It is widely accepted that Medicare beneficiaries with multiple comorbidities (ie, patients with combinations of more than 1 disease) account for a disproportionate amount of mortality and expenditures. The authors previously studied this phenomenon by analyzing Medicare claims data from 2008 to determine the pattern of disease combinations (DCs) for 32,220,634 beneficiaries. Their findings indicated that 22% of these individuals mapped to a long-tailed distribution of approximately 1 million DCs. The presence of so many DCs, each populated by a small number of individuals, raises the possibility that the DC distribution varies over time. Measuring this variability is important because it indicates the rate at which the health care system must adapt to the needs of new patients. This article analyzes Medicare claims data for 3 consecutive calendar years, using 2 algorithms based on the Centers for Medicare & Medicaid Services (CMS)-Hierarchical Conditions Categories (HCC) claims model. These algorithms make different assumptions regarding the degree to which the CMS-HCC model could be disaggregated into its underlying International Classification of Diseases, Ninth Revision, Clinical Modification codes. The authors find that, although a large number of beneficiaries belong to a set of DCs that are nationally stable across the 3 study years, the number of DCs in this set is large (in the range of several hundred thousand). Furthermore, the small number of beneficiaries associated with the larger number of variable DCs (ie, DCs that were not constantly populated in all 3 study years) represents a disproportionally high level of expenditures and death.