Assessment of patient preferences for assisted reproductive technology in China: a discrete choice experiment.

Abstract

Objectives: Given China's low fertility rate, assisted reproductive technology (ART) can be used assist infertile patients in having children. This study aimed to analyse patients' preferences for ART and to determine the relative importance (RI) and willingness to pay (WTP) of key attributes.

Design: We identified six attributes of ART and used a D-efficient design to generate choice sets for conducting a discrete choice experiment. Patients were asked to choose between two scenarios that differed in participation in treatment decision-making (TDM), clinical pregnancy rate, live birth rate, risk of maternal and neonatal complications, and out-of-pocket cost.

Setting: Jiangsu province, China. The anonymous survey was carried out between December 2022 and February 2023.

Participants: Female patients aged 20-45 years, with low fertility or experience of ART treatment. We recruited 465 participants.

Outcomes measures: Patient-reported preferences for each attribute were estimated using a mixed logit model. The latent class model was also used to investigate preference heterogeneity.

Results: All attributes were associated with patient preferences. Patients considered the live birth rate as the most important attribute (RI=29.05%), followed by participation in TDM (RI=21.91%). The latent class model revealed two distinct classes named 'outcome driven' and 'cost driven'. Preferences varied according to their age, monthly household income and location.

Conclusions: This study investigated the preferences of infertile patients when seeking medical assistance for infertility. The study outcomes can contribute to evidence-based counselling and shared decision-making and provide an empirical basis for creating and implementing future policies.