Retrospective Analysis of a Modified Organizational Model to Guarantee CT Workflow during the COVID-19 Outbreak in the Tertiary Hospital of Padova, Italy
Abstract
:1. Introduction
2. Experimental Section
2.1. Diagnostic Department of Imaging
2.1.1. Usual Radiological Assets
2.1.2. Structural Implementation
2.1.3. Organizational Implementation
- Patients admitted to the ER and in-patients: examination was performed in any scanner according to the usual diagnostic pathway.
- Outpatients with scheduled CT examination: examination was performed in any scanner in the hospital according to the usual diagnostic pathway (i.e., CT examinations for neurological diseases are typically performed in the neuroradiology unit).
- Patients admitted to the ER and in-patients: examination was performed using the mobile trailer-mounted CT scanner. Scanner and pathway sanitizations were scheduled twice a day.
- In-patients and patients admitted to the ER in need of an emergency CT scan, who had already performed an RT-PCR test but were still waiting for results or who had received an initial negative test, but who had highly suggestive anamnesis and/or symptoms of COVID-19: the CT scan was performed in the main building, in an area with a separate control room and access path. After patient examination, the CT room was sanitized and halted according to the guidelines.
2.1.4. Safety of the Staff
2.2. Workload Analysis
2.2.1. Performance of the Applied Model
2.2.2. Overall Hospital Workload
2.2.3. Safety Assessment
2.3. Statistical Analysis
3. Results
4. Discussion
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Abbreviations
COVID-19 | Coronavirus Disease 19 |
RT-PCR | reverse transcription polymerase chain reaction SARS |
SARS-CoV-2 | severe acute respiratory syndrome coronavirus 2 |
References
- Lescure, F.-X.; Bouadma, L.; Nguyen, D.; Parisey, M.; Wicky, P.-H.; Behillil, S.; Gaymard, A.; Bouscambert-Duchamp, M.; Donati, F.; Le Hingrat, Q.; et al. Clinical and virological data of the first cases of COVID-19 in Europe: A case series. Lancet Infect. Dis. 2020, 20, 697–706. [Google Scholar] [CrossRef] [Green Version]
- Tuite, A.R.; Ng, V.; Rees, E.; Fisman, D. Estimation of COVID-19 outbreak size in Italy. Lancet Infect. Dis. 2020, 20, 537. [Google Scholar] [CrossRef] [Green Version]
- Lavezzo, E.; Franchin, E.; Ciavarella, C.; Cuomo-Dannenburg, G.; Barzon, L.; Del Vecchio, C.; Rossi, L.; Manganelli, R.; Loregian, A.; Navarin, N.; et al. Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo’. Nature 2020, 584, 425–429. [Google Scholar] [CrossRef] [PubMed]
- Saglietto, A.; D’Ascenzo, F.; Zoccai, G.B.; De Ferrari, G.M. COVID-19 in Europe: The Italian lesson. Lancet 2020, 395, 1110–1111. [Google Scholar] [CrossRef]
- Grasselli, G.; Pesenti, A.; Cecconi, M. Critical Care Utilization for the COVID-19 Outbreak in Lombardy, Italy: Early Experience and Forecast During an Emergency Response. JAMA 2020, 323, 1545–1546. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Poston, J.T.; Patel, B.K.; Davis, A.M. Management of Critically Ill Adults With COVID-19. JAMA 2020, 323, 1839–1841. [Google Scholar] [CrossRef]
- Phua, J.; Weng, L.; Ling, L.; Egi, M.; Lim, C.-M.; Divatia, J.V.; Shrestha, B.R.; Arabi, Y.M.; Ng, J.; Gomersall, C.D.; et al. Intensive care management of coronavirus disease 2019 (COVID-19): Challenges and recommendations. Lancet Respir. Med. 2020, 8, 506–517. [Google Scholar] [CrossRef]
- Pan, Y.; Guan, H. Imaging changes in patients with 2019-nCov. Eur. Radiol. 2020, 30, 3612–3613. [Google Scholar] [CrossRef] [Green Version]
