Zang Grace Yuange, Rao Keqin, Wu Anthony Ting-Yuk, Tang Yi, Zhang Zongjiu
Institute for Hospital Management, Tsinghua University, Beijing, China.
Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MA, USA.
J Alzheimers Dis Rep. 2025 May 4;9:25424823251337941. doi: 10.1177/25424823251337941. eCollection 2025 Jan-Dec.
Population aging increases the economic burden of Alzheimer's disease (AD). Early screening for mild cognitive impairment (MCI) has the potential to mitigate this burden, but optimal strategies regarding screening coverage and age targeting remain unclear.
To explore the impact of varying MCI screening coverage and age-specific screening strategies on the AD population size and the associated healthcare costs in Shanghai, using a system dynamics approach.
A system dynamics model was developed to evaluate disease population and economic costs associated with MCI and AD at different coverage levels and age groups. A cost-benefit comparison was conducted to identify the screening coverage rate and age threshold that maximize cost-effectiveness, balancing reductions in AD-related costs against increases in screening expenditures.
Increasing MCI screening coverage significantly reduced economic costs across the AD spectrum but also increased overall screening expenditures. Expanding screening to additional age groups produced similar effects. Cost-benefit analysis identified an optimal strategy: initiating screening at age 60 or 65 with 80% coverage, which achieves substantial cost savings while avoiding the diminishing returns and excessive expenditures associated with broader, less targeted screening approaches.
Strategically designed MCI screening can reduce the economic burden of AD, improve public health outcomes, and promote social well-being. To maximize societal benefit, screening scope must be balanced with cost. Policymakers and healthcare professionals should tailor strategies to local contexts and urgently adopt innovative technologies such as digital health and artificial intelligence-based solutions, to enhance accessibility and scalability of MCI screening strategy.
人口老龄化增加了阿尔茨海默病（AD）的经济负担。早期筛查轻度认知障碍（MCI）有可能减轻这一负担，但关于筛查覆盖率和年龄目标的最佳策略仍不明确。
采用系统动力学方法，探讨不同的MCI筛查覆盖率和特定年龄筛查策略对上海AD患者数量及相关医疗费用的影响。
建立一个系统动力学模型，以评估不同覆盖率水平和年龄组与MCI和AD相关的疾病人口和经济成本。进行成本效益比较，以确定能使成本效益最大化的筛查覆盖率和年龄阈值，在降低AD相关成本与增加筛查支出之间取得平衡。
提高MCI筛查覆盖率显著降低了整个AD谱系的经济成本，但也增加了总体筛查支出。将筛查范围扩大到更多年龄组产生了类似效果。成本效益分析确定了一种最佳策略：在60岁或65岁开始筛查，覆盖率为80%，这在避免与更广泛、针对性较差的筛查方法相关的收益递减和过度支出的同时，实现了大幅成本节约。
精心设计的MCI筛查可以减轻AD的经济负担，改善公共卫生结果，并促进社会福祉。为了使社会效益最大化，筛查范围必须与成本相平衡。政策制定者和医疗保健专业人员应根据当地情况调整策略，并迫切采用数字健康和基于人工智能的解决方案等创新技术，以提高MCI筛查策略的可及性和可扩展性。
