The impact of non-response weighting in health surveys for estimates on primary health care utilization.

Background: Low response rates in health surveys may affect the representativeness and generalizability of results if non-response is systematically related to the indicator of interest. To account for such potential bias, weighting procedures are widely used with an overall aim to obtain less biased estimates. The aim of this study was to assess the impact of applying calibrated weights on prevalence estimates of primary health care utilization among respondents compared to the entire sample of a representative Danish survey of adults aged ≥16 years.

Methods: Registry-based 1-year prevalence data on health care utilization of chiropractor/physiotherapist, dentist and psychologist in 2016 were linked to the entire sample (n = 312 349), including respondents (n = 183 372), from the Danish National Health Survey in 2017. Calibrated weights, which applied information on e.g. sex, age, ethnic background, education and overall health service use were used to assess their impact on prevalence estimates among respondents.

Results: Across all included types of health care, weighting for non-response decreased prevalence estimates among respondents, which resulted in less biased estimates. For example, the overall 1-year prevalence of chiropractor/physiotherapist, dentist and psychologist utilization decreased from 19.1% to 16.9%, 68.4% to 62.5% and 1.9% to 1.8%, respectively. The corresponding prevalence in the entire sample was 16.5%, 59.4% and 1.7%.

Conclusions: Applying calibrated weights to survey data to account for non-response reduces bias in primary health care utilization estimates. Future studies are needed to explore the possible impact of weighting on other health estimates.