Quantifying Risk and Benchmarking Performance in the Adult Intensive Care Unit

Abstract

Morbidity, mortality, and length-of-stay outcomes in patients receiving critical care are difficult to interpret unless they are risk-stratified for diagnosis, presenting severity of illness, and other patient characteristics. Acuity adjustment systems for adults include the Acute Physiology And Chronic Health Evaluation (APACHE), the Mortality Probability Model (MPM), and the Simplified Acute Physiology Score (SAPS). All have recently been updated and recalibrated to reflect contemporary results. Specialized scores are also available for patient subpopulations where general acuity scores have drawbacks. Demand for outcomes data is likely to grow with pay-for-performance initiatives as well as for routine clinical, prognostic, administrative, and research applications. It is important for clinicians to understand how these scores are derived and how they are properly applied to quantify patient severity of illness and benchmark intensive care unit performance.

Evolution of Critical Care Cardiology: Transformation of the Cardiovascular Intensive Care Unit and the Emerging Need for New Medical Staffing and Training Models

“…138,139 Performance can be evaluated by comparing an ICU against itself over time, against other comparable ICUs, or to other benchmarks such as best practice. 140 Feedback is intended to then drive performance improvement.…”

Red cell distribution width and survival in patients hospitalized on a medical ICU

“…Besides APACHE II, there are further revisions to increase the predictive value of APACHE, i.e., APACHE III and IV 4 . Risk prediction models aima t estimating the risk of patients' mortality, which is the most important and robust outcome measure providing an objective and patient-centered parameter 1,5 . Besides patients' risk prediction, such scoring systems can help to evaluate treatment success or the optimal use of medical resources as well as to compare patients' outcomes between different institutions or in the frame of clinical studies 4, 6 .…”

Applying the Maternal Near Miss Approach for the Evaluation of Quality of Obstetric Care: A Worked Example from a Multicenter Surveillance Study

“…Thus, it is difficult to individually analyze and predict morbidity and mortality outcomes in critically ill patients [1]. Stratification of patient groups according to clinical severity may facilitate interpretation of these results by comparing similar groups [2]. …”