title: Cross-national comparative performance of three versions of the ICD-10 Charlson index.
abstract: OBJECTIVE
  The Charlson comorbidity index has been widely used for risk adjustment in outcome studies using administrative health data. Recently, 3 International Statistical Classification of Diseases, Tenth Revision (ICD-10) translations have been published for the Charlson comorbidities. This study was conducted to compare the predictive performance of these versions (the Halfon, Sundararajan, and Quan versions) of the ICD-10 coding algorithms using data from 4 countries.
  
  
  METHODS
  Data from Australia (N = 2000-2001, max 25 diagnosis codes), Canada (N = 2002-2003, max 16 diagnosis codes), Switzerland (N = 1999-2001, unlimited number of diagnosis codes), and Japan (N = 2003, max 11 diagnosis codes) were analyzed. Only the first admission for patients age 18 years and older, with a length of stay of >/=2 days was included. For each algorithm, 2 logistic regression models were fitted with hospital mortality as the outcome and the Charlson individual comorbidities or the Charlson index score as independent variables. The c-statistic (representing the area under the receiver operating characteristic curve) and its 95% probability bootstrap distribution were employed to evaluate model performance.
  
  
  RESULTS
  Overall, within each population's data, the distribution of comorbidity level categories was similar across the 3 translations. The Quan version produced slightly higher median c-statistics than the Halfon or Sundararajan versions in all datasets. For example, in Japanese data, the median c-statistics were 0.712 (Quan), 0.709 (Sundararajan), and 0.694 (Halfon) using individual comorbidity coefficients. In general, the probability distributions between the Quan and the Sundararajan versions overlapped, whereas those between the Quan and the Halfon version did not.
  
  
  CONCLUSIONS
  Our analyses show that all of the ICD-10 versions of the Charlson algorithm performed satisfactorily (c-statistics 0.70-0.86), with the Quan version showing a trend toward outperforming the other versions in all data sets.
authors.affiliation: Victorian Department of Human Servicest, Royal Melbourne Hospital, Australia. vijaya.sundararajan@dhs.vic.gov.au
authors.forename: Vijaya
authors.initials: V
authors.lastname: Sundararajan
authors.forename: Hude
authors.initials: H
authors.lastname: Quan
authors.forename: Patricia
authors.initials: P
authors.lastname: Halfon
authors.forename: Kiyohide
authors.initials: K
authors.lastname: Fushimi
authors.forename: Jean-Christophe
authors.initials: JC
authors.lastname: Luthi
authors.forename: Bernard
authors.initials: B
authors.lastname: Burnand
authors.forename: William A
authors.initials: WA
authors.lastname: Ghali
mesh_terms: D015897:Comorbidity; D017052:Hospital Mortality; D006801:Humans; D038801:International Classification of Diseases / Q000458:organization & administration*; D007802:Language; D008875:Middle Aged; D011237:Predictive Value of Tests; D020379:Risk Adjustment