The SWALIS 2020 new model to prioritize access to urgent, elective and backlog waiting lists. facing the challenge in the COVID era

Purpose: The COVID-19 pandemic burdens non-covid elective surgical patients by reducing service capacity, forcing extreme selection of patients most in need. New tools are urgently required to prioritize operations and optimize the process sustainably. Our study assesses the SWALIS-2020 model ability to prioritize access to surgery during the highest viral outbreak peaks. Methods: A 2020 March - May feasibility-pilot study, tested a software-aided, inter-hospital, multidisciplinary pathway. All specialties patients in the Genoa Departments referred for urgent elective surgery were included in a multidisciplinary pathway adopting a modified Surgical Waiting List InfoSystem (SWALIS) cumulative prioritization method (PAT-2020) based on waiting time and clinical urgency, in three subcategories: A1-15 days (certain rapid disease progression), A2-21 days (probable progression), and A3-30 days (potential progression). We have studied the model applicability and its ability to prioritize patients by monitoring their waiting list and service performance. https://www.isrctn.com/ISRCTN11384058. Results: Following the feasibility study (N=55 patients), 240 referrals were evaluated in 4 weeks without major criticalities (M/F=73/167, Age=68.7 +/- 14.0). Waiting lists were prioritized and monitored. The SWALIS-2020 score (% of waited-against-maximum time) at operation was 88.7 +/- 45.2 at week 1 and then persistently over 100% (efficiency), over a controlled variation (equity), with a difference between A3 (153.29 +/- 103.52) vs. A1 (97.24 +/- 107.93) (p <0.001), and A3 vs. A2 (88.05 +/- 77.51) (p <0.001). 222 patients underwent surgery, without related complications or delayed/failed discharges. Conclusion: The pathway has selected the very few patients with the greatest need, even with +30% capacity weekly modifications, managing active and backlog waiting lists. We are setting up collaborations for multi-center research.