title: National administrative data produces an accurate and stable risk prediction model for short-term and 1-year mortality following cardiac surgery.
abstract: OBJECTIVE
  Various risk models exist to predict short-term risk-adjusted outcomes after cardiac surgery. Statistical models constructed using clinical registry data usually perform better than those based on administrative datasets. We constructed a procedure-specific risk prediction model based on administrative hospital data for England and we compared its performance with the EuroSCORE (ES) and its variants.
  
  
  METHODS
  The Hospital Episode Statistics (HES) risk prediction model was developed using administrative data linked to national mortality statistics register of patients undergoing CABG (35,115), valve surgery (18,353) and combined CABG and valve surgery (8392) from 2008 to 2011 in England and tested using an independent dataset sampled for the financial years 2011-2013. Specific models were constructed to predict mortality within 1-year post discharge. Comparisons with EuroSCORE models were performed on a local cohort of patients (2580) from 2008 to 2013.
  
  
  RESULTS
  The discrimination of the HES model demonstrates a good performance for early and up to 1-year following surgery (c-stats: CABG 81.6%, 78.4%; isolated valve 78.6%, 77.8%; CABG & valve 76.4%, 72.0%), respectively. Extended testing in subsequent financial years shows that the models maintained performance outside the development period. Calibration of the HES model demonstrates a small difference (CABG 0.15%; isolated valve 0.39%; CABG & valve 0.63%) between observed and expected mortality rates and delivers a good estimate of risk. Discrimination for the HES model for in-hospital deaths is similar for CABG (logistic ES 79.0%) and combined CABG and valve surgery (logistic ES 71.6%) patients and superior for valve patients (logistic ES 70.9%) compared to the EuroSCORE models. The C-statistics of the EuroSCORE models for longer periods are numerically lower than that of the HES model.
  
  
  CONCLUSIONS
  The national administrative dataset has produced an accurate, stable and clinically useful early and 1-year mortality prediction after cardiac surgery.
authors.affiliation: Quality and Outcomes Research Unit, University Hospital Birmingham, UK; Department Cardiothoracic Surgery, University Hospital Birmingham, UK.
authors.forename: Dincer
authors.initials: D
authors.lastname: Aktuerk
authors.affiliation: Quality and Outcomes Research Unit, University Hospital Birmingham, UK.
authors.forename: David
authors.initials: D
authors.lastname: McNulty
authors.affiliation: Quality and Outcomes Research Unit, University Hospital Birmingham, UK.
authors.forename: Daniel
authors.initials: D
authors.lastname: Ray
authors.affiliation: Quality and Outcomes Research Unit, University Hospital Birmingham, UK.
authors.forename: Irena
authors.initials: I
authors.lastname: Begaj
authors.affiliation: Department Cardiothoracic Surgery, University Hospital Birmingham, UK.
authors.forename: Neil
authors.initials: N
authors.lastname: Howell
authors.affiliation: Quality and Outcomes Research Unit, University Hospital Birmingham, UK; Department of Primary Care and Population Health, University College London, UK.
authors.forename: Nick
authors.initials: N
authors.lastname: Freemantle
authors.affiliation: Quality and Outcomes Research Unit, University Hospital Birmingham, UK; Department Cardiothoracic Surgery, University Hospital Birmingham, UK. Electronic address: domenico.pagano@uhb.nhs.uk.
authors.forename: Domenico
authors.initials: D
authors.lastname: Pagano
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D006348:Cardiac Surgical Procedures / Q000401:mortality*; D004739:England; D005260:Female; D006751:Hospital Information Systems; D017052:Hospital Mortality; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011379:Prognosis; D015203:Reproducibility of Results; D018570:Risk Assessment; D013997:Time Factors; D055815:Young Adult
keywords: Administrative database; Cardiac surgery; EuroSCORE; Prediction; Risk model