Using a Semi-Markov Model to Estimate Medicaid Cost Savings due to Minnesota's Return to Community Initiative.
Using a Semi-Markov Model to Estimate Medicaid Cost Savings due to Minnesota's Return to Community Initiative.
复制标题
使用半马尔可夫模型来估计由于明尼苏达州回归社区倡议而节省的医疗补助成本。
DOI：
10.1016/j.jamda.2020.07.016
复制
发表时间：
2021
影响因子：
7.6
通讯作者：
Arling,Greg
中科院分区：
文献类型：
--
作者：
Hass,Zachary;Woodhouse,Mark;Arling,Greg
目标 提供因明尼苏达州回归社区倡议 (RTCI) 而节省的医疗补助成本的估计值和不确定性水平。使用半马尔可夫模型和模拟方法来估计设计医疗补助成本节省。设置和参与者 RTCI 是一项全州范围的计划，旨在帮助私人付费疗养院居民出院后返回社区。最初提出时，预计该计划将减少州医疗补助支出，主要是通过将居民从疗养院转移到成本较低的社区环境来实现。在之前的分析中，我们估计，如果没有 RTCI，大约九分之一的计划目标居民将不会返回社区。准确的成本节省估算需要考虑复杂的居民护理轨迹，即疗养院的重新入院、辅助生活和社区服务的使用以及死亡率。测量数据来自 2011 年入住明尼苏达州 378 个设施的 30,234 名私人付费疗养院居民（主要是急性期后入住），并在入院后对结果和事件发生时间进行了 4 年的跟踪。居民特征取自最低数据集（MDS）入学评估。我们使用半马尔可夫公式对护理轨迹的变异性进行了建模。使用多项回归估计转移概率。使用每条路径的最佳拟合、正、右偏分布对事件发生时间进行建模。在有或没有 RTCI 影响的情况下运行模拟（1000 次），以估计各种设置下医疗补助天数的变化。结果 在 4 年的积累期内，预计该计划每年可节省 410 万美元。结论和影响 RTCI 节省了适度的医疗补助成本，超过了 350 万美元的年度计划预算。半马尔可夫模型和模拟的结果增加了我们对疗养院、社区、医疗补助状态和死亡率之间护理转变的理解。
Objectives To provide an estimate and level of uncertainty for Medicaid cost savings due to Minnesota's Return to Community Initiative (RTCI). Design Medicaid cost savings are estimated using a semi-Markov model and simulation approach. Setting and Participants RTCI is a statewide program that assists private paying nursing home residents with discharge to the community. When originally proposed, it was expected that the program would reduce state Medicaid expenditures, primarily through the shifting of residents from nursing homes to a less costly community setting. In prior analysis, we estimated that approximately 1 in 9 residents targeted for transition by the program would not have returned to the community without the RTCI. Accurate cost savings estimates require consideration of complex resident care trajectories, that is, nursing home readmissions, use of assisted living and community-based services, and mortality. Measures Data were from 30,234 private pay nursing home residents admitted during 2011, primarily for post-acute stays, to 378 facilities in Minnesota, and followed for 4 years postadmission for outcomes and time to event. Resident characteristics were taken from the Minimum Data Set (MDS) admission assessment. We modeled variability in care trajectories with a semi-Markov formulation. Transition probabilities were estimated using Multinomial regression. Time to event was modeled using the best-fitting, positive, right-skewed distribution for each path. The simulation was run (1000 times) with and without the RTCI impact to estimate change in Medicaid days in various settings. Results Program savings was estimated at $4.1 million per year of effort over a 4-year accumulation period. Conclusions and Implications The RTCI produced a modest Medicaid cost savings in excess of the annual program budget of $3.5 million. Findings from the semi-Markov model and simulation increase our understanding of care transitions between nursing home, community, Medicaid status, and mortality.