Implementation of a lean-focused, patient-centric rounding structure stressing essential processes was associated with increased timeliness and efficiency of rounds, improved staff and customer satisfaction, improved throughput, and reduced attending physician man-hours.
Disasters have recently received the attention of the operations research community because of the great potential of improving disaster‐related operations through the use of analytical tools, and the impact on people that this implies. In this introductory article, we describe the main characteristics of disaster supply chains, and we highlight the particular issues that are faced when managing these supply chains. We illustrate how operations research tools can be used to make better decisions, taking debris management operations as an example, and discuss potential general research directions in this area.
We present a two-phase model for a staff planning problem in a surgical department. We consider the setting where staff, in particular nurse circulators and surgical scrub technicians, are assigned to one of different service lines, and while they can be 'pooled' and temporally assigned to other service line if needed, these re-assignments should belimited. In Phase I, we decide on the number of staff hours to budget for each service line, considering policies limiting staff pooling and overtime, and different demand scenarios. In Phase II, we determine how these budgeted staff hours should be allocated across potential work days and shifts, given estimated staff requirements and shift-related scheduling restrictions. We propose a heuristic to speed the model's Phase II solution time. We implement the model using a hospital's surgical data and compare the model's results with the hospital's current practices. Using a simulation model for the surgical operations, we find that our two-phase model reduces the delays caused by staff unavailability as well as staff pooling, without increasing the workforce size. Finally, we briefly describe a decision-support tool we developed with the objective of fine-tuning staff planning decisions.
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