Cost‐effectiveness of continuous glucose monitoring in Chinese adults with uncontrolled type 2 diabetes: A modelling study stratified by baseline HbA 1c

作者
Guangxin Han,Yubing Ye,Yuan Fang,Jisheng Chen,Sha Lai
出处
期刊:Diabetes, Obesity and Metabolism [Wiley]
标识
DOI:10.1111/dom.70333
摘要

Abstract Objective To evaluate the long‐term cost‐effectiveness of continuous glucose monitoring (CGM) versus self‐monitoring of blood glucose (SMBG) in Chinese adults with uncontrolled type 2 diabetes (T2D) to inform optimal disease management and reimbursement policies. Methods The United Kingdom Prospective Diabetes Study Outcomes Model version 2 was used to simulate 30‐year cost and health outcomes for cohorts with baseline HbA 1c levels of 7.70%, 8.70%, 9.70%, and 10.70%. Clinical efficacy data were derived from meta‐analyses. A cost‐effectiveness analysis from China's healthcare perspective referenced a $40 344 per quality‐adjusted life year (QALY) willingness‐to‐pay (WTP) threshold, equal to three times China's per capita gross domestic product (GDP). Sensitivity and scenario analyses addressed model uncertainty and determined annual CGM cost thresholds. Results For baseline HbA 1c levels of 7.70%–10.70%, CGM yielded incremental cost‐effectiveness ratios (ICERs) of $29 428 to $38 819 per QALY gained, respectively—all below the WTP threshold. Higher baseline HbA 1c was associated with greater cost‐effectiveness. Sensitivity analyses showed CGM utility benefits and device costs were key drivers. All cohorts demonstrated >96% cost‐effectiveness probability. Annual CGM cost thresholds for cost‐effectiveness ranged from $1920 to $2316 depending on baseline HbA 1c levels of 7.70%–10.70%. Conclusions CGM represents a cost‐effective intervention for Chinese adults with uncontrolled T2D, demonstrating enhanced economic value in populations with elevated baseline HbA 1c levels. Implementing risk‐stratified reimbursement policies coupled with price negotiations aligned with evidence‐based cost thresholds ($1920–$2316 annually), may optimize healthcare resource allocation.
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