The European Journal of Public Health Advance Access published online on November 5, 2007
The European Journal of Public Health, doi:10.1093/eurpub/ckm103
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The effect of non-response on estimates of health care utilisation: linking health surveys and registers
Jens Gundgaard1, Ola Ekholm2, Ebba Holme Hansen3 and Niels Kr. Rasmussen2
1 Institute of Public Health – Health Economics, University of Southern Denmark, Odense, Denmark
2 National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
3 Faculty of Pharmaceutical Sciences, Section for Social Pharmacy, Copenhagen University, Copenhagen, Denmark
Correspondence: Jens Gundgaard, Institute of Public Health – Health Economics, University of Southern Denmark, J.B. Winsløwsvej 9, 1, 5000 Odense C, Denmark, tel: +45 6550 3965, fax: +45 6550 3880, e-mail: jgu{at}sam.sdu.dk
Received July 4, 2007 , accepted October 4, 2007
Background: Non-response in health surveys may lead to bias in estimates of health care utilisation. The magnitude, direction and composition of the bias are usually not well known. When data from health surveys are merged with data from registers at the individual level, analyses can reveal non-response bias. Our aim was to estimate the composition, direction and magnitude of non-response bias in the estimation of health care costs in two types of health interview surveys. Methods: The surveys were (1) a national personal interview survey of 22 484 Danes (2) a telephone interview survey of 5000 Danes living in Funen County. Data were linked with register information on health care utilisation in hospitals and primary care. Health care utilisation was estimated for respondents and non-respondents, and the difference was explained by a decomposition method of bias components. Results: The surveys produced the same pattern of non-response, but with slight differences in non-response bias. Response rates for the interview and telephone surveys were 75 and 69%, respectively. Refusal was the most frequent reason for non-response (22 and 20% of those sampled, respectively), whereas illness, non-contact, and other reasons were less frequent. Respondents used 3–6% less health care than non-respondents at the aggregate level, but the opposite was true for some specific types of health care. Non-response due to illness was the main contributor to non-response bias. Conclusions: Different types of non-response have different bias effects. However, the magnitude of the bias encourages the continued use of interview health surveys.
Keywords: non-response, health care, health survey, registers, bias
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