Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2008 Oct;14(5):498-505.
doi: 10.1097/MCC.0b013e3283101643.

Outcome prediction in critical care: the Mortality Probability Models

Affiliations
Review

Outcome prediction in critical care: the Mortality Probability Models

Thomas L Higgins et al. Curr Opin Crit Care. 2008 Oct.

Abstract

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. This article will review the history of the Mortality Probability Model (MPM), discuss why and how it was recently updated, and outline examples of MPM use.

Recent findings: All severity-of-illness models have limitations, especially if a unit's patient population becomes highly specialized. In these situations, customized models may provide better accuracy. The MPMs include those calculated at admission (MPM0) and additional models at 24, 48, and 72 h (MPM 24, MPM 48, and MPM 72). The model is now in its third iteration (MPM 0-III). Length of stay (LOS) and subgroup models have also been developed.

Summary: Understanding appropriate application of models such as MPM is important as transparency in healthcare drives demand for severity-adjusted outcomes data.

PubMed Disclaimer