| Summary: | Measures of morbidity and comorbidity are frequently used for the control of confounding, particularly in health services research. Several proposals for those measures are defined with ICD-coded diagnoses available in hospital routine data. However, a measure that makes use of the ICD structure is missing. Objective of this work was to elaborate the power of the ICD structure for defining morbidity and comorbidity measures. Routine data from three German hospitals with inpatients discharged 2008 were used for model development; routine data from 36 German hospitals with inpatients admitted and discharged 2010 were used for model evaluation. Two different risk models were developed, one based on ICD-10 chapters, the other based on ICD-10 groups. The models were transformed into sum scores using whole-number weights. Models and scores were compared with the Charlson Index and the Elixhauser Comorbidities using the receiver operating characteristic. Dependent variable was hospital death. Logistic regression was used to derive the new models. Charlson Index and Elixhauser Comorbidities were mapped to the German ICD-10. According to the receiver operating characteristic, the quality of the measures based on the structure of the ICD-10 was superior compared with the Charlson Index and the Elixhauser Comorbidities. The best result was achieved with the measure based on ICD-10-groups with an area under curve of 0.910 (95% confidence interval = 0.907-0.913). The sum scores showed a comparable performance. The developed new measures may be used to control for confounding.
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