The Swiss Health Insurance Literacy Measure (HILM-CH): Measurement Properties and Cross-Cultural Validation

Abstract

Background: Most consumers face difficulties when choosing and navigating health insurance plans. Health insurance literacy (HIL) has been discussed as a critical lever to ensure efficient choices and navigation in choice-based health insurance systems. Still, existing evidence about HIL mainly comes from the US, and the only validated scale, the Health Insurance Literacy Measure (HILM), may not be adequate to measure HIL outside US samples. This paper describes the measurement properties of the Swiss Health Insurance Literacy Measure (HILM-CH), the first scale to measure HIL in Switzerland. Methods: The items of the HILM-CH were adapted from the HILM in German, French, and Italian. A panel of experts refined it to ensure its suitability for the Swiss context. The final version of the HILM-CH contains 21 items, and other relevant measures were administered in the Swiss Health Insurance Literacy Survey to a sample of 6036 insurees. Measurement properties were investigated overall and per linguistic group. Internal reliability was determined using Cronbach’s alphas. Criterion validity was examined through convergent and concurrent validity of the HILM-CH. The construct validity was assessed using factor analysis. Measurement invariance of the HILM-CH between linguistic regions was further evaluated using multiple-group confirmatory factor analyses. Results: The HILM-CH had acceptable to good reliability (alphas between 0.70 and 0.91). Concurrent and convergent validity showed that HILM-CH is a good measurement of HIL. Factor analysis revealed a four-factor model and showed an acceptable fit to the data (CFI= 0.977; TLI = 0.974; RMSEA = 0.061; SRMR = 0.032). Using the established four-factor model, measurement invariance was established across Switzerland’s German, French, and Italian-speaking regions. Conclusions: The HILM-CH is a reliable and valid measure of HIL across Switzerland’s German, French, and Italian-speaking regions. It can be used in future research to find associations between HIL and individual characteristics.