Treffer: Nurse-to-patient assignment problem with uncertainties in demand and skill requirements: A stochastic programming approach.

In Home Health Care operations, the Nurse-to-Patient Assignment (NPA) is a critical decision that directly impacts workload balance among nurses, the quality of patient care, and total overtime for home health care providers. The NPA problem involves assigning nurses to patients who require health care services at home over a specified treatment period. Several practical factors must be considered, including the compatibility between a nurse's skill set and a patient's needs, continuity of care, and workload balance. However, in real-world scenarios, patient conditions may change over time during the treatment period, potentially requiring different visit frequencies and nurses with varying skill sets. These changes can disrupt continuity of care and lead to potential overtime for nurses. To address this, we formulate the NPA problem while accounting for uncertainty in both patient demand and skill requirements, and propose a stochastic programming approach to optimize nurse-to-patient assignments. The efficiency of the proposed approach and the impact of various problem characteristics are evaluated through extensive computational experiments. • A nurse-to-patient assignment problem minimizing reassignment and overtime. • Incorporation of uncertainties in both patient demand and skill requirements. • We propose a stochastic programming approach to address the problem. • Superior performance of the proposed method over baseline algorithms under demand uncertainty. • Significant reduction in reassignments due to skill mismatch by modeling skill requirement uncertainty. [ABSTRACT FROM AUTHOR]

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