title: Outcome prediction in critical care: the Mortality Probability Models.
abstract: OBJECTIVE
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  Understanding appropriate application of models such as MPM is important as transparency in healthcare drives demand for severity-adjusted outcomes data.
authors.affiliation: Baystate Medical Center, Critical Care Division, Springfield, MA, USA. thomas.higgins@bhs.org
authors.forename: Thomas L
authors.initials: TL
authors.lastname: Higgins
authors.forename: Daniel
authors.initials: D
authors.lastname: Teres
authors.forename: Brian
authors.initials: B
authors.lastname: Nathanson
mesh_terms: D018806:APACHE; D003422:Critical Care; D005544:Forecasting; D017052:Hospital Mortality; D006801:Humans; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000379:methods*; D012720:Severity of Illness Index