Assessing patient information needs for new antidiabetic medications to inform shared decision-making: A best-worst scaling experiment in China.

Abstract

Shared decision-making (SDM) is a patient-centred approach to improve the quality of care. An essential requirement for the SDM process is to be fully aware of patient information needs. Our study aimed to assess patient information needs for new antidiabetic medications using the best-worst scaling (BWS) experiment. BWS tasks were developed according to a literature review and the focus group discussion. We used a balanced incomplete block design and blocking techniques to generate choice sets. The final BWS contains 11 attributes, with 6-choice scenarios in each block. The one-to-one, face-to-face BWS survey was conducted among type 2 diabetic patients in Jiangsu Province. Results were analyzed using count-based analysis and modelling approaches. We also conducted a subgroup analysis to observe preference heterogeneity. Data from 539 patients were available for analysis. The most desired information domain was the comparative effectiveness of new antidiabetic medications. It consists of the incidence of macrovascular complications, the length of extended life years, changes in health-related quality of life, the incidence of microvascular complications, and the control of glycated haemoglobin. Of all the attributes, the incidence of macrovascular complications was the primary concern. Patients' glycemic control and whether they had diabetes complications exerted a significant influence on their information needs. Information on health benefits is of critical significance for diabetic patients. Patients have different information needs as their disease progresses. Personalized patient decision aids that integrate patient information needs and provide evidence of new antidiabetic medications are worthy of being established. Before data collection, a pilot survey was carried out among diabetic patients to provide feedback on the acceptability and intelligibility of the attributes.