case duration and cases requiring general anesthesia were also associated with unplanned ICU admissions.

CONCLUSION: This study establishes a rate of unplanned ICU admission following surgery in the heterogeneous pediatric population. This is the first study to utilize such a large data set encompassing a wide range of practice environments to identify risk factors leading to unplanned postoperative ICU admissions. Our study revealed that patient, surgical, and anesthetic complexity each contributed to an increased number of unplanned ICU admissions in the pediatric population.

Off-hours admission to pediatric intensive care and mortality. (Betters)

McCrory MC, Gower EW, Simpson SL, Nakagawa TA, Mou SS, Morris PE. Off-hours admission to pediatric intensive care and mortality. Pediatrics. 2014 Nov;134(5):e1345-53.

Full-text for Children’s and Emory users.

BACKGROUND: Critically ill patients are admitted to the pediatric ICU at all times, while staffing and other factors may vary by day of the week or time of day. The purpose of this study was to evaluate whether admission during off-hours is independently associated with mortality in PICUs.

METHODS: A retrospective cohort study of admissions of patients <18 years of age to PICUs was performed using the Virtual PICU Systems (VPS, LLC) database. “Off-hours” was defined as nighttime (7:00 pm to 6:59 am) or weekend (Saturday or Sunday any time). Mixed-effects multivariable regression was performed by using Pediatric Index of Mortality 2 (PIM2) to adjust for severity of illness. Primary outcome was death in the pediatric ICU.

RESULTS: Data from 234 192 admissions to 99 PICUs from January 2009 to September 2012 were included. When compared with regular weekday admissions, off-hours admissions were less likely to be elective, had a higher risk for mortality by PIM2, and had a higher observed ICU mortality (off-hours 2.7% vs weekdays 2.2%; P < .001). Multivariable regression revealed that, after adjustment for other significant factors, off-hours admission was associated with lower odds of mortality (odds ratio, 0.91; 95% confidence interval, 0.85-0.97; P = .004). Post hoc multivariable analysis revealed that admission during the morning period 6:00 am to 10:59 am was independently associated with death (odds ratio, 1.27; 95% confidence interval, 1.16-1.39; P < .0001).

CONCLUSIONS: Off-hours admission does not independently increase odds of death in the PICU. Admission from 6:00 am to 10:59 am is associated with increased risk for death and warrants further investigation in the PICU population.



Determining delayed admission to intensive care unit for mechanically ventilated patients in the emergency department. (Stockwell)

Hung SC, Kung CT, Hung CW, Liu BM, Liu JW, Chew G, Chuang HY, Lee WH, Lee TC.
Determining delayed admission to intensive care unit for mechanically ventilated patients in the emergency department. Crit Care. 2014 Aug 23;18(4):485.

Free full-text.

INTRODUCTION: The adverse effects of delayed admission to the intensive care unit (ICU) have been recognized in previous studies. However, the definitions of delayed admission varies across studies. This study proposed a model to define “delayed admission”, and explored the effect of ICU-waiting time on patients’ outcome.

METHODS: This retrospective cohort study included non-traumatic adult patients on mechanical ventilation in the emergency department (ED), from July 2009 to June 2010. The primary outcomes measures were 21-ventilator-day mortality and prolonged hospital stays (over 30 days). Models of Cox regression and logistic regression were used for multivariate analysis. The non-delayed ICU-waiting was defined as a period in which the time effect on mortality was not statistically significant in a Cox regression model. To identify a suitable cut-off point between “delayed” and “non-delayed”, subsets from the overall data were made based on ICU-waiting time and the hazard ratio of ICU-waiting hour in each subset was iteratively calculated. The cut-off time was then used to evaluate the impact of delayed ICU admission on mortality and prolonged length of hospital stay.

RESULTS: The final analysis included 1,242 patients. The time effect on mortality emerged after 4 hours, thus we deduced ICU-waiting time in ED > 4 hours as delayed. By logistic regression analysis, delayed ICU admission affected the outcomes of 21 ventilator-days mortality and prolonged hospital stay, with odds ratio of 1.41 (95% confidence interval, 1.05 to 1.89) and 1.56 (95% confidence interval, 1.07 to 2.27) respectively.

CONCLUSIONS: For patients on mechanical ventilation at the ED, delayed ICU admission is associated with higher probability of mortality and additional resource expenditure. A benchmark waiting time of no more than 4 hours for ICU admission is recommended.