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Potential impact of bundled Medicare payments

Potential impact of bundled Medicare payments
捆绑医疗保险付款的潜在影响
批准号:
6480402
负责人:
JOHN D FITZGERALD
金额:
$15.94万
依托单位国家:
美国
项目类别:
财政年份:
2001
资助国家:
美国
项目状态:
已结题
起止时间:
2001-07-01 至 2003-06-30

项目摘要

项目成果

JOHN D FITZGERALD的其他基金

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中文摘要
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英文摘要
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.
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