Valuing injection frequency and other attributes of type 2 diabetes treatments in Australia: a discrete choice experiment

Simon Fifer, John Rose, Kim K. Hamrosi, Dan Swain

Multiple pharmacotherapy options are available to control blood glucose in Type 2 Diabetes Mellitus (T2DM). Patients and prescribers may have different preferences for T2DM treatment attributes, such as mode and frequency of administration, based on their experiences and beliefs which may impact adherence. As adherence is a pivotal issue in diabetes therapy, it is important to understand what patients value and how they trade-off the risks and benefits of new treatments. This study aims to investigate the key drivers of choice for T2DM treatments, with a focus on injection frequency, and explore patients' associated willingness-to-pay. A discrete choice experiment (DCE) was used to present patients with a series of trade-offs between different treatment options, injectable and oral medicines that were made up of 10 differing levels of attributes (frequency and mode of administration, weight change, needle type, storage, nausea, injection site reactions, hypoglycaemic events, instructions with food and cost). A sample of 171 Australian consenting adult T2DM patients, of which 58 were receiving twice-daily injections of exenatide and 113 were on oral glucose-lowering treatments, completed the national online survey. An error components model was used to estimate the relative priority and key drivers of choice patients place on different attributes and to estimate their willingness to pay for new treatments. Injection frequency, weight change, and nausea were shown to be important attributes for patients receiving injections. Within this cohort, a once-weekly injection generated an additional benefit over a twice-daily injection, equivalent to a weighted total willingness to pay of AUD$22.35 per month. Based on the patient preferences, the importance of frequency of administration and other non-health benefits can be valued. Understanding patient preferences has an important role in health technology assessment, as the identification of the value as well as the importance weighting for each treatment attribute may assist with funding decisions beyond clinical trial outcomes.