Scheduling surgical specialties in a medical facility is a very complex process. The choice of schedules and resource availability impact directly on the number of patients treated by specialty, cancellations, wait times, and the overall performance of the system. In this paper we present a system-wide model developed to allow management to explore tradeoffs between OR availability, bed capacity, surgeons' booking privileges, and wait lists. We developed a mixed integer programming model to schedule surgical blocks for each specialty into ORs and applied it to the hospitals in a British Columbia Health Authority, considering OR time availability and post-surgical resource constraints. The results offer promising insights into resource optimization and wait list management, showing that without increasing post-surgical resources hospitals could handle more cases by scheduling specialties differently.

We consider the problem of determining optimal appointment schedule for a given sequence of jobs (e.g., medical procedures) on a single processor (e.g., operating room, examination facility), to minimize the expected total underage and overage costs when each job has a random processing duration given by a joint discrete probability distribution. Simple conditions on the cost rates imply that the objective function is submodular and L-convex. Then there exists an optimal appointment schedule which is integer and can be found in polynomial time. Our model can handle a given due date for the total processing (e.g., end of day for an operating room) after which overtime is incurred and, no-shows and emergencies.

We consider the problem of determining optimal appointment schedule for a given sequence of jobs (e.g., medical procedures) on a single processor (e.g., operating room, examination facility), to minimize the expected total underage and overage costs when each job has a random processing duration given by a joint discrete probability distribution. Simple conditions on the cost rates imply that the objective function is submodular and L-convex. Then there exists an optimal appointment schedule which is integer and can be found in polynomial time. Our model can handle a given due date for the total processing (e.g., end of day for an operating room) after which overtime is incurred and, no-shows and emergencies.

Purpose We provide an overview of how to work from home during the coronavirus disease 2019 (COVID‐19) pandemic and what measures should be taken to minimize the negative effects of working from during this time. Conclusions The COVID‐19 pandemic has forced an adaptation process for the whole world and working life. One of the most adaptation measures is working from home. Working from home comes with challenges and concerns but it also has favorable aspects. Practice Implications It is crucial to develop and implement best practices for working from home to maintain a good level of productivity, achieve the right level of work and life balance and maintain a good level of physical and mental health.

The duration of kidney transplant donor evaluation is variable and can be lengthy. Better understanding of the reasons for a prolonged evaluation may inform quality improvement initiatives to reduce unnecessary delays.