构建医院部门发展级评估模型:复杂医院数据环境中的机器学习和专家咨询方法
Jingkun Liu1, Jiaojiao Tai1, Junying Han1
1Big Data Analysis Center, Honghui Hospital, Xi'an Jiaotong University, Xi'an, China.
JMIR formative research
|September 4, 2024
概括
一个新的机器学习算法使用客观数据准确评估医院部门的发展. 该模型与专家意见一致,有助于医院的战略管理和资源分配.
科学领域:
- 医疗保健管理的管理
- 数据科学在医学中的数据科学
- 医院管理局 医院管理局
背景情况:
- 医院管理人员致力于稳定,高效的部门.
- 客观数据对于评估医院部门发展至关重要.
- 战略规划需要一个强大的评估模型.
研究的目的:
- 使用客观数据开发医院部门发展评估模型.
- 通过机器学习确定医院部门的关键评估指数.
- 为医院的战略规划和资源分配提供见解.
主要方法:
- 从信息系统中提取了3年的医院部门发展数据.
- 应用神经机器学习算法来评估部门在医院发展中的角色.
- 通过使用统计分析,与高级专家问卷结果对比验证的机器学习风险得分.
主要成果:
- 一个深度机器学习模型准确地预测和评估了医院部门的表现.
- 该模型显示了算法衍生风险排名和专家评估之间的良好匹配.
- 基于客观数据的评估模型被证明是准确和可靠的.
结论:
- 机器学习为评估医院部门发展提供了准确和客观的方法.
- 该模型与专家意见的一致性验证了其对医院管理的可靠性.
- 这种方法可以有效指导战略决策和资源分配.
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