The Transplant Center, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA.
Clin Transplant. 2012 May-Jun;26(3):E269-76. doi: 10.1111/j.1399-0012.2012.01658.x.
Recent changes in Center for Medicare & Medicaid Services (CMS) condition for participation, using benchmark volume/outcomes requirements for certification, have been implemented. Consequently, the ability of a transplant center to assess its risk tolerance is important in successful management. An analysis of SRTR data was performed to determine donor/recipient risk factors for graft loss or patient death in the first year. Each transplant performed was then assigned a prospective relative risk (RR) of failure. Using a Monte-Carlo simulation, transplants were selected at random that met the centers' acceptable risk tolerance. Transplant center volume was fixed and its risk tolerance was adjusted to determine the impact on outcomes. The model was run 1000 times on centers with varying volume. The modeling demonstrates that centers with smaller annual volumes must use a more risk taking strategy than larger volume centers to avoid being flagged for CMS volume requirements. The modeling also demonstrates optimal risk taking strategies for centers based upon volume to minimize the probability of being flagged for not meeting volume or outcomes benchmarks. Small volume centers must perform higher risk transplants to meet current CMS requirements and are at risk for adverse action secondary to chance alone.
最近,医疗保险和医疗补助服务中心(CMS)对参与条件进行了修改,采用了基准量/结果要求进行认证。因此,移植中心评估其风险承受能力的能力对于成功管理至关重要。对 SRTR 数据进行了分析,以确定供体/受体在第一年发生移植物丢失或患者死亡的风险因素。然后为每个移植手术分配了一个前瞻性相对风险(RR)失败概率。使用蒙特卡罗模拟,随机选择符合中心可接受风险承受能力的移植手术。固定移植中心的量,并调整其风险承受能力,以确定对结果的影响。该模型在具有不同量的中心上运行了 1000 次。建模表明,每年的量较小的中心必须比量大的中心采取更冒险的策略,以避免因 CMS 量的要求而被标记。该模型还为基于量的中心展示了最佳的风险承担策略,以最小化因未达到量或结果基准而被标记的概率。小量中心必须进行更高风险的移植,以满足当前 CMS 的要求,并且仅因机会而面临不良行动的风险。