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The Growing Challenges to State Telephone Surveys of Health Insurance Coverage: Minnesota as a Case Study

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Presentation by Kathleen Thiede Call at the AcademyHealth Annual Research Meeting, June 7 2008.

Economy & FinanceBusiness
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Growing Challenges to State Telephone Surveys of Health Insurance Coverage: Minnesota as a Case Study Supported by a grant from the Minnesota Department Health Kathleen Thiede Call, Ph.D. AcademyHealth State Health Research & Policy Group Meeting Washington DC June 7, 2008
Overview of Talk ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
State Health Insurance Surveys ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Methodology ,[object Object],[object Object],[object Object],[object Object],[object Object]
Minnesota Health Access Surveys Response rates in 1999, 2001, 2004, 2007 are based on AAPOR RR4. Current analysis is limited to data from last three years using a consistent sample design.
Challenges to RDD Surveys ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
What is Known about Sample Coverage Error ,[object Object],[object Object],[object Object],[object Object]
Characteristics of Wireless Only Households (Blumberg & Luke, 2008) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Challenges: Comparison of 2001-07 Sample to Population Controls ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Comparison of 2001-07 Sample to Population Controls, Continued ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Method to Deal with Challenges: Post-stratification Weights ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Impact of Post-stratification on Uninsurance Estimates Baseweight adjusts for sample stratum, probability of selection by number of phones and number of people in household. Demographic weight adjusts for region by age, race, and telephone interruption. Wireless demographic weight adjusts for age by education and homeownership in 2007. Nativity weight adjusts for race/ethnicity by US and non-US born.
Summary of Findings ,[object Object],[object Object],[object Object]
Implications ,[object Object],[object Object],[object Object],[object Object],[object Object]
Thank you State Health Access Data Assistance Center (SHADAC) 2221 University Avenue, Suite 345 Minneapolis Minnesota 55414 (612) 624-4802 www.shadac.org [email_address]

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The Growing Challenges to State Telephone Surveys of Health Insurance Coverage: Minnesota as a Case Study

  • 1. Growing Challenges to State Telephone Surveys of Health Insurance Coverage: Minnesota as a Case Study Supported by a grant from the Minnesota Department Health Kathleen Thiede Call, Ph.D. AcademyHealth State Health Research & Policy Group Meeting Washington DC June 7, 2008
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  • 5. Minnesota Health Access Surveys Response rates in 1999, 2001, 2004, 2007 are based on AAPOR RR4. Current analysis is limited to data from last three years using a consistent sample design.
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  • 12. Impact of Post-stratification on Uninsurance Estimates Baseweight adjusts for sample stratum, probability of selection by number of phones and number of people in household. Demographic weight adjusts for region by age, race, and telephone interruption. Wireless demographic weight adjusts for age by education and homeownership in 2007. Nativity weight adjusts for race/ethnicity by US and non-US born.
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  • 15. Thank you State Health Access Data Assistance Center (SHADAC) 2221 University Avenue, Suite 345 Minneapolis Minnesota 55414 (612) 624-4802 www.shadac.org [email_address]