title: Risk-adjustment model in health outcomes evaluation: a contribution to strengthen assessment towards quality improvement in interventional cardiology.
abstract: OBJECTIVE
  The aim of this study was to develop a risk adjustment model for major adverse cardiac and cerebrovascular events following percutaneous coronary intervention (PCI), using data from a national registry, and to highlight the use of the risk adjustment when we evaluate the quality of care in interventional cardiology.
  
  
  METHODS
  The
  
  
  METHODS
  was based on a Coorte study. Bivariate and multivariate logistic regression models were used to identify independent risk factors for these major adverse events.
  
  
  METHODS
  A total of 19 hospitals from the Portuguese National Registry of Interventional Cardiology.
  
  
  METHODS
  Data from 10.641 consecutives procedures collected between June 30, 2003 and June 30, 2006.
  
  
  METHODS
  Build a risk adjustment model for these major adverse events, following percutaneous coronary intervention.
  
  
  METHODS
  Factors that were associated with major adverse cardiac and cerebrovascular events following percutaneous coronary intervention.
  
  
  RESULTS
  The rate of in-hospital major adverse cardiac and cerebrovascular events was 1.9%. Factors associated with major adverse cardiac and cerebrovascular events included, among others: age >80 years (adjusted odds ratio = 3.91); female gender (1.72); and cardiogenic shock (6.05). Overall, a good discrimination was achieved with receiver operating characteristics curve = 0.84 and Hosmer-Lemeshow goodness of fit statistic across groups of risk was not significant (P = 0.18) indicating little departure from a perfect fit.
  
  
  CONCLUSIONS
  These findings will represent an important contribution to quality and safety improvement and should help driving new research and innovative approaches to different subgroups of patients who have higher chances of having an adverse event or poorer outcomes following this intervention.
authors.affiliation: School of Health Technologies of Lisbon, Lisbon, Portugal. paulo.sousa@ensp.unl.pt
authors.forename: Paulo
authors.initials: P
authors.lastname: Sousa
authors.forename: António Sousa
authors.initials: AS
authors.lastname: Uva
authors.forename: Fausto
authors.initials: F
authors.lastname: Pinto
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002309:Cardiology / Q000592:standards*; D002318:Cardiovascular Diseases / Q000601:surgery; D016208:Databases, Factual; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D017063:Outcome Assessment, Health Care; D011174:Portugal; D011785:Quality Assurance, Health Care / Q000379:methods*; D012044:Regression Analysis; D012189:Retrospective Studies; D020379:Risk Adjustment