Potential impact of bundled Medicare payments

本项目旨在确定全关节置换手术(TJR)后TC使用率增加对以住院时间(LOS)和支出衡量的资源消耗的财务影响。TJR是一种昂贵、普遍的手术，每年花费医疗保险70亿美元，总共进行354,000次手术。在过去的十年里，医院一直在越来越频繁地利用过渡期护理(TC)单元来管理急性后康复。急性护理住院时间(LOS)下降，TC使用率上升。 医疗保健融资管理局正在考虑建立急性护理和急性后护理捆绑支付制度。为了研究这种政策的潜在财务影响，该项目建议检查TC利用与患者、医院和医生特征的资源消耗控制之间的关联。为了解决选择偏差的问题，将测试几个候选工具变量(IV)。‘VS在成功识别后对比较组之间的随机分配很有用。最近的平衡预算修正案发生了变化，TC利用率的变化为研究TC利用率和资源消耗之间的关系提供了独特的机会。 将使用两个数据集来完善并随后检验主要假设。联邦医疗保险当前受益人数据集，除了行政账单数据外，还有详细的临床(包括功能和共病)和社会支持变量。尽管样本量限制为每年100例选择性髋关节和膝关节置换术，但该数据集在评估候选辅助变量时将是有用的。最终分析将使用更大的全国联邦医疗保险账单数据集进行。

This project seeks to determine the fiscal impact of increased TC utilization after total joint replacement surgery (TJR) on resource consumption as measured by length of stay (LOS) and expenditures. TJR is an expensive, prevalent surgery costing Medicare $7 billion per year for a total of 354,000 procedures. Over the last decade, hospitals have been utilizing transitional care (TC) units for the management of post-acute rehabilitation with increasing frequency. Acute care length of stay (LOS) has dropped while the utilization of TC has increased. The Health Care Financing Administration is considering an acute care and post-acute care bundled payment system. To study the potential fiscal impact of such a policy, this project proposes to examine the association between TC utilization and resource consumption controlling for patient, hospital and physician characteristics. To address the issue of selection bias, several candidate instrumental variables (IV) will be tested. 'vs when successfully identified are useful to approximate random assignment between the comparison groups. The recent Balanced Budget Amendment changes, and changes in TC utilization provides a unique opportunity to study the relationship between TC utilization and resource consumption. Two datasets will be used to refine and subsequently test the main hypothesis. The Medicare Current Beneficiary Dataset, in addition to administrative billing data, has detailed clinical (including function and comorbidity) and social support variables. Although sample size is restricted to 100 elective hip and knee replacements per year, this dataset will be useful in evaluating candidate instrumental variables. Final analyses will be performed using the larger national Medicare billing dataset.