在下肢手术的住院治疗中应用的分类算法
Marta Rosaria Marino1, Vincenzo Bottino2, Giacomo Negri2
1Department of Public Health, University of Naples "Federico II", Naples, Italy.
Studies in health technology and informatics
|June 30, 2023
概括
这项研究使用分类算法预测患者在下肢手术中的停留时间 (LOS). 后勤回归实现了最高准确率的94%,有助于医疗保健资源管理.
科学领域:
- 医疗保健管理的管理
- 医疗信息学 医疗信息学
- 手术结果分析手术结果分析
背景情况:
- 医疗保健系统面临着提高患者价值和降低成本的压力.
- 绩效指标对于评估医疗保健流程至关重要,而逗留时间 (LOS) 是一个关键指标.
- 预测LOS对于优化资源配置至关重要,特别是对于人口老龄化中的常见程序.
研究的目的:
- 采用分类算法来预测接受下肢手术的患者的停留时间 (LOS).
- 评估各种算法在预测患者LOS在特定医疗保健环境中的性能.
主要方法:
- 利用分类算法来分析患者数据,以预测停留时间 (LOS).
- 专注于在意大利那不勒斯的福音派医院"贝塔尼亚"接受下肢手术的患者 (2019-2020).
- 在LOS预测中比较了多个算法的准确性.
主要成果:
- 所有评估的分类算法都在预测患者LOS时表现出超过90%的准确性.
- 后勤回归成为了表现最好的算法,在LOS预测中达到94%的准确性.
- 这些发现有助于对意大利南部医院绩效进行更大规模的多中心研究.
结论:
- 分类算法,特别是物流回归,在预测下肢手术患者的停留时间方面非常有效.
- 准确的LOS预测可以显著改善医疗保健资源管理和患者价值.
- 这项研究支持数据驱动的战略,以优化手术患者护理途径.
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