For public hospital managers, on the one hand, they must best utilize their hospital beds to serve the COVID-19 patients immediately. In many countries and territories, public hospitals play a major role in coping with the COVID-19 pandemic. Moreover, we identify future research directions that provide opportunities for expanding existing methodologies and especially for narrowing the gap between theory and practice. This is due to the fact that inpatient surgery duration is longer and more variable and to the presence of more emergency patients, although there is a higher likelihood of no-shows for outpatients. We find that outpatient surgery can observe better results in many of the performance measures (i.e., operating room utilization, overtime, and patient cancellation rate) as opposed to inpatient surgery. The literature published between 20 that explicitly mentions either scheduling setting is included and it is analyzed from three dimensions, i.e., the uncertainty incorporation, the research methodology, and a scheduling performance comparison between both settings. This paper provides the first literature review on comparing outpatient surgery scheduling with inpatient surgery scheduling. Identifying possible similarities and differences between outpatient surgery scheduling and inpatient surgery scheduling can serve as a valuable decision-making foundation for practitioners and for operations researchers to efficiently schedule patients for surgery in the surgical department. More recently, a shift from inpatient surgery to outpatient surgery is occurring due to scientific progress in anaesthesia and surgical techniques. Outpatients are normally routine patients that enter and leave the hospital on the same day, while inpatients who need more complex surgeries have to stay overnight. In hospitals, surgeries are treated either on an outpatient or on an inpatient basis. In contrast, a scheduling policy based on downstream capacity usage often performs relatively close to the integrated scheduling policy, and therefore may serve as a simple, effective scheduling heuristic for hospital managers–especially when the downstream capacity is costly and less flexible. The traditional scheduling policy, which is solely driven by operating room usage, however, can lead to significantly suboptimal use of downstream capacity and, as our numerical experiments show, may result in up to a three‐fold increase in total expenses. Our simulations based on real data demonstrate substantial values in making integrated scheduling decisions that simultaneously consider capacity usage at all locations in a hospital, especially when demand and system capacities are balanced or more elective patients present in the patient mix. We conduct extensive simulation experiments to study the applicability of our theoretical model in various settings. This transformation, in particular, allows us to show that the optimal number of patients to admit increases when the waitlist of surgical patients is longer, given the number of patients recovering downstream is fixed. Via a simple and yet innovative variable transformation we reveal the hidden submodularity structure in our model. To address such a shortcoming we introduce the first Markov Decision Process model for scheduling surgical patients on a daily basis, explicitly taking into account patient length‐of‐stay in hospital after surgeries and inpatient census. Despite the fact that hospital care is often delivered in successive stages, current healthcare scheduling and capacity planning methods usually treat different hospital units in isolation.
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