title: Comparing Time-Fixed Mortality Prediction Models and Their Effect on ICU Performance Metrics Using the Simplified Acute Physiology Score 3.
abstract: OBJECTIVE
  To examine ICU performance based on the Simplified Acute Physiology Score 3 using 30-day, 90-day, or 180-day mortality as outcome measures and compare results with 30-day mortality as reference.
  
  
  METHODS
  Retrospective cohort study of ICU admissions from 2010 to 2014.
  
  
  METHODS
  Sixty-three Swedish ICUs that submitted data to the Swedish Intensive Care Registry.
  
  
  METHODS
  The development cohort was first admissions to ICU during 2011-2012 (n = 53,546), and the validation cohort was first admissions to ICU during 2013-2014 (n = 57,729).
  
  
  METHODS
  None.
  
  
  RESULTS
  Logistic regression was used to develop predictive models based on a first level recalibration of the original Simplified Acute Physiology Score 3 model but with 30-day, 90-day, or 180-day mortality as measures of outcome. Discrimination and calibration were excellent for the development dataset. Validation in the more recent 2013-2014 database showed good discrimination (C-statistic: 0.85, 0.84, and 0.83 for the 30-, 90-, and 180-d models, respectively), and good calibration (standardized mortality ratio: 0.99, 0.99, and 1.00; Hosmer-Lemeshow goodness of fit H-statistic: 66.4, 63.7, and 81.4 for the 30-, 90-, and 180-d models, respectively). There were modest changes in an ICU's standardized mortality ratio grouping (< 1.00, not significant, > 1.00) when follow-up was extended from 30 to 90 days and 180 days, respectively; about 11-13% of all ICUs.
  
  
  CONCLUSIONS
  The recalibrated Simplified Acute Physiology Score 3 hospital outcome prediction model performed well on long-term outcomes. Evaluation of ICU performance using standardized mortality ratio was only modestly sensitive to the follow-up time. Our results suggest that 30-day mortality may be a good benchmark of ICU performance. However, the duration of follow-up must balance between what is most relevant for patients, most affected by ICU care, least affected by administrative policies and practically feasible for caregivers.
authors: 1Department of Anesthesiology and Intensive Care, Vrinnevisjukhuset, Norrköping, Sweden. 2Department of Medical and Health Sciences, Faculty of Health Sciences, Linköping University, Sweden. 3Department of Cardiothoracic and Vascular Surgery, Linköping University Hospital, Linköping, Sweden. 4Prescient Healthcare Consulting, Charlottesville, VA. 5The Swedish Intensive Care Registry, Karlstad, Sweden. 6Department of Hand Surgery, Plastic Surgery and Burns, Linköping University Hospital, Linköping, Sweden. 7Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden. 8Linköping Academic Research Center, Linköping University, Linköping, Sweden.
authors: Lars
authors: L
authors: Engerström
authors: Andrew A
authors: AA
authors: Kramer
authors: Thomas
authors: T
authors: Nolin
authors: Folke
authors: F
authors: Sjöberg
authors: Göran
authors: G
authors: Karlström
authors: Mats
authors: M
authors: Fredrikson
authors: Sten M
authors: SM
authors: Walther
mesh_terms: D000368:Aged; D019985:Benchmarking; D015331:Cohort Studies; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care; D012189:Retrospective Studies; D000072878:Simplified Acute Physiology Score; D013548:Sweden