The flexibility level allowed in nursing care delivery and the uncertainty in infusion durations are important factors for chemotherapy scheduling. The nursing care delivery scheme employed in an outpatient chemotherapy clinic (OCC) determines the strictness of the patient-to-nurse assignment policies, while the estimation of infusion durations affects the trade-off between patient waiting time and nurse overtime. We study the problem of daily scheduling of patients, assignment of patients to nurses and chairs in the presence of uncertainty in infusion durations for an OCC that functions according to any of the commonly used nursing care delivery system representing fully, partially, and inflexible care systems. We develop a two-stage stochastic mixed-integer programming model minimizing expected weighted cost of patient waiting time and nurse overtime. We propose multiple variants of a scenario grouping-based decomposition algorithm to solve the model using data from a major university oncology hospital. We compare input-based, solution-based, and random scenario grouping methods within the decomposition algorithm. We obtain near-optimal schedules that are also significantly better than the schedules generated based on the policy used in the clinic. We analyze the impact of nursing care flexibility in order to determine whether a partial or fully flexible delivery system is necessary to adequately improve waiting time and overtime.

护理服务的灵活性和输注持续时间的不确定性是化疗安排的重要因素。门诊化疗诊所（OCC）采用的护理服务方案决定了患者与护士分配政策的严格程度，而输液持续时间的估计则影响患者等待时间和护士加班时间之间的权衡。我们研究 OCC 的输液持续时间不确定的情况下患者的日常安排、患者分配给护士和椅子的问题，该 OCC 根据代表完全、部分和不灵活的护理系统的任何常用护理服务提供系统发挥作用。我们开发了一个两阶段随机混合整数规划模型，最大限度地减少患者等待时间和护士加班的预期加权成本。我们提出了基于场景分组的分解算法的多种变体，以使用来自一家主要大学肿瘤医院的数据来求解模型。我们在分解算法中比较了基于输入、基于解决方案和随机场景分组方法。我们获得了接近最佳的时间表，该时间表也明显优于根据诊所使用的策略生成的时间表。我们分析护理灵活性的影响，以确定是否需要部分或完全灵活的交付系统来充分改善等待时间和加班时间。