Swedish Cancer Institute, Edmonds, WA; American Society of Clinical Oncology, Alexandria, VA; Center for Cancer and Blood Disorders, Weatherford, TX; WellRithms, Portland, OR; Parkland Health System; University of Texas Southwestern, Dallas; University of Texas MD Anderson Cancer Center, Houston, TX; and University of Chicago, Chicago, IL.
J Oncol Pract. 2018 May;14(5):e259-e268. doi: 10.1200/JOP.17.00036. Epub 2018 Apr 12.
This analysis evaluates the impact of bundling drug costs into a hypothetic bundled payment.
An economic model was created for patient vignettes from: advanced-stage III colon cancer and metastatic non-small-cell lung cancer. First quarter 2016 Medicare reimbursement rates were used to calculate the average fee-for-service (FFS) reimbursement for these vignettes. The probabilistic risk faced by practices was captured by the type of patients seen in practices and randomly assigned in a Monte Carlo simulation on the basis of the given distribution of patient types within each cancer. Simulations were replicated 1,000 times. The impact of bundled payments that include drug costs for various practice sizes and cancer types was quantified as the probability of incurring a loss at four magnitudes: any loss, > 10%, > 20%, or > 30%. A loss was defined as receiving revenue from the bundle that was less than what the practice would have received under FFS; the probability of loss was calculated on the basis of the number of times a practice reported a loss among the 1,000 simulations.
Practices that treat a substantial proportion of patients with complex disease compared with the average patient in the bundle would have revenue well below that expected from FFS. Practices that treat a disproportionate share of patients with less complex disease, as compared with the average patient in the bundle, would have revenue well above the revenue under FFS. Overall, bundled payments put practices at greater risk than FFS because their patient case mix could greatly skew financial performance.
Including drug costs in a bundle is subject to the uncontrollable probabilistic risk of patient case mixes.
本分析评估了将药物成本捆绑到假设的捆绑支付中的影响。
为晚期 III 期结肠癌和转移性非小细胞肺癌的患者病例创建了一个经济模型。使用 2016 年第一季度的医疗保险报销率来计算这些病例的按服务收费(FFS)平均报销额。实践中面临的概率风险通过实践中所看到的患者类型以及根据每个癌症中患者类型的给定分布在蒙特卡罗模拟中随机分配来捕获。模拟重复了 1000 次。对于各种实践规模和癌症类型的捆绑支付,包括药物成本的影响,被量化为在四个幅度下发生亏损的概率:任何亏损、>10%、>20%或>30%。亏损被定义为从捆绑中获得的收入少于实践在 FFS 下获得的收入;亏损概率是根据实践在 1000 次模拟中报告亏损的次数计算得出的。
与捆绑中平均患者相比,治疗大量复杂疾病患者的实践的收入将远低于 FFS 的预期。与捆绑中平均患者相比,治疗比例不成比例的较不复杂疾病患者的实践的收入将大大高于 FFS 的收入。总体而言,捆绑支付使实践面临比 FFS 更大的风险,因为他们的患者病例组合可能极大地影响财务表现。
将药物成本包含在捆绑中受到患者病例组合不可控概率风险的影响。