数据创伤:一个概念分析分析
1Author Affiliation: School of Nursing, University at Buffalo, NY.
Computers, informatics, nursing : CIN
|December 12, 2024
概括
医疗保健 医疗保健 医疗保健 医疗保健
科学领域:
- 医疗信息学 医疗信息学
- 数字健康伦理学 数字健康伦理学
- 医学社会学 医学社会学
背景情况:
- 人工智能 (AI) 和算法在医疗保健中的日益集成引发了人们对意外后果的担忧.
- 患者数据是敏感的和潜在的污名化,需要仔细考虑其收集,存储和使用.
- 这是一个很棒的节目,这是一个很棒的节目.
- 数据化数据化数据化
- 在医疗保健机构中的个体的行为带来了新的伦理挑战.
研究的目的:
- 引入和定义iatrogenic数据创伤的概念.
- 探索与收集,存储和使用患者数据相关的风险和危害.
- 分析数据处理如何影响患者福祉和健康公平.
主要方法:
- 使用沃克和阿万特的框架进行概念分析.
- 关于学术和数字来源的综合文献综述.
- 证据综合和实践示例说明.
主要成果:
- Iatrogenic数据创伤源于医疗保健中的数据处理有缺陷.
- 这种创伤可能会加剧健康差距,边缘化和隐私侵犯.
- 它在整个医疗连续性中侵蚀了患者与提供者关系的信任.
结论:
- Iatrogenic数据创伤是影响多个医疗保健学科的一个重要问题.
- 了解和处理数据创伤对于在医疗保健中实施道德AI至关重要.
- 未来的研究应该采用创伤信息化的方法来调查与数据相关的危害.
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