- Kim, H. Outbreak of novel coronavirus (COVID-19): What is the role of radiologists? Eur. Radiol. 2020, 30, 3266–3267. [Google Scholar] [CrossRef] [Green Version]
- Fichera, G.; Stramare, R.; De Conti, G.; Motta, R.; Giraudo, C. It’s not over until it’s over: The chameleonic behavior of COVID-19 over a six-day period. Radiol. Med. 2020, 125, 514–516, in press. [Google Scholar] [CrossRef]
- Tosato, F.; Giraudo, C.; Pelloso, M.; Musso, G.; Piva, E.; Plebani, M. One disease, different features: COVID-19 laboratory and radiological findings in three Italian patients. Clin. Chem. Lab. Med. CCLM 2020, 58, 1149–1151. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Baracchini, C.; Pieroni, A.; Viaro, F.; Cianci, V.; Cattelan, A.M.; Tiberio, I.; Munari, M.; Causin, F. Acute stroke management pathway during Coronavirus-19 pandemic. Neurol. Sci. 2020, 41, 1003–1005. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Shi, H.; Han, X.; Jiang, N.; Jiang, N.; Cao, Y.; Alwalid, O.; Gu, J.; Fan, Y.; Zheng, C. Radiological findings from 81 patients with COVID- 19 pneumonia in Wuhan, China: A descriptive study. Lancet Infect. Dis. 2020, 20, 425–434. [Google Scholar] [CrossRef]
- Mossa-Basha, M.; Medverd, J.; Linnau, K.; Lynch, J.B.; Wener, M.H.; Kicska, G.; Staiger, T.; Sahani, D. Policies and Guidelines for COVID-19 Preparedness: Experiences from the University of Washington. Radiology 2020. [Google Scholar] [CrossRef]
- Clinical Care for Severe Acute Respiratory Infection: Toolkit. World Health Organization. WHO/2019-nCoV/SARI_toolkit/2020.1. Available online: https://apps.who.int/iris/bitstream/handle/10665/331736/WHO-2019-nCoV-SARI_toolkit-2020.1-eng.pdf (accessed on 20 April 2020).
- ACR Recommendations for the Use of Chest Radiography and Computed Tomography (CT) for Suspected COVID-19 Infection. Available online: https://www.acr.org/Advocacy-and-Economics/ACR-Position-Statements/Recommendations-for-Chest-Radiography-and-CT-for-Suspected-COVID19-Infection (accessed on 15 April 2020).
- COVID-19 Situazione in Italia. Available online: http://www.salute.gov.it/portale/nuovocoronavirus/dettaglioContenutiNuovoCoronavirus.jsp?area=nuovoCoronavirus&id=5351&lingua=italiano&menu=vuoto (accessed on 20 April 2020).
- Operational Considerations for Case Management of COVID-19 in Health Facility and Community. Available online: https://apps.who.int/iris/bitstream/handle/10665/331492/WHO-2019-nCoVHCF_operations-2020.1-eng.pdf (accessed on 18 April 2020).
- COVID-19 Operatori Sanitari. Available online: http://www.salute.gov.it/portale/nuovocoronavirus/dettaglioContenutiNuovoCoronavirus.jsp?lingua=italiano&id=5373&area=nuovoCoronavirus&menu=vuoto (accessed on 18 April 2020).
- He, Y.; Lin, Z.; Tang, D.; Yang, Y.; Wang, T.; Yang, M. Lancet Strategic plan for management of COVID-19 in paediatric haematology and oncology departments. Lancet Haematol. 2020, 7, E359–E362. [Google Scholar] [CrossRef]
- Chan, S.S.; Mak, P.S.; Shing, K.K.; Chan, P.N.; Ng, W.H.; Rainer, T.H. Chest radiograph screening for severe acute respiratory syndrome in the ED. Am. J. Emerg. Med. 2005, 23, 525–530. [Google Scholar] [CrossRef] [Green Version]
- Parmar, H.A.; Lim, T.C.; Goh, J.S.; Tan, J.T.; Sitoh, Y.Y.; Hui, F. Providing optimal radiology service in the severe acute respiratory syndrome outbreak: Use of mobile CT. AJR Am. J. Roentgenol. 2004, 182, 57–60. [Google Scholar] [CrossRef] [Green Version]
- Xie, Y.; Wang, X.; Yang, P.; Zhang, S. COVID-19 Complicated by Acute Pulmonary Embolism. Radiol. Cardiothorac. Imaging 2020, 2, e200067. [Google Scholar] [CrossRef] [Green Version]
- Casey, K.; Iteen, A.; Nicolini, R.; Auten, J. COVID-19 pneumonia with hemoptysis: Acute segmental pulmonary emboli associated with novel coronavirus infection. Am. J. Emerg. Med. 2020, 38, 1544.e1–1544.e3. [Google Scholar] [CrossRef]
