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医疗保险市场中风险调整的匹配与插补方法

Matching and Imputation Methods for Risk Adjustment in the Health Insurance Marketplaces.

作者信息

Rose Sherri, Shi Julie, McGuire Thomas G, Normand Sharon-Lise T

机构信息

Harvard Medical School, Department of Health Care Policy, 180 Longwood Ave, Boston, MA, 02115, USA, Tel.: +1-617-432-3493, ,

Peking University, School of Economics, Haidian District, Beijing, China 100871.

出版信息

Stat Biosci. 2017 Dec;9(2):525-542. doi: 10.1007/s12561-015-9135-7. Epub 2015 Aug 5.

Abstract

New state-level health insurance markets, denoted , created under the Affordable Care Act, use risk-adjusted plan payment formulas derived from a population to participate in the Marketplaces. We develop methodology to derive a sample from the target population and to assemble information to generate improved risk-adjusted payment formulas using data from the Medical Expenditure Panel Survey and Truven MarketScan databases. Our approach requires multi-stage data selection and imputation procedures because both data sources have systemic missing data on crucial variables and arise from different populations. We present matching and imputation methods adapted to this setting. The long-term goal is to improve risk-adjustment estimation utilizing information found in Truven MarketScan data supplemented with imputed Medical Expenditure Panel Survey values.

摘要

根据《平价医疗法案》设立的新的州级医疗保险市场(记为 ),采用了从参与市场交易的人群中推导出来的风险调整后的计划支付公式。我们开发了一种方法,用于从目标人群中抽取样本,并利用医疗支出小组调查和Truven MarketScan数据库中的数据来收集信息,以生成改进后的风险调整支付公式。我们的方法需要多阶段的数据选择和插补程序,因为这两个数据源在关键变量上都存在系统性缺失数据,且来自不同的人群。我们提出了适用于这种情况的匹配和插补方法。长期目标是利用Truven MarketScan数据中发现的信息,并辅以插补后的医疗支出小组调查值,来改进风险调整估计。

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