Sequencing Daily Patient Workload for an Ancillary Service Provider

Ancillary service providers (ASPs) on an inpatient unit (IU), such as social workers, care managers, and physical and occupational therapists, play crucial roles in the inpatient discharge process. However, on a typical day, these ASPs must balance the needs of newly arriving, recurring, and outgoing patients (discharges). While prioritizing the discharges is shown to improve the hospital patient flow and bed utilization, the needs of the other patients cannot be neglected. We examine whether patient sequencing strategies for these ASPs can be found that maintain patient care and optimize patient flow. We approach this ASP workload sequencing problem by proposing a stochastic optimization model and developing a simulated annealing algorithm to derive sequencing strategies that are easy to implement and promising to all scenarios. Our experimental results suggest that patients with pressing constraints should be prioritized over discharges, with discharges then prioritized over other patients. As the complexity of the workload increases (a large number of patients and/or a high percentage of discharges), the focus should shift more towards discharges. We further evaluate the performance of our derived strategies against simpler realistic ASP sequencing strategies and classical machine scheduling rules. Our strategies consistently perform well on deviation from the optimal upstream boarding time and always ensure that patient constraints are met; other simpler strategies can outperform ours only at the cost of increases in cutoff and due-date violations. This paper reveals the importance of a systemic view (inpatient and upstream) on the part of the ASP when prioritizing patients in an IU. Note to Practitioners -This paper was motivated by the problem of sequencing patients daily for ancillary service providers (ASPs) on an inpatient unit (IU). This work is applicable to such ASPs as care managers and therapists. We derive patient sequencing strategies (rules), which they can apply to prioritize their patient workload in such a way that upstream patient boarding time is minimized without affecting the promptness of care for recurring and newly arriving patients. We develop a mathematical model that faithfully captures an ASP's workload dynamics and a heuristic approach to derive easy-to-use, sequencing strategies. An experimental study using retrospective data and interviews with ASPs from a large teaching hospital in the Northeast U.S. led to a set of strat