To analyze the influence of using mortality 1, 3, and 6 months after intensive care unit (ICU) admission instead of in-hospital mortality on the quality indicator standardized mortality ratio (SMR). A cohort study of 77,616 patients admitted to 44 Dutch mixed ICUs between 1 January 2008 and 1 July 2011. Four Acute Physiology and Chronic Health Evaluation (APACHE) IV models were customized to predict in-hospital mortality and mortality 1, 3, and 6 months after ICU admission. Models' performance, the SMR and associated SMR rank position of the ICUs were assessed by bootstrapping. The customized APACHE IV models can be used for prediction of in-hospital mortality as well as for mortality 1, 3, and 6 months after ICU admission. When SMR based o...
OBJECTIVE: To develop a model to assess severity of illness and predict vital status at hospital dis...
No specific prognostic model has been developed for patients readmitted to the intensive care unit (...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
To analyze the influence of using mortality 1, 3, and 6 months after intensive care unit (ICU) admis...
PURPOSE:To assess and improve the effectiveness of ICU care, in-hospital mortality rates are often u...
OBJECTIVES: To compare ICU performance using standardized mortality ratios generated by the Acute Ph...
Purpose To assess and improve the effectiveness of ICU care, in-hospital mortality rates are often u...
Context: Various scoring systems have been developed to predict mortality and morbidity in Intensive...
BackgroundStandardised mortality ratio (SMR) is a common quality indicator in critical care and is t...
Intensive care unit (ICU) prognostic models can be used to predict mortality outcomes for criticall...
The aim of this study is to verify calibration and discrimination after 5 years in the case mix of p...
OBJECTIVE: To examine the accuracy of the original Mortality Probability Admission Model III, ICU Ou...
OBJECTIVES\nTo assess the mortality risk of ICU patients after hospital discharge and compare it to ...
Accurate mortality prediction in intensive care units (ICUs) allows for the risk adjustment of study...
Objectives: To develop a model to benchmark mortality in hospitalized patients using accessible ele...
OBJECTIVE: To develop a model to assess severity of illness and predict vital status at hospital dis...
No specific prognostic model has been developed for patients readmitted to the intensive care unit (...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
To analyze the influence of using mortality 1, 3, and 6 months after intensive care unit (ICU) admis...
PURPOSE:To assess and improve the effectiveness of ICU care, in-hospital mortality rates are often u...
OBJECTIVES: To compare ICU performance using standardized mortality ratios generated by the Acute Ph...
Purpose To assess and improve the effectiveness of ICU care, in-hospital mortality rates are often u...
Context: Various scoring systems have been developed to predict mortality and morbidity in Intensive...
BackgroundStandardised mortality ratio (SMR) is a common quality indicator in critical care and is t...
Intensive care unit (ICU) prognostic models can be used to predict mortality outcomes for criticall...
The aim of this study is to verify calibration and discrimination after 5 years in the case mix of p...
OBJECTIVE: To examine the accuracy of the original Mortality Probability Admission Model III, ICU Ou...
OBJECTIVES\nTo assess the mortality risk of ICU patients after hospital discharge and compare it to ...
Accurate mortality prediction in intensive care units (ICUs) allows for the risk adjustment of study...
Objectives: To develop a model to benchmark mortality in hospitalized patients using accessible ele...
OBJECTIVE: To develop a model to assess severity of illness and predict vital status at hospital dis...
No specific prognostic model has been developed for patients readmitted to the intensive care unit (...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...