Model‐informed health system reorganization during emergencies

• DOI: 10.1111/poms.13710
• Publication Date: 2022-03-16T14:01:42Z
• Authors: Paulo Gonçalves; Paolo Ferrari; Luca Crivelli; Emiliano Albanese
• Keywords: Healthcare system

The COVID‐19 pandemic presented the world to a novel class of problems highlighting distinctive features that rendered standard academic research and participatory processes less effective in properly informing public health interventions timely way. urgency rapidity emergency required tight integration high‐quality simulation modeling with policy implementation. By introducing flexibility agility into processes, we aligned effort imposed reality rapidly develop regional system dynamics (SD) model integrating diverse streams data could reliably inform both restructuring policy. Using Lombardy data, our SD was able generate early projections for diffusion neighbor Ticino. Later, it projected timing size peak patient demand. Our work also supported need reorganization healthcare volume strategies increasing hospital capacity (e.g., intensive care unit [ICU] ward beds, medical nursing staff, oxygen supply) Counterfactual analyses quantify impact decisions by interventions. contributes understanding used organizations during emergencies, critical role played available response time deployment either prioritize services or leverage resources. It literature on systems describing flexible agile process successfully deployed evolving high‐stakes emergency.