Best Practices on Radiology Department Workflow: Tips from the Impact of the COVID-19 Lockdown on an Italian University Hospital
Abstract
:1. Introduction
2. Methods
2.1. University Hospital “Arcispedale Sant’Anna”
2.2. Data Source and Population
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- X-rays examinations, including bedside ones, performed respectively by the ERU and GRU;
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- Ultrasound investigations, including bedside ones, performed respectively by the ERU and GRU;
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- CT scans conducted respectively by the ERU and GRU;
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- MRI scans performed by the GRU.
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- trauma;
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- accidental or syncopal fall;
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- road accident;
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- wound (incised wound, laceration, abrasion, penetration wound, avulsion, traumatic amputation);
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- crush injury;
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- hematoma;
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- assault or scuffle;
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- distractive injuries and strain;
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- violent suicide attempt (hanging);
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- excessive physical exertion during work or sporting activity.
2.3. Statistical Analysis
3. Results
3.1. Variation in the Number of Examinations and Assisted Patients
3.2. Variation in Diagnostic Activity by Patient Type and Method
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- 31.2% fewer outpatients (−2264);
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- 30.7% fewer inpatients (−1512);
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- 38.7% fewer ED patients (−3106).
3.3. Change in Diagnostic Activity Related to Trauma
3.4. Poisson Regression Analysis
4. Discussion
4.1. Immediate Impact of the COVID-19 Lockdown on the Radiology Department Workflow
4.2. Lean Tools for Improving the Radiology Department Workflow
- The significant decrease in the volume of emergency examinations during the global outbreak of coronavirus suggests a temporary downsizing of emergency radiological staff by relocating them to other tasks and to counter the financial strain deriving from COVID-19 patients on other radiology services, particularly those dedicated to the hospitalized patients.
- The increased volume of chest imaging in emergency settings may suggest using radiologists with expertise in thoracic imaging due to their increased sensitivity in detecting subtle pneumonia findings. In addition, specific training programs should be established for generalist radiologists who could also benefit from the support of artificial intelligence to improve the interpretation and efficiency of images, especially during night shifts [42].
- The excessive use of chest CT examinations and the concomitant decrease in conventional chest X-rays found in our data in the first wave of an unknown severe acute respiratory infection is not justified by guidelines regulating the use of imaging in COVID-19 in the subsequent pandemic phases. All major thoracic radiology societies advise against the indiscriminate use of imaging as a screening test for COVID-19 in patients with mild or no symptoms, while recommending its use based on symptom severity, pre-test probability, and COVID-19 testing [29,43,44].
- It is essential to separate the diagnostic pathways between suspected and non-suspected COVID-19 patients to prevent viral transmission between patients and healthcare workers [45]. One CT device should be closest to the COVID-19 emergency room only for infected patients and not too far away from the inpatient unit where patients with suspected or confirmed COVID-19 pneumonia are hospitalized.
- Mobile X-ray units and bedside ultrasounds should be encouraged to avoid the transportation of patients from the ward to the CT unit and to reduce the risk of contamination of staff and other patients. Although chest X-rays had low detection rates in the early stages of COVID-19 infection [27], these methods may be helpful in patient follow-up during treatment and also for detecting complications, such as pleural effusions or pneumothorax in mechanically ventilated subjects [46].
- For overcrowded RDs based on the local prevalence of COVID-19, non-urgent imaging exam appointments should be decreased or scheduled with a longer time gap, and accompanying visitors should be limited to avoid crowding the waiting zones.
- Since radiology is one of the medical specialties with a greater degree of digitalization, teleradiology and teleworking solutions should be strengthened in a similar dramatic scenario. The structured model of outsourced teleradiology has, in fact, been demonstrated to meet the requirements of emergency medicine during the pandemic with high diagnostic accuracy of chest CTs in the diagnosis of COVID-19 and a remarkable inter-observer agreement between teleradiologists with various degrees of experience and in contexts with different levels of disease prevalence [47]. By holding a small group of radiologists on-site and the rest of the group working safely from home to minimize the risk of cross-infection, teleradiology allows for the preservation of workload in the RD, increasing the productivity in other areas, such as administrative, operations, education, and research units, or updating strategies for optimizing workflow and safety protocols [48].
