title: Development of 2 registry-based risk models suitable for characterizing hospital performance on 30-day all-cause mortality rates among patients undergoing percutaneous coronary intervention.
abstract: BACKGROUND
  Variation in outcomes after percutaneous coronary interventions (PCI) may reflect differences in quality of care. To date, however, we lack a methodology to monitor and improve national hospital 30-day mortality rates among patients undergoing PCI.
  
  
  RESULTS
  We developed hierarchical logistic regression models to calculate hospital risk-standardized 30-day all-cause PCI mortality rates. Due to differences in risk, patients were divided into 2 cohorts: those with ST-segment elevation myocardial infarction or cardiogenic shock, and those with no ST-segment elevation myocardial infarction and no cardiogenic shock. The models were derived using 2006 data from the CathPCI Registry linked with administrative claims data, and validated using comparable 2005 data. In the derivation cohort of the ST-segment elevation myocardial infarction or shock model (n=15 123), the unadjusted 30-day mortality rate was 9.2%. The final model included 13 variables with the observed mortality rates ranging from 1.4% to 40.3% across deciles of the predicted patient mortality rates. The 25th and 75th percentiles of the risk-standardized mortality rate were 8.5% and 9.7%, with 5th and 95th percentiles of 7.6% and 11.0%. In the derivation cohort of the no ST-segment elevation myocardial infarction and no shock model (n=110 529), the unadjusted 30-day mortality rate was 1.4%. The final model included 16 variables with the observed predicted mortality rates ranging from 0.1% to 7.0% across deciles of the predicted patient mortality rates. The 25th and 75th percentiles of the risk-standardized mortality rate across 612 hospitals were 1.3% and 1.6%, with 5th and 95th percentiles of 1.0% and 2.0%.
  
  
  CONCLUSIONS
  These National Quality Forum endorsed registry-based models produce estimates of hospital risk-standardized mortality rates for patients undergoing PCI.
authors.affiliation: Department of Internal Medicine, Section of Cardiovascular Medicine, Yale University School of Medicine, New Haven, CT, USA. jeptha.curtis@yale.edu
authors.forename: Jeptha P
authors.initials: JP
authors.lastname: Curtis
authors.forename: Lori L
authors.initials: LL
authors.lastname: Geary
authors.forename: Yongfei
authors.initials: Y
authors.lastname: Wang
authors.forename: Jersey
authors.initials: J
authors.lastname: Chen
authors.forename: Elizabeth E
authors.initials: EE
authors.lastname: Drye
authors.forename: Laura M
authors.initials: LM
authors.lastname: Grosso
authors.forename: John A
authors.initials: JA
authors.lastname: Spertus
authors.forename: John S
authors.initials: JS
authors.lastname: Rumsfeld
authors.forename: William S
authors.initials: WS
authors.lastname: Weintraub
authors.forename: Frederick A
authors.initials: FA
authors.lastname: Masoudi
authors.forename: Ralph G
authors.initials: RG
authors.lastname: Brindis
authors.forename: Harlan M
authors.initials: HM
authors.lastname: Krumholz
mesh_terms: D054058:Acute Coronary Syndrome / Q000401:mortality / Q000628:therapy; D000368:Aged; D000369:Aged, 80 and over; D000787:Angina Pectoris / Q000401:mortality / Q000628:therapy; D016009:Chi-Square Distribution; D015897:Comorbidity; D005260:Female; D006331:Heart Diseases / Q000401:mortality / Q000628:therapy*; D017052:Hospital Mortality; D006761:Hospitals / Q000592:standards*; D006801:Humans; D016015:Logistic Models; D008297:Male; D009203:Myocardial Infarction / Q000401:mortality / Q000628:therapy; D016017:Odds Ratio; D010043:Outcome and Process Assessment, Health Care / Q000592:standards*; D062645:Percutaneous Coronary Intervention / Q000401:mortality*; D019984:Quality Indicators, Health Care / Q000592:standards*; D012042:Registries; D018570:Risk Assessment; D012307:Risk Factors; D012770:Shock, Cardiogenic / Q000401:mortality / Q000628:therapy; D013997:Time Factors; D016896:Treatment Outcome; D014481:United States