Literature DB >> 19187185

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

Michael Davern1, Jacob Alex Klerman, David K Baugh, Kathleen Thiede Call, George D Greenberg.   

Abstract

OBJECTIVE: To assess reasons why survey estimates of Medicaid enrollment are 43 percent lower than raw Medicaid program enrollment counts (i.e., "Medicaid undercount"). DATA SOURCES: Linked 2000-2002 Medicaid Statistical Information System (MSIS) and the 2001-2002 Current Population Survey (CPS). DATA COLLECTION
METHODS: Centers for Medicare and Medicaid Services provided the Census Bureau with its MSIS file. The Census Bureau linked the MSIS to the CPS data within its secure data analysis facilities. STUDY
DESIGN: We analyzed how often Medicaid enrollees incorrectly answer the CPS health insurance item and imperfect concept alignment (e.g., inclusion in the MSIS of people who are not included in the CPS sample frame and people who were enrolled in Medicaid in more than one state during the year). PRINCIPAL
FINDINGS: The extent to which the Medicaid enrollee data were adjusted for imperfect concept alignment reduces the raw Medicaid undercount considerably (by 12 percentage points). However, survey response errors play an even larger role with 43 percent of Medicaid enrollees answering the CPS as though they were not enrolled and 17 percent reported being uninsured.
CONCLUSIONS: The CPS is widely used for health policy analysis but is a poor measure of Medicaid enrollment at any time during the year because many people who are enrolled in Medicaid fail to report it and may be incorrectly coded as being uninsured. This discrepancy should be considered when using the CPS for policy research.

Entities:  

Mesh:

Year:  2009        PMID: 19187185      PMCID: PMC2699917          DOI: 10.1111/j.1475-6773.2008.00941.x

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


  8 in total

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

Authors:  Sherry Glied; Dahlia K Remler; Joshua Graff Zivin
Journal:  Milbank Q       Date:  2002       Impact factor: 4.911

2.  Interpreting the estimates from four national surveys of the number of people without health insurance.

Authors:  K Swartz
Journal:  J Econ Soc Meas       Date:  1986-10

Review 3.  Monitoring the uninsured: a state policy perspective.

Authors:  Lynn A Blewett; Margaret Brown Good; Kathleen Thiede Call; Michael Davern
Journal:  J Health Polit Policy Law       Date:  2004-02       Impact factor: 2.265

4.  Unstable inferences? An examination of complex survey sample design adjustments using the Current Population Survey for health services research.

Authors:  Michael Davern; Arthur Jones; James Lepkowski; Gestur Davidson; Lynn A Blewett
Journal:  Inquiry       Date:  2006       Impact factor: 1.730

5.  Meeting the need for state-level estimates of health insurance coverage: use of State and Federal survey data.

Authors:  Lynn A Blewett; Michael Davern
Journal:  Health Serv Res       Date:  2006-06       Impact factor: 3.402

6.  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

7.  Medicaid undercount and bias to estimates of uninsurance: new estimates and existing evidence.

Authors:  Kathleen Thiede Call; Gestur Davidson; Michael Davern; Rebecca Nyman
Journal:  Health Serv Res       Date:  2008-06       Impact factor: 3.402

8.  State variation in SCHIP allocations: how much is there, what are its sources, and can it be reduced?

Authors:  Michael Davern; Lynn A Blewett; Boris Bershadsky; Kathleen Thiede Call; Todd Rockwood
Journal:  Inquiry       Date:  2003       Impact factor: 1.730

  8 in total
  20 in total

1.  Measurement Error in Public Health Insurance Reporting in the American Community Survey: Evidence from Record Linkage.

Authors:  Michel H Boudreaux; Kathleen Thiede Call; Joanna Turner; Brett Fried; Brett O'Hara
Journal:  Health Serv Res       Date:  2015-04-12       Impact factor: 3.402

2.  Survey mode effects and insurance coverage estimates in the redesigned Gallup well-being index.

Authors:  Benjamin D Sommers; Anna L Goldman; Dennis Lee; Arnold M Epstein
Journal:  Health Serv Res       Date:  2019-04-22       Impact factor: 3.402

3.  Response error and the Medicaid undercount in the current population survey.

Authors:  James M Noon; Leticia E Fernandez; Sonya R Porter
Journal:  Health Serv Res       Date:  2018-10-01       Impact factor: 3.402

4.  Potential Data Sources for a New Study of Social Mobility in the United States.

Authors:  John Robert Warren
Journal:  Ann Am Acad Pol Soc Sci       Date:  2014-12-10

5.  Comparing errors in Medicaid reporting across surveys: evidence to date.

Authors:  Kathleen T Call; Michael E Davern; Jacob A Klerman; Victoria Lynch
Journal:  Health Serv Res       Date:  2012-07-20       Impact factor: 3.402

6.  Migration patterns for Medicaid enrollees 2005-2007.

Authors:  David K Baugh; Shinu Verghese
Journal:  Medicare Medicaid Res Rev       Date:  2013-12-18

7.  CHIP reporting in the CPS.

Authors:  Jacob Klerman; Michael R Plotzke; Mike Davern
Journal:  Medicare Medicaid Res Rev       Date:  2012-07-31

8.  Access and Quality of Care by Insurance Type for Low-Income Adults Before the Affordable Care Act.

Authors:  Kevin H Nguyen; Benjamin D Sommers
Journal:  Am J Public Health       Date:  2016-05-19       Impact factor: 9.308

9.  Multiple imputation to account for linkage ineligibility in the NHANES-CMS Medicaid linked data: General use versus subject specific imputation models.

Authors:  Jennifer Rammon; Yulei He; Jennifer D Parker
Journal:  Stat J IAOS       Date:  2019-08-26

10.  Accounting for study participants who are ineligible for linkage: a multiple imputation approach to analyzing the linked National Health and Nutrition Examination Survey and Centers for Medicare and Medicaid Services' Medicaid data.

Authors:  Jennifer Rammon; Yulei He; Jennifer D Parker
Journal:  Health Serv Outcomes Res Methodol       Date:  2018-08-16
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.