Comorbidity, additional disease beyond the condition under study that increases a patient's total burden of illness, is one dimension of health status. For investigators working with observational data obtained from administrative databases, comorbidity assessment may be a useful and important means of accounting for differences in patients' underlying health status. There are multiple ways of measuring comorbidity. This paper provides an overview of current approaches to and issues in assessing comorbidity using claims data, with a particular focus on established indices and the SEER-Medicare database. In addition, efforts to improve measurement of comorbidity using claims data are described, including augmentation of claims data with medical record, patient self-report, or health services utilization data; incorporation of claims data from sources other than inpatient claims; and exploration of alternative conditions, indices, or ways of grouping conditions. Finally, caveats about claims data and areas for future research in claims-based comorbidity assessment are discussed. Although the use of claims databases such as SEER-Medicare for health services and outcomes research has become increasingly common, investigators must be cognizant of the limitations of comorbidity measures derived from these data sources in capturing and controlling for differences in patient health status. The assessment of comorbidity using claims data is a complex and evolving area of investigation.