Assistant Secretary for Planning and Evaluation, Office of Science and Data Policy, Washington, District of Columbia 20201, USA.
Popul Health Manag. 2011 Aug;14(4):161-6. doi: 10.1089/pop.2010.0044. Epub 2011 Jan 17.
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.
开发针对患有多种疾病的医疗保险受益人的死亡率、发病率和支出的护理系统，将得益于更深入地了解医疗保险人群中发现的疾病组合（DC）的复杂性。为了估计 DC 的数量，我们对 Medicare Fee-for-Service 索赔数据库中的 32220634 名受益人的数据进行了观察性分析，该数据库基于一组记录，其中包含每个受益人的 Medicare 部分 A 和 B 的 ICD-9-CM 索赔数据，记录年份为 2008 年。我们进行了两项简化调整。首先，我们将单个 ICD-9-CM 编码映射到 2004 年开发的 Medicare 和 Medicaid Services-Hierarchical Conditions Categories (HCC) 模型，该模型根据其参保人的医疗支出风险，为私人医疗保健计划的人头费调整风险。其次，我们汇总了具有相同 HCC 的受益人，而不论他们在 2008 年索赔年度内发现这些 HCC 的时间顺序如何；因此，他们被分配的 DC 代表他们 2008 年索赔数据的总和。我们在 HCC 级别定义了三个不同的人群。第一组占受益人的 35%，他们不属于任何 HCC 类别，占支出的 6%。第二组由 100 个最常见的 DC 组成，占受益人的 33%，占支出的 15%。最后一组占受益人的 32%，占支出的 79%，人群非常复杂，由超过 200 万个 DC 组成。我们的结果表明，大部分支出与一组复杂的受益人群有关。
