在一个大型卫生系统中,使用混合整数线性编程方法重新分配化疗预约
1Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.
Health systems (Basingstoke, England)
|May 29, 2025
概括
通过将预约从主要地点重新分配到未充分利用的地点,优化门诊化疗安排可以提高患者满意度和资源利用率. 该战略利用旅行距离数据来提高整个卫生系统的效率.
科学领域:
- 卫生系统科学 卫生系统科学
- 运营研究 运营研究
- 瘤病患者护理专业的患者护理
背景情况:
- 门诊化疗安排显著影响患者满意度和卫生系统资源利用率.
- 目的地医疗中心往往面临着大量的预约,造成资源紧张.
- 患者的旅行距离是影响治疗地点偏好和安排决策的关键因素.
研究的目的:
- 开发和评估一种用于重新分配门诊化疗预约的模型,以优化卫生系统资源利用.
- 通过利用其他系统位置,评估在初级处理地点减压预约体积的潜力.
- 分析患者旅行距离对预约重新分配策略的影响.
主要方法:
- 开发了一个混合整数线性编程 (MILP) 模型来重新分配约会.
- 该模型考虑了任命再分配的四个不同的场景.
- 该方法应用于来自明尼苏达州梅奥诊所卫生系统地区的现实数据.
主要成果:
- 该研究表明,有可能将大约50%的符合条件的门诊化疗预约从主要地点转移.
- 这种重新分配导致约30%的总体变化,任命量分布.
- 利用未充分利用的地点有效地利用瘤护士和椅子的可用性.
结论:
- 重定位门诊化疗预约可以显著提高卫生系统内的效率和资源管理.
- 将患者的旅行距离纳入调度模型是成功重新分配预约的关键.
- 这种方法提供了一个可行的战略,以优化化疗交付和患者在多个站点访问.
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