scholarly journals Predicting Patient Outcomes, Futility, and Resource Utilization in the Intensive Care Unit: The Role of Severity Scoring Systems and General Outcome Prediction Models

2005 ◽  
Vol 80 (2) ◽  
pp. 161-163 ◽  
Author(s):  
Pedro A. Mendez-Tellez ◽  
Todd Dorman
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Patient Outcomes ◽  
Resource Utilization ◽  
Outcome Prediction ◽  
Prediction Models ◽  
Scoring Systems ◽  
Severity Scoring ◽  
General Outcome

Organization and Structure of the Cardiothoracic Intensive Care Unit

2015 ◽  
pp. 86-104
Author(s):  
Michael H. Wall
Keyword(s):  
Intensive Care Unit ◽  
Critical Care ◽  
Intensive Care ◽  
Patient Outcomes ◽  
Nurse Practitioners ◽  
Physician Assistants ◽  
Cost Of Care ◽  
Team Members ◽  
Low Intensity

The purpose of this chapter is to emphasize and describe the team nature of critical care medicine in the Cardiothoracic Intensive Care Unit. The chapter will review the importance of various team members and discuss various staffing models (open vs closed, high intensity vs low intensity, etc.) on patient outcomes and cost. The chapter will also examine the roles of nurse practitioners and physician assistants (NP/PAs) in critical care, and will briefly review the growing role of the tele-ICU. Most studies support the concept that a multi-disciplinary ICU team, led by an intensivist, improves patient outcomes and decreases overall cost of care. The role of the tele-ICU and 24 hour in-house intensivist staffing in improving outcomes is controversial, and more research is needed in this area. Finally, a brief discussion of billing for critical care will be discussed.

Organization and Structure of the Cardiothoracic Intensive Care Unit

Oncology ◽  
2017 ◽  
pp. 709-727
Author(s):  
Michael H. Wall
Keyword(s):  
Intensive Care Unit ◽  
Critical Care ◽  
Intensive Care ◽  
Patient Outcomes ◽  
Nurse Practitioners ◽  
Physician Assistants ◽  
Cost Of Care ◽  
Team Members ◽  
Low Intensity

The purpose of this chapter is to emphasize and describe the team nature of critical care medicine in the Cardiothoracic Intensive Care Unit. The chapter will review the importance of various team members and discuss various staffing models (open vs closed, high intensity vs low intensity, etc.) on patient outcomes and cost. The chapter will also examine the roles of nurse practitioners and physician assistants (NP/PAs) in critical care, and will briefly review the growing role of the tele-ICU. Most studies support the concept that a multi-disciplinary ICU team, led by an intensivist, improves patient outcomes and decreases overall cost of care. The role of the tele-ICU and 24 hour in-house intensivist staffing in improving outcomes is controversial, and more research is needed in this area. Finally, a brief discussion of billing for critical care will be discussed.

scholarly journals Individual outcome prediction models for patients with COVID-19 based on their first day of admission to the intensive care unit

2021 ◽  
Author(s):  
Raúl Rigo-Bonnin ◽  
Víctor-Daniel Gumucio-Sanguino ◽  
Xose-Luís Pérez-Fernández ◽  
Luisa Corral-Ansa ◽  
MariPaz Fuset-Cabanes ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Outcome Prediction ◽  
Prediction Models ◽  
Individual Outcome

scholarly journals Performance of Intensive Care Unit Severity Scoring Systems Across Different Ethnicities

2020 ◽  
Author(s):  
Rahuldeb Sarkar ◽  
Christopher Martin ◽  
Heather Mattie ◽  
Judy Wawira Gichoya ◽  
David J. Stone ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Scoring Systems ◽  
Severity Scoring

scholarly journals Predicting hospital mortality for intensive care unit patients: Time-series analysis

2019 ◽  
Vol 26 (2) ◽  
pp. 1043-1059 ◽  
Author(s):  
Aya Awad ◽  
Mohamed Bader-El-Den ◽  
James McNicholas ◽  
Jim Briggs ◽  
Yasser El-Sonbaty
Keyword(s):  
Intensive Care Unit ◽  
Time Series ◽  
Intensive Care ◽  
Time Series Analysis ◽  
Intensive Care Unit Admission ◽  
Hospital Mortality ◽  
Prediction Models ◽  
Scoring Systems ◽  
Machine Learning Classification ◽  
Series Analysis

Current mortality prediction models and scoring systems for intensive care unit patients are generally usable only after at least 24 or 48 h of admission, as some parameters are unclear at admission. However, some of the most relevant measurements are available shortly following admission. It is hypothesized that outcome prediction may be made using information available in the earliest phase of intensive care unit admission. This study aims to investigate how early hospital mortality can be predicted for intensive care unit patients. We conducted a thorough time-series analysis on the performance of different data mining methods during the first 48 h of intensive care unit admission. The results showed that the discrimination power of the machine-learning classification methods after 6 h of admission outperformed the main scoring systems used in intensive care medicine (Acute Physiology and Chronic Health Evaluation, Simplified Acute Physiology Score and Sequential Organ Failure Assessment) after 48 h of admission.

Sign in / Sign up

Export Citation Format

Share Document