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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11 March 2019–26 May 2019 | 11 March 2020–26 May 2020 | Comparison | ||||
---|---|---|---|---|---|---|
Unit | Number of Patients | Proportion | Number of Patients | Proportion | Difference | Percentage |
GRU | 10,866 | 55% | 8070 | 60.6% | −2796 | −25.7% |
ERU | 8905 | 45% | 5252 | 39.4% | −3653 | −41% |
Total | 19,771 | - | 13,322 | - | −6449 | −32.6% |
Unit | Number of Examinations | Proportion | Number of Examinations | Proportion | Difference | Percentage |
GRU | 31,203 | 61.7% | 23,260 | 66.8% | −7943 | −25.5% |
ERU | 19,396 | 38.3% | 11,552 | 33.2% | 41 | −40.4% |
Total | 50,599 | - | 34,812 | - | −15,787 | −31.2% |
11 March 2019–26 May 2019 | 11 March 2020–26 May 2020 | Comparison | ||
---|---|---|---|---|
Week Number | Number of Examinations | Number of Examinations | Difference | Percentage |
Week 1 (11/03–17/03) | 4841 | 3601 | −1240 | −25.6% |
Week 2 (18/03–24/03) | 5221 | 3171 | −2050 | −39.3% |
Week 3 (25/03–31/03) | 5109 | 2783 | −2326 | −45.5% |
Week 4 (01/04–07/04) | 4972 | 3070 | −1902 | −38.3% |
Week 5 (08/04–14/04) | 4750 | 2569 | −2181 | −45.9% |
Week 6 (15/04–21/04) | 4145 | 2957 | −1188 | −28.7% |
Week 7 (22/04–28/04) | 2364 | 2364 | 0 | - |
Week 8 (29/04–05/05) | 4155 | 2687 | −1468 | −35.3% |
Week 9 (06/05–12/05) | 4840 | 3940 | −900 | −18.6% |
Week 10 (13/05–19/05) | 5181 | 4137 | −1044 | −20.2% |
Week 11 (20/05–26/05) | 5021 | 3533 | −1488 | −29.6% |
Total | 50,599 | 34,812 | −15,787 | −31.2% |
11 March 2019–26 May 2019 | 11 March 2020–26 May 2020 | Comparison | ||
---|---|---|---|---|
Week Number | Number of Patients | Number of Patients | Difference | Percentage |
Week 1 (11/03–17/03) | 2250 | 1721 | −529 | −23.5% |
Week 2 (18/03–24/03) | 2278 | 1492 | −786 | −34.5% |
Week 3 (25/03–31/03) | 2302 | 1366 | −936 | −40.7% |
Week 4 (01/04–07/04) | 2267 | 1321 | −946 | −41.7% |
Week 5 (08/04–14/04) | 2214 | 1221 | −993 | −44.9% |
Week 6 (15/04–21/04) | 2085 | 1230 | −855 | −41% |
Week 7 (22/04–28/04) | 1187 | 908 | −279 | −23.5% |
Week 8 (29/04–05/05) | 1765 | 1213 | −552 | −31.3% |
Week 9 (06/05–12/05) | 2140 | 1626 | −514 | −24% |
Week 10 (13/05–19/05) | 2187 | 1683 | −504 | −23% |
Week 11 (20/05–26/05) | 2187 | 1567 | −620 | −28.3% |
Total | 22,862 | 15,348 | −7514 | −32.9% |
11 March 2019–26 May 2019 | 11 March 2020–26 May 2020 | Comparison | |||||
---|---|---|---|---|---|---|---|
Examinations by Patient Type | Number of Patients | Proportion | Number of Patients | Proportion | Difference | Percentage | p Value |
Outpatient | 7249 | 35.9% | 4985 | 37.4% | −2264 | −31.2% | 0.004 |
Inpatient | 4918 | 24.3% | 3406 | 25.6% | −1512 | −30.7% | 0.012 |
ED patient | 8035 | 39.8% | 4929 | 37% | −3106 | −38.7% | <0.001 |
Total | 20,202 | - | 13,320 | - | −6882 | −34.1% | - |
Examinations by Patient Type | Number of Examinations | Proportion | Number of Examinations | Proportion | Difference | Percentage | p Value |
Outpatient | 15,179 | 30% | 10,253 | 29.5% | −4926 | −32.5% | >0.05 |
Inpatient | 19,793 | 39.1% | 14,393 | 41.3% | −5400 | −27.3% | <0.001 |
ED patient | 15,627 | 30.9% | 10,166 | 29.2% | −5461 | −34.9% | <0.001 |
Total | 50,599 | - | 34,812 | - | −15,787 | −31.2% | - |
11 March 2019–26 May 2019 | 11 March 2020–26 May 2020 | Comparison | ||||
---|---|---|---|---|---|---|
Examinations by Clinical Question | Number of Examinations | Proportion | Number of Examinations | Proportion | Difference | Percentage |
Not trauma | 43,008 | 85.2% | 30,372 | 87.5% | −12,636 | −29.4% |
Trauma | 7470 | 14.8% | 4348 | 12.5% | −3122 | −41.8% |
Not determined | 121 | - | 92 | - | - | - |
Total | 50,478 | - | 34,720 | - | −15,758 | −31.2% |
11 March 2019–26 May 2019 | 11 March 2020–26 May 2020 | Comparison | ||||
---|---|---|---|---|---|---|
Patients by Clinical Condition | Number of Patients | Proportion | Number of Patients | Proportion | Difference | Percentage |
Not trauma | 15,316 | 83.4% | 10,486 | 87.5% | −4830 | −31.5% |
Trauma | 3038 | 16.6% | 1495 | 12.5% | −1543 | −50.8% |
Not determined | 52 | - | 49 | - | - | |
Total | 18,354 | - | 11,981 | - | −6373 | −34.7% |
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Pellegrino, F.; Carnevale, A.; Bisi, R.; Cavedagna, D.; Reverberi, R.; Uccelli, L.; Leprotti, S.; Giganti, M. Best Practices on Radiology Department Workflow: Tips from the Impact of the COVID-19 Lockdown on an Italian University Hospital. Healthcare 2022, 10, 1771. https://doi.org/10.3390/healthcare10091771
Pellegrino F, Carnevale A, Bisi R, Cavedagna D, Reverberi R, Uccelli L, Leprotti S, Giganti M. Best Practices on Radiology Department Workflow: Tips from the Impact of the COVID-19 Lockdown on an Italian University Hospital. Healthcare. 2022; 10(9):1771. https://doi.org/10.3390/healthcare10091771
Chicago/Turabian StylePellegrino, Fabio, Aldo Carnevale, Riccardo Bisi, Davide Cavedagna, Roberto Reverberi, Licia Uccelli, Stefano Leprotti, and Melchiore Giganti. 2022. "Best Practices on Radiology Department Workflow: Tips from the Impact of the COVID-19 Lockdown on an Italian University Hospital" Healthcare 10, no. 9: 1771. https://doi.org/10.3390/healthcare10091771