Literature DB >> 12532642

Inside the sausage factory: improving estimates of the effects of health insurance expansion proposals.

Sherry Glied1, Dahlia K Remler, Joshua Graff Zivin.   

Abstract

The fate of a proposal to expand health insurance is influenced by predictions of the proposal's effects on the number of newly insured and the cost of new coverage. Estimates vary widely, for reasons that are often hard to discern and evaluate. This article describes and compares the frameworks and parameters used for insurance modeling. It examines conventions and controversies surrounding a series of modeling parameters: how individuals respond to a change in the price of coverage, the extent of participation in a new plan by those already privately insured, firms' behavior, and the value of public versus private coverage. The article also suggests ways of making models more transparent and proposes "reference case" guidelines for modelers so that consumers can compare modeling results.

Mesh:

Year:  2002        PMID: 12532642      PMCID: PMC2690126          DOI: 10.1111/1468-0009.00026

Source DB:  PubMed          Journal:  Milbank Q        ISSN: 0887-378X            Impact factor:   4.911


  18 in total

1.  Health insurance reform in the small-group market.

Authors:  R Curtis; S Lewis; K Haugh; R Forland
Journal:  Health Aff (Millwood)       Date:  1999 May-Jun       Impact factor: 6.301

2.  Hidden assets: health insurance reform in New Jersey.

Authors:  K Swartz; D W Garnick
Journal:  Health Aff (Millwood)       Date:  1999 Jul-Aug       Impact factor: 6.301

3.  Waiting in the wings: eligibility and enrollment in the State Children's Health Insurance Program.

Authors:  T M Selden; J S Banthin; J W Cohen
Journal:  Health Aff (Millwood)       Date:  1999 Mar-Apr       Impact factor: 6.301

4.  Providing health insurance to the short-term unemployed.

Authors:  J R Baumgardner
Journal:  Inquiry       Date:  1998       Impact factor: 1.730

5.  The effects of Medicaid expansions on insurance coverage of children.

Authors:  L C Dubay; G M Kenney
Journal:  Future Child       Date:  1996

6.  Assessing SCHIP effects using household survey data: promises and pitfalls.

Authors:  L Dubay; G Kenney
Journal:  Health Serv Res       Date:  2000-12       Impact factor: 3.402

7.  Confessions of the estimators: numbers and health reform.

Authors:  L T Bilheimer; R D Reischauer
Journal:  Health Aff (Millwood)       Date:  1995       Impact factor: 6.301

8.  Numerical estimates and the policy debate.

Authors:  L M Nichols
Journal:  Health Aff (Millwood)       Date:  1995       Impact factor: 6.301

9.  Medical savings accounts: microsimulation results from a model with adverse selection.

Authors:  D Zabinski; T M Selden; J F Moeller; J S Banthin
Journal:  J Health Econ       Date:  1999-04       Impact factor: 3.883

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  7 in total

1.  Modeling health care policy alternatives.

Authors:  Jeanne S Ringel; Christine Eibner; Federico Girosi; Amado Cordova; Elizabeth A McGlynn
Journal:  Health Serv Res       Date:  2010-08-02       Impact factor: 3.402

2.  Are the Current Population Survey uninsurance estimates too high? An examination of the imputation process.

Authors:  Michael Davern; Holly Rodin; Lynn A Blewett; Kathleen Thiede Call
Journal:  Health Serv Res       Date:  2007-10       Impact factor: 3.402

3.  An examination of the Medicaid undercount in the current population survey: preliminary results from record linking.

Authors:  Michael Davern; Jacob Alex Klerman; David K Baugh; Kathleen Thiede Call; George D Greenberg
Journal:  Health Serv Res       Date:  2009-01-28       Impact factor: 3.402

4.  Using microsimulation models to inform U.S. health policy making.

Authors:  Jean Marie Abraham
Journal:  Health Serv Res       Date:  2013-04       Impact factor: 3.402

5.  The Polls-Review: Inaccurate Age and Sex Data in the Census Pums Files: Evidence and Implications.

Authors:  J Trent Alexander; Michael Davern; Betsey Stevenson
Journal:  Public Opin Q       Date:  2010-08-13

6.  Will employers drop health insurance coverage because of the Affordable Care Act?

Authors:  Thomas Buchmueller; Colleen Carey; Helen G Levy
Journal:  Health Aff (Millwood)       Date:  2013-09       Impact factor: 9.048

7.  Improvements in Uninsurance Estimates for Fully Imputed Cases in the Current Population Survey Annual Social and Economic Supplement.

Authors:  Heide Jackson; Edward R Berchick
Journal:  Inquiry       Date:  2020 Jan-Dec       Impact factor: 1.730

  7 in total

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