Title |
Matching and Imputation Methods for Risk Adjustment in the Health Insurance Marketplaces
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Published in |
Statistics in Biosciences, August 2015
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DOI | 10.1007/s12561-015-9135-7 |
Pubmed ID | |
Authors |
Sherri Rose, Julie Shi, Thomas G. McGuire, Sharon-Lise T. Normand |
Abstract |
New state-level health insurance markets, denotedMarketplaces, created under the Affordable Care Act, use risk-adjusted plan payment formulas derived from a populationineligibleto 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. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Canada | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
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Scientists | 2 | 67% |
Members of the public | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 16 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Master | 4 | 25% |
Other | 2 | 13% |
Student > Bachelor | 2 | 13% |
Unspecified | 1 | 6% |
Student > Ph. D. Student | 1 | 6% |
Other | 1 | 6% |
Unknown | 5 | 31% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 3 | 19% |
Biochemistry, Genetics and Molecular Biology | 1 | 6% |
Nursing and Health Professions | 1 | 6% |
Computer Science | 1 | 6% |
Unspecified | 1 | 6% |
Other | 4 | 25% |
Unknown | 5 | 31% |