DÄ internationalArchive3/2022Helicopter-Assisted Interhospital Transport of Ventilated Patients With COVID-19 Infection

Research letter

Helicopter-Assisted Interhospital Transport of Ventilated Patients With COVID-19 Infection

Data From the First Three Waves of the Pandemic

Dtsch Arztebl Int 2022; 119: 38. DOI: 10.3238/arztebl.m2022.0073

Heinrich, S; Schlürmann, CN; Braun, J; Korhummel, R; Busch, HJ

LNSLNS

In dealing with the SARS-CoV-2 pandemic, the available intensive care capacities constitute the critical resource for ensuring the survival of the greatest possible number of patients (1). To prevent regional overload of intensive care units and to allocate patients requiring intensive care, the German Interdisciplinary Association for Intensive Care and Emergency Medicine (DIVI) initiated a registry of up-to-the-minute available intensive care capacities. On the basis of data from the DIVI registry, it was possible to plan bilaterally medically indicated interhospital transfers within regional care clusters (for example, to escalate treatment). In case that in a scenario of regional overload, supraregional transports are required to alleviate the burden on the most severely affected regions, the so-called Kleeblatt concept [clover leaf concept—an agreement between federal government and states to enable the nationwide transfer of COVID-19 patients requiring intensive care] was developed to organize transport (2). In both scenarios, helicopter assisted transport has a particular role in providing transport capacity. In this article, we analyze the interhospital transports undertaken by the air rescue service charity Stiftung Luftrettung (DRF) during the first three waves of the COVID-19 pandemic as regards medical criteria and deployment tactics.

Methods

All data about helicopter deployments of the air rescue stations run by the DRF are documented via the digital central documentation portal HEMSEinsatzDatenErfassung (helicopter emergency service deployment data collection). The data were processed internally by the DRF and were made available, reviewed, and the manuscript approved in its final form as Project DRF-WAK-ID 67. The analysis and publication of data from the central documentation portal received ethics approval from the ethics committee of the State Medical Chamber of Baden-Württemberg. The study was conducted in accordance with the STROBE guidelines for retrospective observational studies (3). On the basis of all interhospital transports of ventilated patients undertaken by the DRF since January 2020, those with a COVID-19 association (confirmation or well-founded suspicion) were filtered out. They were assigned to the pandemic waves by using the national course of incidence rates as published by the Robert Koch-Institute. We used the Dimensional Charting Javascript Library (dc.js) to bring together the data in a multidimensional model, so that interhospital transports can be displayed on the basis of georeferenced data (geo)graphically and evaluated on the basis of metadata (4).

Results

We studied a total of 896 COVID-19 associated transports of ventilated patients. The Table shows the distribution of patients to the wave periods of the nationwide pandemic, as well as patient specific and transport specific characteristics. 189 transports (21%) were started after 6.00 pm and before 8.00 am, with 167 at an urgency of <2 hours.

Characteristics of patients and deployments
Table
Characteristics of patients and deployments

Across the pandemic waves, medical complications were documented in nine cases (1%). In one case, a patient had to be resuscitated during the flights because of a sudden cardiovascular arrest. This patient died within three hours after admission to intensive care. In four cases, ventilation problems were documented that resulted in a drop in oxygen saturation during the transport. The remaining documented complications did not affect the patients in any way.

The interactive figure at www.drf-luftrettung.de/untersuchung-coronapandemie shows a geographical breakdown and can be filtered by pandemic waves, admitting hospitals, and air rescue stations involved. The filtering functionality of the interactive figure can be used to visualize regional and temporal foci of transport volumes during the pandemic (Figure). The interactive figure is updated continuously, so that the transports after August 2021 can also be shown.

Example of use of the interactive multidimensional transport graphic
Figure
Example of use of the interactive multidimensional transport graphic

Discussion

According to data from the health insurers, 461 ventilated patients were transferred by road or air transport during the first COVID-19 wave in Germany (5). The 166 patients in the first wave who were captured in this study therefore represented 36% of ventilated transported patients. As road-based transports and air transports by air rescue services other than the DRF were not included in this description, our data are representative of the total pandemic related transport scenario only to a limited degree. Further efforts are required to achieve the desirable unified/consistent documentation that would enable reflecting on the totality of all intensive care transports by road and air in Germany.

One limitation of our study lies in the fact that the available data do not allow for more detailed explanations of care provision, such as of the frequency distribution in terms of capacity or medically necessary transfers or the duration of ventilation before the transport.

Transports of children and adolescents, of patients with non-invasive ventilation, with extracorporeal membrane oxygenation (ECMO), and patient isolation systems are of lesser importance in view of the total number of transports. The use of patient isolation systems decreased during the course of the pandemic, especially as vaccines became available for the crews. These systems are currently in use especially for longer transport distances, so as to reduce the time that crew needs to don PPE.

