Literature DB >> 29484032

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

Sherri Rose1, Julie Shi2, Thomas G McGuire3, Sharon-Lise T Normand4.   

Abstract

New state-level health insurance markets, denoted Marketplaces, created under the Affordable Care Act, use risk-adjusted plan payment formulas derived from a population ineligible 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.

Entities:  

Keywords:  Imputation; Matching; Prediction; Risk adjustment

Year:  2015        PMID: 29484032      PMCID: PMC5824732          DOI: 10.1007/s12561-015-9135-7

Source DB:  PubMed          Journal:  Stat Biosci        ISSN: 1867-1764


  18 in total

1.  The HHS-HCC risk adjustment model for individual and small group markets under the Affordable Care Act.

Authors:  John Kautter; Gregory C Pope; Melvin Ingber; Sara Freeman; Lindsey Patterson; Michael Cohen; Patricia Keenan
Journal:  Medicare Medicaid Res Rev       Date:  2014-05-09

2.  A comparison of propensity score methods: a case-study estimating the effectiveness of post-AMI statin use.

Authors:  Peter C Austin; Muhammad M Mamdani
Journal:  Stat Med       Date:  2006-06-30       Impact factor: 2.373

3.  A targeted maximum likelihood estimator for two-stage designs.

Authors:  Sherri Rose; Mark J van der Laan
Journal:  Int J Biostat       Date:  2011-03-11       Impact factor: 0.968

4.  Rose and van der Laan respond to "Some advantages of the relative excess risk due to interaction".

Authors:  Sherri Rose; Mark van der Laan
Journal:  Am J Epidemiol       Date:  2014-01-31       Impact factor: 4.897

5.  A double robust approach to causal effects in case-control studies.

Authors:  Sherri Rose; Mark van der Laan
Journal:  Am J Epidemiol       Date:  2014-01-31       Impact factor: 4.897

6.  Assessing incentives for service-level selection in private health insurance exchanges.

Authors:  Thomas G McGuire; Joseph P Newhouse; Sharon-Lise Normand; Julie Shi; Samuel Zuvekas
Journal:  J Health Econ       Date:  2014-02-17       Impact factor: 3.883

7.  One-to-many propensity score matching in cohort studies.

Authors:  Jeremy A Rassen; Abhi A Shelat; Jessica Myers; Robert J Glynn; Kenneth J Rothman; Sebastian Schneeweiss
Journal:  Pharmacoepidemiol Drug Saf       Date:  2012-05       Impact factor: 2.890

8.  Generalizing observational study results: applying propensity score methods to complex surveys.

Authors:  Eva H Dugoff; Megan Schuler; Elizabeth A Stuart
Journal:  Health Serv Res       Date:  2013-07-16       Impact factor: 3.402

9.  Improving propensity score weighting using machine learning.

Authors:  Brian K Lee; Justin Lessler; Elizabeth A Stuart
Journal:  Stat Med       Date:  2010-02-10       Impact factor: 2.373

10.  Multiple imputation for handling systematically missing confounders in meta-analysis of individual participant data.

Authors:  Matthieu Resche-Rigon; Ian R White; Jonathan W Bartlett; Sanne A E Peters; Simon G Thompson
Journal:  Stat Med       Date:  2013-07-16       Impact factor: 2.373

View more
  3 in total

1.  Sample Selection for Medicare Risk Adjustment Due to Systematically Missing Data.

Authors:  Savannah L Bergquist; Thomas G McGuire; Timothy J Layton; Sherri Rose
Journal:  Health Serv Res       Date:  2018-09-11       Impact factor: 3.402

2.  Computational health economics for identification of unprofitable health care enrollees.

Authors:  Sherri Rose; Savannah L Bergquist; Timothy J Layton
Journal:  Biostatistics       Date:  2017-10-01       Impact factor: 5.899

3.  Development and Assessment of a New Framework for Disease Surveillance, Prediction, and Risk Adjustment: The Diagnostic Items Classification System.

Authors:  Randall P Ellis; Heather E Hsu; Jeffrey J Siracuse; Allan J Walkey; Karen E Lasser; Brian C Jacobson; Corinne Andriola; Alex Hoagland; Ying Liu; Chenlu Song; Tzu-Chun Kuo; Arlene S Ash
Journal:  JAMA Health Forum       Date:  2022-03-25
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.