计算生物医学知识的应用,以改变以患者为中心的调度
Namita Azad1, Carolyn Armstrong1, Corinne Depue1
1Columbia University Irving Medical Center New York New York USA.
Learning health systems
|October 20, 2023
概括
使用新的调度算法优化门诊预约,最大限度地减少了患者等待时间和医生置时间. 这种解决方案通过有效地分组预约来提高医疗保健的效率.
科学领域:
- 医疗保健 运营 研究 研究 研究
- 医疗信息学 医疗信息学
- 临床工作流程优化 临床工作流程优化
背景情况:
- 门诊安排面临的挑战是变化,不确定性,不出现和入诊,导致患者等待时间和资源不足利用.
- 现有的调度方法在门诊环境中通常是有限的,与住院环境不同.
研究的目的:
- 为门诊机构开发和试点一个优化的预约安排解决方案.
- 为了尽量减少相关程序之间的时间,并减少患者的总体预期时间.
主要方法:
- 开发了一种线性整数编程模型来选择最佳的约会分组.
- 该模型包含预约请求,资源可用性,订单限制和患者偏好.
- 该解决方案包括在电子医疗记录系统中集成的技术基础设施.
主要成果:
- 计划进行试点研究,在一个部门评估算法.
- 关键绩效指标包括时间表的利用率,资源置时间,患者满意度以及预约领先/等待时间.
- 通过非正式的员工访谈收集定性数据.
结论:
- 开发的算法旨在提高门诊调度效率.
- 未来的改进包括将机器学习纳入访问类型的变化,并将系统扩展到其他部门.
- 目标是提高准确性,灵活性,并最终提高患者护理.
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