One possible reason for the increase in urgent applications for transport in Germany during the pandemic is the fall in the number of available intensive care beds. During the first wave on 1 April 2020, the DIVI registry shows that 40% of intensive care beds were available in Germany, whereas 37% of the transports studied here were categorized as predictable. During the second and third waves, 27% of transports—19% plannable—were logged, with rates of available intensive care beds at 16% on 3 January 2021 and 13% on 26 April 2021. Of all transports under study, 21% were undertaken between 6.00 pm and 8.00 am and therefore required an intensive transport helicopter able to fly at night. The high proportion in the overall volume of transports and the great urgency of transports in the evenings or during the night underline the importance of interhospital transport helicopters than can fly around the clock.

Our study shows that air rescue in Germany played a substantial part in handling the pandemic across all three waves, in ensuring adequate intensive care for those patients who were worst affected.

Sebastian Heinrich, Christoph-Nils Schlürmann, Jörg Braun, Rudolf Korhummel, Hans-Jörg Busch, für den Wissenschaftlichen Arbeitskreis (WAK) der DRF Stiftung Luftrettung gAG

Department of Anesthesiology and Critical Care, Medical Center, University of Freiburg, Germany (Heinrich, Schlürmann), Medizinische Fakultät, Albert-Ludwigs-Universität Freiburg; sebastian.heinrich@uniklinik-freiburg.de

DRF Stiftung Luftrettung gemeinnützige AG, Luftrettung Station Freiburg Christoph 54, Germany (Heinrich, Schlürmann, Busch)

German Air Rescue gAG (DRF Stiftung Luftrettung gAG), Filderstadt, Germany
(Braun, Wissenschaftlicher Arbeitskreis der DRF Stiftung Luftrettung)

Zentrum für Digitalisierung und Informationstechnologie, University of Freiburg, University Medical Center, Freiburg (Korhummel), Medizinische Fakultät, Albert-Ludwigs-Universität Freiburg

Department of Emergency Medicine, University Hospital of Freiburg, Faculty of Medicine, University of Freiburg (Busch)

Conflict of interest statement
The authors declare that no conflict of interest exists.

Manuscript received on 30 October 2021, revised version accepted on 30 November 2021.

Translated from the original German by Birte Twisselmann, PhD.

Cite this as:

Heinrich S, Schlürmann CN, Braun J, Korhummel R, Busch HJ: Helicopter-assisted interhospital transport of ventilated patients with COVID-19 infection—data from the first three waves of the pandemic. Dtsch Arztebl Int 2022; 119: 38–9. DOI: 10.3238/arztebl.m2022.0073

1.
Bravata DM, Perkins AJ, Myers LJ, et al.: Association of intensive care unit patient load and demand with mortality rates in US department of veterans affairs hospitals during the COVID-19 pandemic. JAMA Netw Open 2021; 4: e2034266 CrossRef MEDLINE PubMed Central
2.
Graesner J-T, Hannappel L, Zill M, Alpers B, Weber-Carstens S: COVID-19-Intensivpatienten: innerdeutsche Verlegungen. Deutsches Ärzteblatt 2020; 117: A-2321 VOLLTEXT
3.
von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP, for the STROBE Initiative: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 2008; 61: 344–9 CrossRef MEDLINE
4.
dc.js – Dimensional Charting Javascript Library. https://dc-js.github.io/dc.js/ (last accesssed on 16 October 2021).
5.
Karagiannidis C, Mostert C, Hentschker C, et al.: Case characteristics, resource use, and outcomes of 10021 patients with COVID-19 admitted to 920 German hospitals: an observational study. Lancet Respir Med 2020; 8: 853–62 CrossRef
Example of use of the interactive multidimensional transport graphic
Figure
Example of use of the interactive multidimensional transport graphic
Characteristics of patients and deployments
Table
Characteristics of patients and deployments
1.Bravata DM, Perkins AJ, Myers LJ, et al.: Association of intensive care unit patient load and demand with mortality rates in US department of veterans affairs hospitals during the COVID-19 pandemic. JAMA Netw Open 2021; 4: e2034266 CrossRef MEDLINE PubMed Central
2.Graesner J-T, Hannappel L, Zill M, Alpers B, Weber-Carstens S: COVID-19-Intensivpatienten: innerdeutsche Verlegungen. Deutsches Ärzteblatt 2020; 117: A-2321 VOLLTEXT
3.von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP, for the STROBE Initiative: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 2008; 61: 344–9 CrossRef MEDLINE
4.dc.js – Dimensional Charting Javascript Library. https://dc-js.github.io/dc.js/ (last accesssed on 16 October 2021).
5.Karagiannidis C, Mostert C, Hentschker C, et al.: Case characteristics, resource use, and outcomes of 10021 patients with COVID-19 admitted to 920 German hospitals: an observational study. Lancet Respir Med 2020; 8: 853–62 CrossRef