BACKGROUND: The Charlson and Elixhauser comorbidity measures are commonly used methods to account for patient comorbidities in hospital-level comparisons of clinical quality using administrative data. Both have been validated in North America, but there is less evidence of their performance in Europe and in pooled cross-country data, which are features of the European Collaboration for Healthcare Optimization (ECHO) project. This study compares the performance of the Charlson/Deyo and Elixhauser comorbidity measures in predicting in-hospital mortality using data from five European countries in three inpatient groups.
METHODS: Administrative data is used from five countries in 2008-2009 for three indicators commonly used in hospital quality comparisons: mortality rates following acute myocardial infarction, coronary artery bypass graft surgery and stroke. Logistic regression models are constructed to predict mortality controlling for age, gender and the relevant comorbidity measure. Model discrimination is evaluated using c-statistics. Model calibration is evaluated using calibration slopes. Overall goodness-of-fit is evaluated using Nagelkerke's R(2) and the Akaike information criterion. All models are validated internally by using bootstrapping and externally by using the 2009 model parameters to predict mortality in 2008.
RESULTS: The Elixhauser measure has better overall predictive ability in terms of discrimination and goodness-of-fit than the Charlson/Deyo measure or the age-sex only model. There is no clear difference in model calibration. These findings are robust to the choice of country, to pooling all five countries and to internal and external validation.
CONCLUSIONS: The Elixhauser list contains more comorbidities, which may enable it to achieve better discrimination than the Charlson measure. Both measures achieve similar calibration, so for the purpose of ECHO we judged the Elixhauser measure to be preferable.
|Number of pages||6|
|Journal||European Journal of Public Health|
|Issue number||Suppl 1|
|Publication status||Published - Feb 2015|