Model Informed Health System Reorganization During Emergencies (preprint)

ABSTRACT

The COVID-19 pandemic presented the world to a novel class of problems highlighting distinctive features that render standard academic research and participatory processes less effective in properly informing public health interventions in a timely way. The urgency and rapidity of the emergency, requiring tight integration of novel and high-quality simulation modeling with policy implementation, render traditional participatory approaches inadequate to properly and promptly inform public health policy decisions. By introducing flexibility and agility into standard participatory processes, we aligned the modeling effort with the imposed reality of the emergency to rapidly develop a regional system dynamics model integrating diverse streams of data that could reliably inform both health system restructuring and public health policy. Counterfactual analyses quantify the impact of the decisions supported by our interventions. Moreover, our analyses supported volume flexibility strategies that increased hospital (e.g., ICU and ward beds, medical and nursing staff, and oxygen supply) capacity. Our research also contributes to our understanding of volume flexibility strategies used by healthcare organizations during emergencies. It highlights the critical aspect that time available to respond plays in the deployment of strategies that either prioritize critical services or leverage already available internal resources.