RTI International, Waltham, MA 02451-1623, USA.
Med Care. 2012 Dec;50(12):1102-8. doi: 10.1097/MLR.0b013e318269eb20.
The continued success of the Medicare Part D program is contingent on appropriate Medicare payment adjustments for the projected drug costs of Part D plan enrollees. This article describes a major revision of these "risk adjustments," intended to more accurately match payments to costs, especially for high-cost, disadvantaged populations.
For the first time actual Part D data are used to calibrate risk adjustment. The sample is Medicare beneficiaries with fee-for-service enrollment in 2007 and Part D standalone prescription drug plan enrollment in 2008 (N = 14,224,301). Part D plan liability expenditures are predicted using demographic and diagnostic factors in a weighted least squares regression. Models for Medicare subpopulations are analyzed. The predictive accuracy of risk adjustment models is evaluated using R and predictive ratio statistics.
Based on differences in both mean expenditures and incremental expenditures by diagnosis, separate Part D risk adjustment models are calibrated for 5 Medicare subpopulations: aged not low income; aged low income; nonaged not low income; nonaged low income; and institutionalized. The variation in plan liability drug expenditures (R) explained by these models ranges from 13% to 29%. The 5 separate models accurately predict mean plan liability expenditures ranging from $967 to $1762 across subpopulations and account for differences in incremental disease coefficients by subpopulation.
The refined Part D risk adjustment model represents a significant improvement in the accuracy and fairness of payment to Part D plans. The new model provides greater incentives for drug plans to compete for low-income and institutionalized enrollees.
《医疗保险处方药计划》(Medicare Part D)的持续成功取决于对计划参保者预计药物费用的医疗保险支付进行适当调整。本文描述了对这些“风险调整”的重大修订,旨在更准确地将支付与成本匹配,特别是针对高成本、弱势人群。
首次使用实际的《医疗保险处方药计划》数据对风险调整进行校准。样本为 2007 年采用按服务收费制的医疗保险和 2008 年《医疗保险处方药计划》独立参保的医疗保险受益人(N=14,224,301)。使用加权最小二乘法回归,根据人口统计和诊断因素预测《医疗保险处方药计划》的负债支出。分析了医疗保险子群体的模型。使用 R 和预测比率统计数据评估风险调整模型的预测准确性。
根据诊断导致的平均支出和增量支出的差异,为 5 个医疗保险子群体校准了独立的《医疗保险处方药计划》风险调整模型:非低收入老年人群体;低收入老年人群体;非低收入非老年人群体;低收入非老年人群体;和机构化人群体。这些模型解释的计划负债药物支出(R)的变化范围为 13%至 29%。这 5 个独立的模型准确地预测了各子群体的平均计划负债支出,范围从 967 美元到 1762 美元不等,并考虑了子群体间增量疾病系数的差异。
经过改进的《医疗保险处方药计划》风险调整模型在提高向《医疗保险处方药计划》支付的准确性和公平性方面取得了重大进展。新模式为药品计划争夺低收入和机构化参保者提供了更大的激励。