title: Risk adjusted mortality after hip replacement surgery: a retrospective study.
abstract: BACKGROUND
  Hip replacement (HR) operations are increasing. Short term mortality is an indicator of quality; few studies include risk adjustment models to predict HR outcomes. We evaluated in-hospital and 30-day mortality in hospitalized patients for HR and compared the performance of two risk adjustment algorithms.
  
  
  METHODS
  A retrospective cohort study on hospital discharge records of patients undergoing HR from 2000 to 2005 in Tuscany Region, Italy, applied All-Patient Refined Diagnosis Related Groups (APR-DRG) and Elixhauser Index (EI) risk adjustment models to predict outcomes. Logistic regression was used to analyse the performance of the two models; C statistic (C) was used to define their discriminating ability.
  
  
  RESULTS
  25 850 hospital discharge records were studied. In-hospital and 30-day crude mortality were 1.3% and 3%, respectively. Female gender was a significant (p < 0.001) protective factor under both models and had the following Odds Ratios (OR): 0.64 for in-hospital and 0.51 for 30-day mortality using APR-DRG and 0.55 and 0.48, respectively, with EI. Among EI comorbidities, heart failure and liver disease were associated with in-hospital (OR 9.29 and 5.60; p < 0.001) and 30-day (OR 6.36 and 3.26; p < 0.001) mortality. Increasing age and APR-DRG risk class were predictive of all the outcomes. Discriminating ability for in-hospital and 30-day mortality was reasonable with EI (C 0.79 and 0.68) and good with APR-DRG (C 0.86 and 0.82).
  
  
  CONCLUSIONS
  Our study found that gender, age, EI comorbidities and APR-DRG risk of death are predictive factors of in-hospital and 30-day mortality outcomes in patients undergoing HR. At least one risk adjustment algorithm should always be implemented in patient management.
authors.affiliation: Dipartimento di Medicina Molecolare e dello Sviluppo, Università degli Studi di Siena, Siena, Italy.
authors.forename: Gabriele
authors.initials: G
authors.lastname: Messina
authors.affiliation: Agenzia Regionale di Sanità della Toscana, Florence, Italy.
authors.forename: Silvia
authors.initials: S
authors.lastname: Forni
authors.affiliation: Scuola di Specializzazione in Igiene e Medicina Preventiva, Università degli Studi di Siena, Siena, Italy.
authors.forename: Daniele
authors.initials: D
authors.lastname: Rosadini
authors.affiliation: Agenzia Regionale di Sanità della Toscana, Florence, Italy.
authors.forename: Manuele
authors.initials: M
authors.lastname: Falcone
authors.affiliation: Agenzia Regionale di Sanità della Toscana, Florence, Italy.
authors.forename: Francesca
authors.initials: F
authors.lastname: Collini
authors.affiliation: Dipartimento di Medicina Molecolare e dello Sviluppo, Università degli Studi di Siena, Siena, Italy.
authors.forename: Nicola
authors.initials: N
authors.lastname: Nante
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D019644:Arthroplasty, Replacement, Hip / Q000401:mortality*; D015331:Cohort Studies; D015897:Comorbidity; D005260:Female; D006801:Humans; D007558:Italy / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies; D020379:Risk Adjustment; D012737:Sex Factors