The complexity of disease combinations in the Medicare population.
Developing systems of care that address the mortality, morbidity, and expenditures associated with Medicare beneficiaries with multiple diseases would benefit from a greater understanding of the complexity of disease combinations (DCs) found in the Medicare population. To develop estimates of the number of DCs, we performed an observational analysis on 32,220,634 beneficiaries in the Medicare Fee-for-Service claims database based on a set of records containing each beneficiary's Part A and B International Classification of Diseases, 9(th) Revision, Clinical Modification (ICD-9-CM) claims data for the year of 2008. We made 2 simplifying adjustments. First, we mapped the individual ICD-9-CM codes to the Centers for Medicare and Medicaid Services-Hierarchical Conditions Categories (HCC) model that was developed in 2004 to risk adjust capitation payments to private health care plans based on the health expenditure risk of their enrollees. Second, we aggregated beneficiaries with identical HCCs regardless of the temporal order of these findings within the 2008 claims year; thus the DC to which they are assigned represents the summation of their 2008 claims data. We defined 3 distinct populations at the HCC level. The first consisted of 35% of the beneficiaries who did not fall into any HCC category and accounted for 6% of expenditures. The second was represented by the 100 next most prevalent DCs that accounted for 33% of the beneficiaries and 15% of expenditures. The final population, accounting for 32% of the beneficiaries and 79% of expenses, was complex and consisted of over 2 million DCs. Our results indicate that the majority of expenditures are associated with a complex set of beneficiaries.
Assistant Secretary for Planning and Evaluation, Office of Science and Data Policy, Washington, District of Columbia 20201, USA. james.sorace@hhs.gov
James
J
Sorace
Hui-Hsing
HH
Wong
Chris
C
Worrall
Jeffrey
J
Kelman
Shahin
S
Saneinejad
Thomas
T
MaCurdy
D000368:Aged; D015897:Comorbidity; D016208:Databases, Factual; D005102:Health Expenditures / Q000639:trends*; D006801:Humans; D038801:International Classification of Diseases; D006278:Medicare / Q000191:economics*; D014481:United States