4.3 Article

Education and patient preferences for treating type 2 diabetes: a stratified discrete-choice experiment

期刊

PATIENT PREFERENCE AND ADHERENCE
卷 11, 期 -, 页码 1729-1736

出版社

DOVE MEDICAL PRESS LTD
DOI: 10.2147/PPA.S139471

关键词

preference heterogeneity; stated-preference methods; preference heterogeneity; willingness-to-pay; choice experiment; educational attainment

资金

  1. Patient-Centered Outcomes Research Institute (PCORI) [ME-1303-5946]
  2. Center for Excellence in Regulatory Science and Innovation (CERSI) [1U01FD004977-01]

向作者/读者索取更多资源

Purpose: Diabetes is a chronic condition that is more prevalent among people with lower educational attainment. This study assessed the treatment preferences of patients with type 2 diabetes by educational attainment. Methods: Patients with type 2 diabetes were recruited from a national online panel in the US. Treatment preferences were assessed using a discrete-choice experiment. Participants completed 16 choice tasks in which they compared pairs of treatment profiles composed of six attributes: A1c decrease, stable blood glucose, low blood glucose, nausea, treatment burden, and out-of-pocket cost. Choice models and willingness-to-pay (WTP) estimates were estimated using a conditional logit model and were stratified by educational status. Results: A total of 231 participants with a high school diploma or less education, 156 participants with some college education, and 165 participants with a college degree or more completed the survey. Participants with a college degree or more education were willing to pay more for A1c decreases ($58.84, standard error [SE]:10.6) than participants who had completed some college ($28.47, SE:5.53) or high school or less ($17.56, SE:3.55) (p <= 0.01). People with a college education were willing to pay more than people with high school or less to avoid nausea, low blood glucose events during the day/night, or two pills per day. Conclusion: WTP for aspects of diabetes medication differed for people with a college education or more and a high school education or less. Advanced statistical methods might overcome limitations of stratification and advance understanding of preference heterogeneity for use in patient-centered benefit-risk assessments and personalized care approaches.

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