公共风险感知,机构AI采用和诊断安全:利用追踪条件方法进行探索性跨层次分析
Zhichao Li1, Mengxue Lyu1,2, Jilin Huang1,3
1School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, China.
Digital health
|March 9, 2026
概括
社会对医疗人工智能 (AI) 的担忧限制了医院的采用. 然而,人工智能在重症监护中的使用增加与更多的诊断错误有关,强调需要仔细监督.
科学领域:
- 社会技术系统 社会技术系统
- 医疗信息学 医疗信息学
- 医疗人工智能的人工智能
背景情况:
- 社会风险感知影响机构采用技术.
- 了解人工智能采用和临床安全之间的联系对于医疗管理至关重要.
- 现有的研究往往忽略了影响AI在临床环境中的实施的社会技术因素.
研究的目的:
- 检查公众对医疗人工智能的看法,医院采用模式和临床安全结果之间的社会技术联系.
- 评估社会压力如何影响医院人工智能策略.
- 评估人工智能使用强度和急性护理诊断错误之间的关联.
主要方法:
- 使用技术接受模型和机构理论构建了一个跨层次的分析框架.
- 综合调查数据 (N=4764),医院运营面板 (1728个医院月观察) 和社交媒体情绪.
- 用人结构方程建模与时间滞后分析和稳定性检查的双重验证.
主要成果:
- 较高的公众风险感知与较低的医院AI应用频率 (算法厌恶) 有关.
- 人工智能使用强度增加与急性成像依赖条件 (自动化偏差) 中更高的误诊率相关.
- 公众的信任和地理偏远程度减轻了这些影响.
结论:
- 公共风险感知作为AI部署的制度约束.
- 在急性护理中不关键的AI依赖可能会降低诊断警.
- 为了实现安全的数字健康实施,平衡社会接受与临床监督是必不可少的.
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