Editors and researchers beware: calculating response rates in random digit dial health surveys

Health Serv Res. 2013 Apr;48(2 Pt 1):665-76. doi: 10.1111/j.1475-6773.2012.01464.x. Epub 2012 Sep 21.

Abstract

Objective: To demonstrate that different approaches to handling cases of unknown eligibility in random digit dial health surveys can contribute to significant differences in response rates.

Data source: Primary survey data of individuals with chronic disease.

Study design: We computed response rates using various approaches, each of which make different assumptions about the disposition of cases of unknown eligibility.

Data collection: Data were collected via telephone interviews as part of the Aligning Forces for Quality (AF4Q) consumer survey, a representative survey of adults with chronic illnesses in 17 communities and nationally.

Principal findings: We found that various approaches to estimating eligibility rates can lead to substantially different response rates.

Conclusions: Health services researchers must consider strategies to standardize response rate reporting, enter into a dialog related to why response rate reporting is important, and begin to utilize alternate methods for demonstrating that survey data are valid and reliable.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Chronic Disease
  • Data Interpretation, Statistical*
  • Health Surveys / methods*
  • Health Surveys / statistics & numerical data*
  • Humans
  • Research Design*