Steward Health Care 利用 DataRobot 的自动化机器学习平台进行预测分析
公司规模
Large Corporate
地区
- America
国家
- United States
产品
- DataRobot’s automated machine learning platform
- Proactive Labor Management (PLM) dashboard
技术栈
- Machine Learning
- Predictive Analytics
- Artificial Intelligence
- Microsoft Azure
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
技术
- 分析与建模 - 机器学习
- 分析与建模 - 预测分析
适用行业
- 医疗保健和医院
适用功能
- 人力资源
- 商业运营
用例
- 预测性维护
- 过程控制与优化
服务
- 数据科学服务
关于客户
Steward Health Care 是美国最大的营利性私立医院运营商。该公司在全国运营着 38 家医院网络。Steward Health Care 致力于提高运营效率并降低其网络内的成本。该公司一直在寻找利用其收集和维护的大量数据来推动价值的方法。Steward Health Care 特别有兴趣使用预测分析、人工智能 (AI) 和机器学习来实现这些目标。该公司拥有一支由信息系统和软件开发执行总监 Erin Sullivan 领导的专业团队，负责寻找这些挑战的解决方案。
挑战
Steward Health Care 是美国最大的营利性私立医院运营商，它面临的挑战是如何利用预测分析、人工智能 (AI) 和机器学习从他们需要收集和维护的大量数据中获取价值。其主要任务是提高 Steward 旗下 38 家医院网络的运营效率，并重点降低成本。该公司决定解决医院运营面临的最紧迫挑战之一 — — 人员配备量。典型的医院人员配备模型是根据平均人口普查和数量设定的，这导致在患者数量高峰和低谷期间效率低下。这导致值班人员的费用和加班费高昂。Steward Health Care 的首席执行官 Ralph de la Torre 博士要求他的团队找到一种更积极主动的方法。
解决方案
Steward Health Care 利用 DataRobot 的自动化机器学习平台来处理他们的数据，快速构建和测试来自该数据的模型，并最终从数据中学习。该项目首先确定了来自网络所有医院的历史数据来源。他们输入到模型中的数据越多，他们就越能微调他们的预测。住院量贡献者主要来自两个主要来源：急诊科 (ED) 和择期手术室 (OR) 时间表。该团队确定了可能影响数量预测的其他外部因素。DataRobot 自动化机器学习平台帮助 Steward 以前所未有的速度构建和测试新的、更准确的模型。Steward 能够在 Erin 和她的团队构建的仪表板中快速将 384 个针对特定日数量的模型和 1,152 个针对特定班次的模型投入生产。这些 DataRobot 模型被输入到 Steward 专有的、正在申请专利的主动劳动力管理 (PLM) 仪表板中，这是一个在 Microsoft Azure 上运行的 SaaS 平台，可供 Steward Health Care 网络内的所有 38 家医院使用。
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