做正义:伦理考虑 识别和研究变性人和性别多样的人在保险索赔数据数据中
Ash B Alpert1,2,3,4, Gray Babbs5, Rebecca Sanaeikia6
1Yale Cancer Center, 333 Cedar Street, WWW 205, New Haven, CT, 06511, USA. ash.alpert@yale.edu.
Journal of medical systems
|October 11, 2024
概括
跨性别和性别多样性 (TGD) 个体的健康数据有限. 用于在健康数据中识别TGD人群的基于索赔的算法引发了重大的伦理担忧,并可能使偏见永久化.
科学领域:
- 医疗信息学 医疗信息学
- 流行病学 流行病学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 对于跨性别和性别多样性 (TGD) 的人群,存在有限的健康数据.
- 研究人员利用保险索赔数据来研究TGD的健康负担.
- 开发了算法,以使用诊断,程序和处方代码在索赔数据中识别TGD个体.
研究的目的:
- 探索使用基于索赔的算法来识别TGD个体的认识论和伦理复杂性.
- 讨论这些算法对cisnormative偏见和TGD自我识别的影响.
- 用声明数据为TGD健康研究提供道德考虑和建议.
主要方法:
- 对现有文献和伦理框架的分析.
- 讨论基于索赔的算法的局限性和潜在危害.
- 在TGD健康研究中应用认识不公正框架.
主要成果:
- 识别TGD个体的基于索赔的算法可以延续cisnormative偏见.
- 这些算法可能会忽视TGD个体的自我识别.
- 伦理复杂性来自于从非识别数据中推断性别身份.
结论:
- 关于TGD健康的基于索赔的研究需要谨慎的伦理导航.
- 必须优先考虑最大限度地减少对TGD社区的伤害,最大限度地提高对TGD社区的益处.
- 解决认识系统的不公正对于公平的TGD健康研究至关重要.
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