患者排程优化（患者未就诊预测分析）
公司规模
Large Corporate
地区
- America
国家
- United States
产品
- Intermedix technology-enabled services
- Dataiku DSS
技术栈
- Dataiku DSS
- Python
- R
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
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
- 商业运营
用例
- 补货预测
服务
- 数据科学服务
关于客户
Intermedix 成立于 2002 年，为医疗服务提供商、政府机构和企业提供技术支持服务和 SaaS 解决方案。作为全球健康和安全网技术支持解决方案的领先提供商，Intermedix 为 15,000 多家医疗服务提供商提供实践管理、收入周期管理和数据分析工具。该公司为 95% 以上的美国人口提供危机管理和应急准备技术。Intermedix 目前正在帮助 50 多家诊所降低与患者缺席相关的成本。
挑战
医疗行业正在努力应对患者失约率高的问题，研究表明，5-10% 的预约患者会错过预约。这对医疗机构的财务状况及其照顾其他患者的能力产生了重大影响。初级保健医生每失约一次，平均损失 228 美元，专科医生的收入损失甚至更高。当患者错过预约时，包括人员配备、保险和水电费在内的间接费用将无法报销。初级保健医生取消预约还会影响这些医生可以进行的必要专科转诊数量。这些因素加在一起，导致医生的收入损失惨重。为了帮助最大限度地减少失约的发生，从而降低相关成本，Intermedix 决定开发并实施一种失约预测器，以帮助办公室经理安排预约。
解决方案
Intermedix 向其数据科学团队介绍了 Dataiku DSS，以开发和实施失约预测器。该团队设置了自动提取和处理历史、预约和人口统计患者数据的功能。数据科学家建立了一个预测模型，根据患者在分配的时间段内错过预约的概率对个体患者进行评分。根据需求，此输出每周自动多次直接反馈给每个诊所。办公室经理和调度员可以使用此预测报告来优化医生的日程安排和患者预约。开发和部署此类应用程序以涵盖特定站点的模式通常需要 3 个月以上的时间。但是，借助 Dataiku DSS，Intermedix 的数据科学团队能够在短短一个月内制作原型并交付解决方案。
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