一个定量模型,以确保在远程患者监测计划中确保足够的容量及时获得护理
Annie Chang1,2, Michael Z Gao2, Johannes O Ferstad2
1Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Endocrinology, diabetes & metabolism
|June 22, 2023
概括
一个新的模型和仪表板帮助诊所规划远程患者监测 (RPM) 程序的容量,确保对1型糖尿病 (T1D) 患者的及时护理. 该系统确定了关键指标,以有效地将患者需求与提供者资源相匹配.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 临床信息学 临床信息学
- 儿科内分泌学 儿科内分泌学
背景情况:
- 算法支持的远程患者监控 (RPM) 为医疗保健提供者带来了运营挑战.
- 现有的容量规划模型对于RPM程序来说是不够的,可能会影响患者及时获得护理.
- 需要一种标准化的方法来管理对RPM服务的日益增长的需求,特别是在儿科环境中.
研究的目的:
- 开发一款灵活的模型和交互式仪表板,用于在全人口的RPM基础上为1型糖尿病 (T1D) 提供护理的能力规划.
- 确定关键的运营,人口和劳动力指标,这些指标会影响RPM程序中的护理提供者需求.
- 促进儿童内分泌学RPM计划的系统设计和扩展.
主要方法:
- 对277名儿科T1D患者每周RPM计划的两年运行数据的分析.
- 与护理团队进行代采访,以确定需求驱动指标.
- 基于确定指标的交互式容量规划模型和仪表板的开发.
主要成果:
- 人口层面的需求驱动因素包括患者数量,入学/毕业率和数据审查频率.
- 临床级容量驱动因素包括提供者数量,数据审查时间和分配的提供者时间.
- 该模型确定了切实可行的策略,以使护理需求与研究机构可用的资源保持一致.
结论:
- 为RPM容量规划开发了一种可通用,系统的模型,并作为交互式仪表板部署.
- 该模型成功地促进了对新诊断的T1D患者的新型护理计划的扩展.
- 这种方法可以支持系统设计和实施有效的基于RPM的护理计划.
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