人员配置优化
公司规模
Large Corporate
地区
- Europe
国家
- United Kingdom
产品
- DSS Patient Forecasting System
技术栈
- Machine Learning
- API
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
- Employee Satisfaction
技术
- 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
用例
- 补货预测
服务
- 数据科学服务
关于客户
客户是英国一家大型医疗服务提供商。它拥有约 1700 名员工，负责为大量人口提供医疗服务。医院致力于为患者提供尽可能优质的护理，这需要高效且有效的人员配备。然而，医院正努力应对人员配备效率低下的问题，这导致医生工作过度、患者不满和成本过高。医院寻求一种解决方案，使其能够更好地预测患者数量，并以更透明、更高效的方式做出人员配备决策。
挑战
英国一家大型医疗服务提供商正努力解决人员配置效率低下的问题，导致医生过度劳累、患者不满和成本高昂。该医院的人员配置流程主要是手动的，并且基于可用床位数量，这无法有效分配人员配置时间。缺乏数据驱动的决策阻碍了医院提供最佳护理和留住最佳医生的能力。该医院寻求一种技术解决方案，使其能够小规模地模拟患者流量，并根据患者需求预测推荐人员配置计划。
解决方案
该医院与 DSS 合作建立并实施了患者预测系统应用程序。该应用程序会自动编译和处理内部和历史数据以及外部数据集，例如天气、全国流行病、节假日和交通。然后，机器学习算法会构建一个预测患者需求的统计模型。随着新数据被纳入模型，该预测会不断改进。API 将预测模型链接到人员安排系统，根据时间、日期和部门，为人员安排经理在其排班工具中提供更新的人员安排建议。
运营影响
数量效益
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