Calculating Preference Weights for the Labor and Delivery Index- A Discrete Choice Experiment on Women’s Birth Experiences

Abstract

Objective

The aim of this study was to calculate preference weights for the Labor and Delivery Index (LADY-X) to make it suitable as a utility measure for perinatal care studies.

Methods

In an online discrete choice experiment, 18 pairs of hypothetical scenarios were presented to respondents, from which they had to choose a preferred option. The scenarios describe the birth experience in terms of the seven LADY-X attributes. A D-efficient discrete choice experiment design with priors based on a small sample (N = 110) was applied. Two samples were gathered, women who had recently given birth and subjects from the general population. Both samples were analyzed separately using a panel mixed logit (MMNL) model. Using the panel mixed multinomial logit (MMNL) model results and accounting for preference heterogeneity, we calculated the average preference weights for LADY-X attribute levels. These were transformed to represent a utility score between 0 and 1, with 0 representing the worst and 1 representing the best birth experience.

Results

In total, 1097 women who had recently given birth and 367 subjects from the general population participated. Greater value was placed on differences between bottom and middle attribute levels than on differences between middle and top levels. The attributes that resulted in larger utility increases than the other attributes were “feeling of safety” in the sample of women who had recently given birth and “feeling of safety” and “availability of professionals” in the general population sample.

Conclusions

By using the derived preference weights, LADY-X has the potential to be used as a utility measure for perinatal (cost-) effectiveness studies.

Authors

Fania R. Gärtner Esther W. de Bekker-Grob Anne M. Stiggelbout Marlies E. Rijnders Liv M. Freeman Johanna M. Middeldorp Kitty W.M. Bloemenkamp Esteriek de Miranda M. Elske van den Akker-van Marle

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