The Impact of Implementing an Intensivist Model With Nighttime In-Hospital Nocturnist and Effect on ICU Outcomes.

Background: Various intensivist staffing models have been suggested, but the long-term sustainability and outcomes vary and may not be sustained. We examined the impact of implementing a high-intensity intensivist coverage model with a nighttime in-house nocturnist (non-intensivist) and its effect on intensive care unit (ICU) outcomes.

Methods: We obtained historical control baseline data from 2007 to 2011 and compared the same data from 2011 to 2015.

Do elderly patients fare well in the ICU?

Background: A recent update of the Mortality Probability Model (MPM)-III found 14% of intensive care patients had age as their only MPM risk factor for hospital mortality. This subgroup had a low mortality rate (2% vs 14% overall), and pronounced differences were noted among elderly patients. This article is an expanded analysis of age-related mortality rates in patients in the ICU.

Can we identify patients at high risk for unplanned extubation? A large-scale multidisciplinary survey.

Background: Unplanned extubation represents a threat to patient safety, and risk factors and prevention strategies for unplanned extubation have not been fully explored.

Objectives: To define high-risk patients for unplanned extubation and determine clinicians' beliefs on perceived risks for unplanned extubation

Methods: With a Web-based survey instrument we surveyed critical care clinician members of the American Association for Respiratory Care, the American Association of Critical Care Nurses, and the Society of Critical Care Medicine.

Results: Surveys were completed by 1,976 clinicians, including 419 respiratory therapists, 870 critical care nurses, and 605 critical care physicians.

Subgroup mortality probability models: are they necessary for specialized intensive care units?

Objectives: To examine the sensitivity of the performance of the latest Mortality Probability Model at intensive care unit admission (MPM0-III) to case-mix variations and to determine how specialized models for these subgroups would affect intensive care unit performance assessment. MPM0-III is an important benchmarking tool for intensive care units in Project IMPACT. Overall, MPM0-III has excellent discrimination and calibration but its performance varies on six common patient subsets.

Prospective validation of the intensive care unit admission Mortality Probability Model (MPM0-III).

Objective: To validate performance characteristics of the intensive care unit (ICU) admission mortality probability model, version III (MPM0-III) on Project IMPACT data submitted in 2004 and 2005. This data set was external from the MPM0-III developmental and internal validation data collected between 2001 and 2004.

Design: Retrospective analysis of clinical data collected concurrently with care.

Outcome prediction in critical care: the Mortality Probability Models.

Purpose Of Review: The comparison of morbidity, mortality, and length-of-stay outcomes in patients receiving critical care requires adjustment based on their presenting illness. These adjustments are made with severity-of-illness models. These models must be periodically updated to reflect current medical practices.

A revised method to assess intensive care unit clinical performance and resource utilization.

Objective: In 1994, Rapoport et al. published a two-dimensional graphical tool for benchmarking intensive care units (ICUs) using a Mortality Probability Model (MPM0-II) to assess clinical performance and a Weighted Hospital Days scale (WHD-94) to assess resource utilization. MPM0-II and WHD-94 do not calibrate on contemporary data, giving users of the graph an inflated assessment of their ICU's performance.

Assessing contemporary intensive care unit outcome: an updated Mortality Probability Admission Model (MPM0-III).

Objective: To update the Mortality Probability Model at intensive care unit (ICU) admission (MPM0-II) using contemporary data.

Design: Retrospective analysis of data from 124,855 patients admitted to 135 ICUs at 98 hospitals participating in Project IMPACT between 2001 and 2004. Independent variables considered were 15 MPM0-II variables, time before ICU admission, and code status.

The value and limits of severity adjusted mortality for ICU patients.

Intensive care unit (ICU) data systems serve a variety of valuable functions for ICU directors, quality-of-care managers, safety officers and health service researchers. Although controversial, severity adjusted mortality cross-linked with resource measures may provide additional value when comparisons are made to similar types of ICUs. This article describes several options for improving the standardized mortality ratio.

Length of stay data as a guide to hospital economic performance for ICU patients.

Context: Length of stay data are increasingly used to monitor ICU economic performance. How such material is presented greatly affects its utility.

Objective: To develop a weighted length of stay index and to estimate expected length of stay.

Early indicators of prolonged intensive care unit stay: impact of illness severity, physician staffing, and pre-intensive care unit length of stay.

Objective: Scoring systems that predict mortality do not necessarily predict prolonged length of stay or costs in the intensive care unit (ICU). Knowledge of characteristics predicting prolonged ICU stay would be helpful, particularly if some factors could be modified. Such factors might include process of care, including active involvement of full-time ICU physicians and length of hospital stay before ICU admission.

Effects of severity of illness on resource use by survivors and nonsurvivors of severe sepsis at intensive care unit admission.

Objective: To determine the relationship between severity of illness and length of stay for survivors and nonsurvivors of severe sepsis at intensive care unit admission.

Design: Observational study.

Setting: Fifty intensive care units participating in Project IMPACT submitted data during 1998-99.