## 4 Discussion  
The present study describes the organizational aspects of EH19 as a way to better manage the COVID-19 pandemic. According to our experience, EH19 was very effective in facing the first and second waves as evidenced by a decrease in mortality and LOS, ultimately improving the overall quality of care. Based on data about global COVID-19 cases by John Hopkins CSSE updated at the end of the first wave, Italy was the third most-affected country of the world, only preceded by the US and Spain, accounting for 159,516 confirmed cases and 20,465 deaths [(20)]. Overall, the Lombardy region was the epicenter of the Italian pandemic, with 37.4% of total cases registered in the national territory and more than 50% of the total number of deaths ([[http://www.salute.gov.it](http://www.salute.gov.it)]([http://www.salute.gov.it](http://www.salute.gov.it)) accessed on 1 March 2021) [(21; 22; 23)]. The large number of cases in northern Italy overwhelmed the health care system and created a demand for an imminent change on the containment of the infection. After the implementation of EH19 and the Lean operational algorithm, the adjusted mortality rate was reduced, despite a seven-year increase in median patients' age and higher comorbidity rate in the second wave. Meanwhile, on the contrary, the need for HFO2 support increased. Moreover, the average in-hospital LOS was not prolonged in the second wave, resulting in a substantial advantage in terms of cost-effectiveness. These data may be explained by the overall improvement in the quality of care. \begin{table}
\begin{tabular}{c c c} \hline \hline  & **First Wave a** & **Second Wave a** \\ \hline Age (years) & 68.2 & 68.2 \\ \hline Male (\%) & 65.1 & 65.1 \\ \hline Hypertension (\%) & 49.5 & 49.5 \\ \hline Cardiovascular diseases (\%) & 25.8 & 25.8 \\ \hline Diabetes (\%) & 20.1 & 20.1 \\ \hline Malignancy (\%) & 18.8 & 18.8 \\ \hline Neurological diseases (\%) & 16.6 & 16.6 \\ \hline Respiratory diseases (\%) & 13.9 & 13.9 \\ \hline Chronic kidney diseases (\%) & 8.5 & 8.5 \\ \hline In-hospital death & 24.9 & 21.4 \\ \hline RR (95\% CI) & 0.86 (0.73–1.02) & \\ \hline OR (95\% CI) & 0.82 (0.66–1.03) & \\ \hline \hline \end{tabular}  
* Reported is either the overlap propensity score–weighted mean or proportion for each group.OR: Odds Ratio; RR: Relative Risk.  
\end{table} 
Table 2: Overlap propensity score–weighted characteristics and in-hospital death among patients hospitalized for COVID-19 during the first or the second epidemic wave. As reported by several authors, the implementation of an additional hospital facility has a primary role in centralizing the professional figures specifically trained in the cure of COVID-19 patients [24; 25; 26]. COVID-19-dedicated hospitals have been proven to be effective in flattening the infection curve and slowing the spread of the virus worldwide--these being the major strengths of these facilities [24; 25; 26; 27]. It should be mentioned that the ICU admission rate decreased in group 2 (16.9% vs. 8.75%, \(p<0.001\)). This could also be explained by considering that, in our newly born facility, besides the ordinary ward beds and the ICU beds, we had eight high-dependency unit beds at our disposal that could be easily converted to ICU or ordinary ward beds according to our needs with maximal flexibility. The main sequelae of the COVID-19 spread included the alarming collapse of the clinic caseload and the consequent delays of elective medical and surgical activity. [PERSON] and colleagues recently stressed these concerns regarding the significant reduction in optimal cardiovascular health care delivery in Canada, basically consisting of a substantial deferral of elective cardiovascular procedures [28]. The same alarm has been reported for cardiac surgery [29], and as many apprehensions do exist for specialties other than the cardiovascular field, these reports highlight a negative trend in health care delivery, even in critical care [30; 31; 32; 33; 34].