Literature DB >> 15762899

Health benefits offer rates: is there a nonresponse bias?

Jeremy D Pickreign1, Jon R Gabel.   

Abstract

OBJECTIVE: To determine whether a nonresponse bias exists in the offer rate for health benefits in firms with fewer than 50 workers and to present a simple adjustment to correct for observed bias. DATA SOURCES: The 2003 Employer Health Benefits Survey (EHBS) conducted by the Kaiser Family Foundation and Health Research and Educational Trust, and a follow-up survey of nonrespondents to the 2003 EHBS. STUDY
DESIGN: We conducted a follow-up survey to the 2003 EHBS to collect health benefits offering data from firms with fewer than 50 workers. We used McNemar's test to verify that the follow-up survey provided results comparable to the EHBS, and t-tests were used to determine nonresponse bias. We applied a simple weighting adjustment to the EHBS. DATA COLLECTION: The data for both the EHBS and the follow-up survey were collected by the same survey research firm. The EHBS interviews the person most knowledgeable about the firm's health benefits, while the follow-up survey interviews the first person who answers the telephone whether they are the most knowledgeable or not. Principal Findings. Firms with 3-9 workers were more likely to exhibit a bias than were firms with 10-24 workers and 25-49 workers. Although the calculated bias for each size category was not significant, there is sufficient evidence to warrant caution when reporting offer rates.
CONCLUSIONS: Survey nonresponse in the EHBS produces an upward bias on estimates for the offer rates of small firms. Although not significant, this upward bias is because of nonresponse by small firms that do not offer health benefits. Our research is limited in that we only control for differences in the size of the firm.

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Year:  2005        PMID: 15762899      PMCID: PMC1361148          DOI: 10.1111/j.1475-6773.2005.00364.x

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


  3 in total

1.  Health benefits in 2003: premiums reach thirteen-year high as employers adopt new forms of cost sharing.

Authors:  Jon Gabel; Gary Claxton; Erin Holve; Jeremy Pickreign; Heidi Whitmore; Kelley Dhont; Samantha Hawkins; Diane Rowland
Journal:  Health Aff (Millwood)       Date:  2003 Sep-Oct       Impact factor: 6.301

2.  Job-based health benefits in 2002: some important trends.

Authors:  Jon Gabel; Larry Levitt; Erin Holve; Jeremy Pickreign; Heidi Whitmore; Kelley Dhont; Samantha Hawkins; Diane Rowland
Journal:  Health Aff (Millwood)       Date:  2002 Sep-Oct       Impact factor: 6.301

3.  Nonresponse bias and early versus all responders in mail and telephone surveys.

Authors:  J Siemiatycki; S Campbell
Journal:  Am J Epidemiol       Date:  1984-08       Impact factor: 4.897

  3 in total

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