Using implementation science to anticipate adoption challenges for an operations research solution in a children’s hospital

Abstract

Introduction: Mathematical and optimisation models are frequently used to improve hospital planning and capacity management. However, the resulting model-derived solutions are rarely evaluated for their adoption within the real-world context of a hospital. Objectives: In this study, we share our experience of an interdisciplinary collaboration between operations research/management science and implementation science, as one way of bridging the gap between technically sound solutions and their practical, sustainable use in healthcare. Methodology: We applied implementation science prospectively to anticipate adoption implications at the design stage of a scheduling tool. Specifically, we used the Consolidated Framework for Implementation Research (CFIR) to identify anticipated barriers and facilitators for adopting a mathematically optimised surgery blueprint schedule within a children’s hospital. Results: Identified anticipated facilitators included strong staff motivation to improve schedules, as well as positive perceptions of an objectively designed mathematical scheduling tool. Barriers included resistance to change among some staff and the demand for more evidence of the schedule’s benefits prior to implementation. We identified a strong culture of retaining autonomy in scheduling decisions, as well as operational adjustments made to current scheduling tools. Practical implications: Applying CFIR prospectively demonstrated how implementation science frameworks could provide a structured way to anticipate adoption challenges and align technical solutions with organisational realities.