title: Using routine blood test results to predict the risk of death for emergency medical admissions to hospital: an external model validation study.
abstract: BACKGROUND
  The Biochemistry and Haematology Outcome Model (BHOM) relies on the results from routine index blood tests to predict the patient risk of death. We aimed to externally validate the BHOM model.
  
  
  METHODS
  We considered all emergency adult medical patients who were discharged from Northern Lincolnshire and Goole (NLAG) hospital in 2014. We compared patient characteristics between NLAG (the validation sample) and the hospital where BHOM was developed. We evaluated the predictive performance, according to discriminative ability (with a concordance statistic, c), and calibration (agreement between observed and predicted risk).
  
  
  RESULTS
  There were 29 834 emergency discharges of which 24 696 (83%) had complete data. In comparison with the development sample, the NLAG sample was similar in age, blood test results, but experienced a lower mortality (4.7 vs. 8.7%). When applied to NLAG, the BHOM model had good discrimination (c-statistic 0.83 [95% CI 0.823-0.842]). Calibration was good overall, although the BHOM model overpredicted for lowest (<5%, observed = 229, predicted = 286) and highest (≥50%, observed = 31, predicted = 49) risk groups, even after recalibrating for the differences in baseline risk of death.
  
  
  CONCLUSIONS
  Differences in patient case-mix profile and baseline risk of death need to be considered before the BHOM model can be used in another hospital. After re-calibrating for the baseline difference in risk the BHOM model had good discrimination but less adequate calibration.
authors.affiliation: From the Faculty of Health Studies, University of Bradford, Bradford, UK.|Bradford Teaching Hospitals NHS Foundation Trust Bradford Institute for Health Research, Bradford, UK.
authors.forename: M
authors.initials: M
authors.lastname: Faisal
authors.affiliation: Northern Lincolnshire and Goole NHS Foundation, Diana, Princess of Wales Hospital, Grimsby, North East Lincolnshire, UK.
authors.forename: R
authors.initials: R
authors.lastname: Howes
authors.affiliation: Department of Public Health, Erasmus University, Rotterdam, The Netherlands.
authors.forename: E W
authors.initials: EW
authors.lastname: Steyerberg
authors.affiliation: Department of Renal Medicine, York District Hospital, York, UK.
authors.forename: D
authors.initials: D
authors.lastname: Richardson
authors.affiliation: From the Faculty of Health Studies, University of Bradford, Bradford, UK.|Bradford Teaching Hospitals NHS Foundation Trust Bradford Institute for Health Research, Bradford, UK.
authors.forename: M A
authors.initials: MA
authors.lastname: Mohammed
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D004636:Emergency Service, Hospital; D005260:Female; D006403:Hematologic Tests; D017052:Hospital Mortality; D006760:Hospitalization; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D018570:Risk Assessment / Q000379:methods