Using discrete choice experiments to elicit preferences for digital wearable health technology for self-management of chronic kidney disease

Citation

Gc 3S, Iglesias CP, Erdem S, Hassan L, Peek N & Manca A (2022) Using discrete choice experiments to elicit preferences for digital wearable health technology for self-management of chronic kidney disease. International Journal of Technology Assessment in Health Care, 38 (1), Art. No.: e77. https://doi.org/10.1017/S0266462322003233

Abstract
Objectives: Wearable digital health technologies (DHTs) have the potential to improve chronic kidney disease (CKD) management through patient engagement. This study aimed to investigate and elicit preferences of individuals with CKD toward wearable DHTs designed to support self-management of their condition. Methods: Using the results of our review of the published literature and after conducting qualitative patient interviews, five-choice attributes were identified and included in a discretechoice experiment. The design consisted of 10-choice tasks, each comprising two hypothetical technologies and one opt-out scenario. We collected data from 113 adult patients with CKD stages 3–5 not on dialysis and analyzed their responses via a latent class model to explore preference heterogeneity. Results: Two patient segments were identified. In all preference segments, the most important attributes were the device appearance, format, and type of information provided. Patients within the largest preference class (70 percent) favored information provided in any format except the audio, while individuals in the other class preferred information in text format. In terms of the style of engagement with the device, both classes wanted a device that provides options rather than telling them what to do. Conclusions: Our analysis indicates that user preferences differ between patient subgroups, supporting the case for offering a different design of the device for different patients’ strata, thus moving away from a one-size-fits-all service provision. Furthermore, we showed how to leverage the information from user preferences early in the R&D process to inform and support the provision of nuanced person-centered wearable DHTs

Keywords
patient preferences; chronic kidney disease; wearable devices; mixed methods; discrete choice experiment; conjoint analysis

Journal
International Journal of Technology Assessment in Health Care: Volume 38, Issue 1

People

Professor Seda Erdem

Professor, Economics