基于人工智能的全人口查计划的成本效益,用于荷兰的初级开放角度眼镜
Bart-Jan Boverhof1, Isaac Corro Ramos2, Koen A Vermeer3
1Erasmus School of Health Policy and Management, Erasmus University, Rotterdam, The Netherlands.
概括
在荷兰,人工智能 (AI) 用 fundus 照片对玻璃眼查是具有成本效益的. 与机会性查相比,这种AI方法改善了早期检测,并减少了视力障碍.
科学领域:
- 眼科医生 眼科 眼科
- 卫生经济学 卫生经济学
- 人工智能的人工智能
背景情况:
- 由于患病率低,成本高,全民大眼查往往不具有成本效益.
- 机会主义的病例发现是当前的标准,但在早期检测方面存在局限性.
研究的目的:
- 评估基于人工智能 (AI) 的重复眼查的成本效益,使用荷兰人口 (年龄在50-75岁) 中的 fundus 照片.
- 为了比较AI查与初级开角绿眼病的机会性病例发现.
主要方法:
- 开发了一种健康经济模型,其中包括用于查模拟的决策树和疾病进展的马尔科夫模型.
- 人工智能查涉及每5年重复一次 fundus 摄影,并进行人工智能分类,随后对阳性病例进行眼科评估.
- 模型输入来源于人工智能开发数据,荷兰队列,专家意见和文献,分析一生中的社会和医疗保健观点.
主要成果:
- 与机会主义方法相比,人工智能查检测到1.60倍多的青光眼病例,每个人视力损伤减少了0.8个月.
- 增量成本效益比 (ICER) 为每获得的质量调整后寿命年19,311欧元,低于20,000欧元门的概率为51.2%.
- 青光眼的进展率,公用事业和视力障碍成本是影响结果的最敏感因素.
结论:
- 在荷兰,基于人工智能的玻璃眼查提供了一种具有成本效益的策略,以提高早期检测并减轻视力障碍的负担.
- 建议进行进一步的研究,以解决疾病进展率和与视力障碍相关的成本的不确定性.
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