title: Risk-standardizing survival for in-hospital cardiac arrest to facilitate hospital comparisons.
abstract: OBJECTIVE
  The purpose of this study is to develop a method for risk-standardizing hospital survival after cardiac arrest.
  
  
  BACKGROUND
  A foundation with which hospitals can improve quality is to be able to benchmark their risk-adjusted performance against other hospitals, something that cannot currently be done for survival after in-hospital cardiac arrest.
  
  
  METHODS
  Within the Get With The Guidelines (GWTG)-Resuscitation registry, we identified 48,841 patients admitted between 2007 and 2010 with an in-hospital cardiac arrest. Using hierarchical logistic regression, we derived and validated a model for survival to hospital discharge and calculated risk-standardized survival rates (RSSRs) for 272 hospitals with at least 10 cardiac arrest cases.
  
  
  RESULTS
  The survival rate was 21.0% and 21.2% for the derivation and validation cohorts, respectively. The model had good discrimination (C-statistic 0.74) and excellent calibration. Eighteen variables were associated with survival to discharge, and a parsimonious model contained 9 variables with minimal change in model discrimination. Before risk adjustment, the median hospital survival rate was 20% (interquartile range: 14% to 26%), with a wide range (0% to 85%). After adjustment, the distribution of RSSRs was substantially narrower: median of 21% (interquartile range: 19% to 23%; range 11% to 35%). More than half (143 [52.6%]) of hospitals had at least a 10% positive or negative absolute change in percentile rank after risk standardization, and 50 (23.2%) had a ≥20% absolute change in percentile rank.
  
  
  CONCLUSIONS
  We have derived and validated a model to risk-standardize hospital rates of survival for in-hospital cardiac arrest. Use of this model can support efforts to compare hospitals in resuscitation outcomes as a foundation for quality assessment and improvement.
authors.affiliation: Saint Luke's Mid America Heart Institute, Kansas City, Missouri; University of Missouri, Kansas City, Missouri 64111, USA. pchan@cc-pc.com
authors.forename: Paul S
authors.initials: PS
authors.lastname: Chan
authors.forename: Robert A
authors.initials: RA
authors.lastname: Berg
authors.forename: John A
authors.initials: JA
authors.lastname: Spertus
authors.forename: Lee H
authors.initials: LH
authors.lastname: Schwamm
authors.forename: Deepak L
authors.initials: DL
authors.lastname: Bhatt
authors.forename: Gregg C
authors.initials: GC
authors.lastname: Fonarow
authors.forename: Paul A
authors.initials: PA
authors.lastname: Heidenreich
authors.forename: Brahmajee K
authors.initials: BK
authors.lastname: Nallamothu
authors.forename: Fengming
authors.initials: F
authors.lastname: Tang
authors.forename: Raina M
authors.initials: RM
authors.lastname: Merchant
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D016887:Cardiopulmonary Resuscitation / Q000379:methods / Q000401:mortality*; D005260:Female; D006323:Heart Arrest / Q000401:mortality* / Q000628:therapy*; D017052:Hospital Mortality / Q000639:trends*; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D011787:Quality of Health Care; D012042:Registries; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment; D012308:Risk Management / Q000592:standards*; D012737:Sex Factors; D016019:Survival Analysis; D014481:United States
keywords: AHA; American Heart Association; DNR; GWTG; Get With The Guidelines; cardiac arrest; do not resuscitate; risk adjustment; variation in care