Search

Background: Cross-country comparisons of socioeconomic equity in health care typically use sample survey data on general services such as physician visits. This study uses comprehensive administrative data on a specific service: hip replacement. Methods: We analyse 651 652 publicly funded hip replacements, excluding fractures and accidents, in adults over 35 in Denmark, England, Portugal and Spain from 2002 to 2009. Sub-national administrative areas are split into socioeconomic quintile groups comprising approximately one-fifth of the national population. Area-level Poisson regression with Huber-White standard errors is used to calculate age-sex standardised hip replacement rates by quintile group, together with gaps and ratios between richest and poorest groups (Q5 and Q1) and the middle group (Q3). Results: We find pro-rich-area inequality in England (2009 Q5/Q1 ratio 1.35 [CI 1.25–1.45]) and Spain (2009 Q5/Q1 ratio 1.43 [CI 1.17–1.70]), pro-poor-area inequality in Portugal (2009 Q5/Q1 ratio 0.67 [CI 0.50–0.83]) and no significant inequality in Denmark. Pro-rich-area inequality increased over time in England and Spain but not significantly. Within-country differences between socioeconomic quintile groups are smaller than between-country differences in general population averages: hip replacement rates are substantially lower in Portugal and Spain (8.6 and 7.4 per 10 000 in 2009) than England and Denmark (20.2 and 27.8 per 10 000 in 2009). Conclusion: Despite limitations regarding individual-level inequality and area heterogeneity, analysis of area-level data on publicly funded hospital activity can provide useful cross-country comparisons and longitudinal monitoring of socioeconomic inequality in specific health services. Although this kind of analysis cannot provide definitive answers, it can raise important questions for decision makers. [ABSTRACT FROM AUTHOR]

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 R2 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. [ABSTRACT FROM AUTHOR]