在医疗保健环境中确定数据科学实施场景的方法:基于多个学术机构的经验的建议
Lillian Sung1, Michael Brudno2, Michael C W Caesar3
1Department of Paediatrics, The Hospital for Sick Children, Institute of Health Policy Management & Evaluation, University of Toronto, Toronto, ON, Canada.
Frontiers in digital health
|March 31, 2025
概括
在医疗保健中确定有效的数据科学实施场景需要明确的价值主张和强大的项目冠军. 成功的方法侧重于创意产生,与优先事项保持一致,以及对数据科学计划的可行性评估.
科学领域:
- 医疗保健数据科学 数据科学
- 临床信息学 临床信息学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 学术医疗机构越来越多地采用数据科学来获得临床见解.
- 确定适合数据科学实施的项目是一个关键的挑战.
- 以前用于场景识别的方法已经产生了不同的成功率.
研究的目的:
- 描述成功和失败的策略,以确定数据科学在医疗保健中的实施场景.
- 为优化未来场景识别流程提供建议.
主要方法:
- 一场为期一天的研讨会,涉及来自多伦多七所学术医疗机构的代表.
- 机构介绍了他们的临床数据科学计划和场景识别方法 (成功和不成功).
- 用内容分析来总结共同的观察和主题.
主要成果:
- 成功的关键因素包括促进多样化的想法组合和明确阐述价值主张.
- 与组织优先事项保持一致,通过批准者进行可行性评估,以及专门的项目冠军至关重要.
- 围绕创意产生,价值主张,优先级,认可和冠军识别出现了共同的主题.
结论:
- 提供了建议,以加强在学术医疗保健环境中识别数据科学实施场景.
- 这些发现为医疗机构提供了实际指导,旨在有效利用数据科学.
- 成功实施取决于战略规划,利益相关者参与和强有力的项目监督.
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