- Rotzinger, D.C.; Beigelman-Aubry, C.; von Garnier, C.; Qanadli, S.D. Pulmonary embolism in patients with COVID-19: Time to change the paradigm of computed tomography. Thromb. Res. 2020, 190, 58–59. [Google Scholar] [CrossRef]
- The Lancet. COVID-19: Protecting health-care workers. Lancet 2020, 395, 922. [Google Scholar] [CrossRef]
- Ai, T.; Yang, Z.; Hou, H.; Zhan, C.; Chen, C.; Lv, W.; Tao, Q.; Sun, Z.; Xia, L. Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases. Radiology 2020, 296, E32–E40. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Liu, W.H.; Wang, X.W.; Cai, Z.Q.; Wang, X.; Huang, X.L.; Jin, Z.G. Chest CT as a screening tool for COVID-19 in unrelated patients and asymptomatic subjects without contact history is unjustified. Quant. Imaging Med. Surg. 2020, 10, 876–877. [Google Scholar] [CrossRef] [PubMed]
CT Request Pattern | ||||
---|---|---|---|---|
PATHWAY B COVID-19-Positive Patients * | PATHWAY C High-Risk Patients * | |||
Thorax | ||||
HRCT evaluation | 41 | HRCT for screening | 23 | |
Pulmonary embolism | 8 | HRCT for diagnosis (negative RT-PCT test) | 11 | |
Pulmonary embolism | 16 | |||
Head | ||||
Stroke and impaired state of consciousness | 9 | Stroke and impaired state of consciousness | 14 | |
Headache | 3 | Headache | 8 | |
Disequilibrium, vertigo | 3 | Disorientation | 4 | |
Epilepsy | 3 | Epilepsy | 4 | |
Other | 1 | |||
Abdomen | ||||
Acute abdomen | 1 | Acute abdomen | 3 | |
Pancreatitis | 1 | Abdominal occlusion | 1 | |
Other | 1 | Other | 2 | |
Vascular | ||||
Aortic dissection | 2 | Aortic dissection | 3 | |
Hemorrhage | 5 | |||
Neoplasm | ||||
Follow-up | 2 | Complications | 1 | |
Other Infections | ||||
Exclusion of concomitant infection | 1 | Exclusion of concomitant infection | 3 | |
Trauma | ||||
Head and cervical spine | 7 | Head and cervical spine | 13 | |
Other | 2 | Polytrauma | 1 | |
Other |
Origin of Patients | Number of CT Acquisitions | |||||||
---|---|---|---|---|---|---|---|---|
Pathway A | Pathway B | Pathway C | Total | |||||
Low-Risk | Positive | High-Risk | ||||||
(n) | (%) | (n) | (%) | (n) | (%) | (n) | (%) | |
ER | 970 | 29% | 16 | 18% | 93 | 84% | 1079 | 29% |
In-patients | 1626 | 49% | 73 | 82% | 18 | 16% | 1717 | 49% |
Out-patients | 741 | 22% | 0 | 0% | 0 | 0% | 741 | 22% |
3337 | 100% | 89 * | 100% | 111 | 100% | 3537 | 100% |
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Share and Cite
Cester, G.; Giraudo, C.; Causin, F.; Boemo, D.G.; Anglani, M.; Capizzi, A.; Carretta, G.; Cattelan, A.; Cecchin, D.; Cianci, V.; et al. Retrospective Analysis of a Modified Organizational Model to Guarantee CT Workflow during the COVID-19 Outbreak in the Tertiary Hospital of Padova, Italy. J. Clin. Med. 2020, 9, 3042. https://doi.org/10.3390/jcm9093042
Cester G, Giraudo C, Causin F, Boemo DG, Anglani M, Capizzi A, Carretta G, Cattelan A, Cecchin D, Cianci V, et al. Retrospective Analysis of a Modified Organizational Model to Guarantee CT Workflow during the COVID-19 Outbreak in the Tertiary Hospital of Padova, Italy. Journal of Clinical Medicine. 2020; 9(9):3042. https://doi.org/10.3390/jcm9093042
Chicago/Turabian StyleCester, Giacomo, Chiara Giraudo, Francesco Causin, Deris Gianni Boemo, Mariagiulia Anglani, Alfio Capizzi, Giovanni Carretta, Annamaria Cattelan, Diego Cecchin, Vito Cianci, and et al. 2020. "Retrospective Analysis of a Modified Organizational Model to Guarantee CT Workflow during the COVID-19 Outbreak in the Tertiary Hospital of Padova, Italy" Journal of Clinical Medicine 9, no. 9: 3042. https://doi.org/10.3390/jcm9093042