The Complexity of Disease Combinations in the Medicare Population
Assistant Secretary for Planning and Evaluation, Office of Science and Data Policy, Washington, District of Columbia 20201, USA.Population Health Management (Impact Factor: 1.51). 08/2011; 14(4):161-6. DOI: 10.1089/pop.2010.0044
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.
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ABSTRACT: To determine patterns of co-occurring diseases in older adults and the extent to which these patterns vary between the young-old and the old-old. Observational study. Department of Veterans Affairs. Veterans aged 65 years and older (1.9 million male, mean age 76 ± 7; 39,000 female, mean age 77 ± 8) with two or more visits to Department of Veterans Affairs (VA) or Medicare settings in 2007 and 2008. The presence of 23 common conditions was assessed using hospital discharge diagnoses and outpatient encounter diagnoses from the VA and Medicare. The mean number of chronic conditions (out of 23 possible) was 5.5 ± 2.6 for men and 5.1 ± 2.6 for women. The prevalence of most conditions increased with advancing age, although diabetes mellitus and hyperlipidemia were 11% to 13% less prevalent in men and women aged 85 and older than in those aged 65 to 74 (P < .001 for each). In men, the most common three-way combination of conditions was hypertension, hyperlipidemia, and coronary heart disease, which together were present in 37% of men. For women, the most common combination was hypertension, hyperlipidemia, and arthritis, which co-occurred in 25% of women. Reflecting their high population prevalence, hypertension and hyperlipidemia were both present in 9 of the 15 most common three-way disease combinations in men and in 11 of the 15 most common combinations in women. The prevalence of many disease combinations varied substantially between young-old and old-old adults. Specific combinations of diseases are highly prevalent in older adults and inform the development of guidelines that account for the simultaneous presence of multiple chronic conditions.
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ABSTRACT: Abstract 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. (Population Health Management 2013;16:XX-XX).
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ABSTRACT: Older adults with multiple chronic conditions (MCCs) require considerable health services and complex care. Because the persistence and progression of diseases and courses of treatments affect health status in multiple dimensions, well-validated universal outcome measures across diseases are needed for research, clinical care, and administrative purposes. An expert panel meeting held by the National Institute on Aging in September 2011 recommends that older persons with MCCs complete a brief initial composite measure that includes general health; pain; fatigue; and physical health, mental health, and social role function, along with gait speed measurement. Suitable composite measures include the Medical Outcomes Study 8 (SF-8) and 36 (SF-36) -item Short-Form Survey and the Patient Reported Outcomes Measurement Information System 29-item Health Profile. Based on responses to items in the initial measure, short follow-on measures should be selectively targeted to symptom burden, depression, anxiety, and daily activities. Persons unable to walk a short distance to assess gait speed should be assessed using a physical function scale. Remaining gaps to be considered for measure development include disease burden, cognitive function, and caregiver burden. Routine outcome assessment of individuals with MCCs could facilitate system-based care improvement and clinical effectiveness research. J Am Geriatr Soc 60: 2333-2341, 2012.
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