title: Prediction of hospital mortality rates by admission laboratory tests.
abstract: BACKGROUND
  The aim of this study was to explore whether electronically retrieved laboratory data can predict mortality in internal medicine departments in a regional hospital.
  
  
  METHODS
  All 10,308 patients hospitalized in internal medicine departments over a 1-year period were included in the cohort. Nearly all patients had a complete blood count and basic clinical chemistries on admission. We used logistic regression analysis to predict the 573 deaths (5.6%), including all variables that added significantly to the model.
  
  
  RESULTS
  Eight laboratory variables and age significantly and independently contributed to a logistic regression model (area under the ROC curve, 88.7%). The odds ratio for the final model per quartile of risk was 6.44 (95% confidence interval, 5.42-7.64), whereas for age alone, the odds ratio per quartile was 2.01 (95% confidence interval, 1.84-2.19).
  
  
  CONCLUSIONS
  A logistic regression model including only age and electronically retrieved laboratory data highly predicted mortality in internal medicine departments in a regional hospital, suggesting that age and routine admission laboratory tests might be used to ensure a fair comparison when using mortality monitoring for hospital quality control.
authors.affiliation: Department of Epidemiology and Preventive Medicine, Sackler Medical School, Tel Aviv University, Tel Aviv, Israel. froom@maaganm.co.il
authors.forename: Paul
authors.initials: P
authors.lastname: Froom
authors.forename: Zvi
authors.initials: Z
authors.lastname: Shimoni
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D003955:Diagnostic Tests, Routine / Q000706:statistics & numerical data; D005260:Female; D017052:Hospital Mortality / Q000639:trends*; D006801:Humans; D016015:Logistic Models; D008297:Male; D011237:Predictive Value of Tests