速度,准确性和效率:病理学数字化的承诺和实践
Olsi Kusta1, Margaret Bearman2, Radhika Gorur3
1Department of Public Health, University of Copenhagen, Denmark; Centre for Research in Assessment and Digital Learning (CRADLE), Deakin University, Melbourne, Australia; Øster Farimagsgade 5 opg. B, Building: 15-0-11, 1014, Copenhagen, Denmark.
Social science & medicine (1982)
|February 16, 2024
概括
政策制定者在病理学中推动数字化以提高效率和准确性,但当前的做法显示,它未能实现这些承诺. 未来的人工智能 (AI) 整合可能会解决一些差距,但对病理学家来说带来了新的挑战.
科学领域:
- 医疗保健政策 医疗保健政策
- 医学领域的数字化转型
- 病理学信息学 病理学信息学
背景情况:
- 医疗保健系统面临着日益增长的需求和劳动力短缺.
- 数字化被提议作为政策话语中的解决方案.
- 丹麦是一个高度数字化的国家,正在探索病理学数字化.
研究的目的:
- 对病理学当前的做法进行评估,以评估数字化的政策承诺.
- 了解病理学的数字化转型的政治动态和实际现实.
- 识别政策预期与实践者经验之间的差异.
主要方法:
- 对政策文件和实践者经验进行比较分析.
- 在线搜索和文档分析以确定利益相关者和政策承诺.
- 采访和观察日常病理学工作实践.
主要成果:
- 政策承诺强调通过数字化提高速度,患者安全,诊断准确性和效率.
- 当前的病理学实践并没有完全实现这些数字化的期望.
- 实现政策目标取决于未来的人工智能 (AI) 的开发和实施.
- 病理学家预计人工智能可以处理简单的病例,而复杂,繁的病例则由他们来处理.
结论:
- 病理学数字化在调整政策雄心壮志与实际现实方面面临挑战.
- 政策承诺的政治工作可能会掩盖实施的复杂性.
- 病理学的固有性质可能会对广泛采用数字技术构成独特的障碍.
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