| Popis: |
Iride Francesca Ceresa,1 Gabriele Savioli,1,2 Valentina Angeli,3 Viola Novelli,4 Alba Muzzi,4 Giuseppina Grugnetti,5 Lorenzo Cobianchi,6 Federica Manzoni,7 Catherine Klersy,7 Paolo Lago,8 Pierantonio Marchese,9 Carlo Marena,4 Giovanni Ricevuti,10 Maria Antonietta Bressan11 1Emergency Department, San Matteo IRCCS Hospital Foundation, Pavia 27100, Italy; 2Department of Clinical-Surgical, Diagnostic and Pediatric Sciences, PhD School in Experimental Medicine, University of Pavia, Pavia 27100, Italy; 3Emergency Department, Sant’Andrea Hospital, Vercelli, 13100, Italy; 4Direzione Medica di Presidio, San Matteo IRCCS Hospital Foundation, Pavia 27100, Italy; 5SITRA, San Matteo IRCCS Hospital Foundation, Pavia 27100, Italy; 6Surgery, University of Pavia, Pavia 27100, Italy; 7Clinical Epidemiology and Biometric Unit, Scientific Direction, San Matteo IRCCS Hospital Foundation, Pavia, Italy; 8Ingegneria Clinica, IRCCS Policlinico San Matteo, Pavia 27100, Italy; 9Servizio Prevenzione e Protezione, IRCCS Policlinico San Matteo, Pavia 27100, Italy; 10Department of Drug Science, University of Pavia, Saint Camillus International University of Health Sciences, Rome, Italy; 11Emergency Department, IRCCS Policlinico San Matteo, Pavia 27100, ItalyCorrespondence: Gabriele SavioliEmergency Department, Irccs Policlinico San Matteo, Piazza Botta, 2, Pavia 27100, ItalyTel +39 340 9070001Email gabrielesavioli@gmail.comIntroduction: The sudden increase in the number of critically ill patients following a disaster can be overwhelming.Study Objective: The main objective of this study was to assess the real number of available and readily freeable beds (“bed surge capacity”) and the availability of emergency operating rooms (OR) in a maximum emergency using a theoretical simulation.Patients and Methods: The proportion of dismissible patients in four areas (Medical Area, Surgical Area, Sub-intensive Care Units, Intensive Care Units) and three emergency OR was assessed at 2 and 24 hours after a simulated maximum emergency. Four scenarios were modeled. Hospitalization and surgical capacities were assessed on weekdays and holidays. The creation of new beds was presumed by the possibility of moving patients to a lower level of care than that provided at the time of detection, of dislocation of patients to a discharge room, with care transferred to lower-intensity hospitals, rehabilitation, or discharge facilities. The Phase 1 table-top simulations were conducted during the weekday morning hours. In particular, the 24-hour table-top simulations of a hypothetical event lasted about 150 minutes compared to those conducted at 2 hours, which were found to be longer (about 195 minutes). Phase 2 was conducted on two public holidays and a quick response time was observed within the first 40 minutes of the start of the test (about 45% of departments).Results: The availability of simulated beds was greater than that indicated in the maximum emergency plans (which was based solely on the census of beds). Patients admitted to Intensive Care and The Sub-Intensive Area may be more difficult to move than those in low-intensity care. The availability of emergency OR was not problematic. Age influenced the possibility of remitting/transferring patients.Conclusion: Simulation in advance of a maximum emergency is helpful in designing an efficient response plan.Keywords: simulation, maximum emergency, table-top simulation, bed surge capacity, disaster medicine, maxiemergency |
