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Figure.  EMS Interhospital Ground and Air Transportation Events in Patients With Acute LRTI in the US, January 1, 2019, to February 28, 2021
EMS Interhospital Ground and Air Transportation Events in Patients With Acute LRTI in the US, January 1, 2019, to February 28, 2021

Panels A and C depict trends in the 30-day rolling average of daily interhospital transports for prepandemic (January 2019-February 2020) and pandemic (beginning March 2020 based on the World Health Organization declaration of pandemic; blue area) periods for those patients with documented primary or secondary impressions of emergency medical services (EMS) personnel suggestive of acute lower respiratory tract illness (LRTI) transported by ground and air. Panels B and D depict the percentage change in pandemic vs prepandemic transport counts of patients with acute LRTI in each pandemic wave transported by ground and air. A value below the baseline represents a decline in transports during the pandemic as compared with the same time period during the prior year; values above the baseline represent an increase in transports during the pandemic as compared with the same time period during the prior year. The dashed lines in panels A and C separate the pandemic period into wave 1 (March-May 2020), wave 2 (June-August 2020), and wave 3 (September 2020-February 2021). Trends are limited to data from 1252 EMS agencies from all US Census regions that reported data in each month over the study period.

Table.  Characteristics of Interhospital Transports of Patients With Acute LRTI Before and During the COVID-19 Pandemica
Characteristics of Interhospital Transports of Patients With Acute LRTI Before and During the COVID-19 Pandemica
1.
Kadri  SS, Sun  J, Lawandi  A,  et al.  Association between caseload surge and COVID-19 survival in 558 US hospitals, March to August 2020.   Ann Intern Med. 2021;174(9):1240-1251.PubMedGoogle ScholarCrossref
2.
Payet  C, Polazzi  S, Rimmelé  T, Duclos  A.  Mortality among noncoronavirus disease 2019 critically ill patients attributable to the pandemic in France.   Crit Care Med. 2022;50(1):138-143.PubMedGoogle ScholarCrossref
3.
Troncoso  RD  Jr, Garfinkel  EM, Leon  D,  et al.  Decision making and interventions during interfacility transport of high-acuity patients with severe acute respiratory syndrome coronavirus 2 infection.   Air Med J. 2021;40(4):220-224.PubMedGoogle ScholarCrossref
4.
Allen  R, Wanersdorfer  K, Zebley  J, Shapiro  G, Coullahan  T, Sarani  B.  Interhospital transfer of critically ill patients because of coronavirus disease 19–related respiratory failure.   Air Med J. 2020;39(6):498-501.PubMedGoogle ScholarCrossref
5.
Painvin  B, Messet  H, Rodriguez  M,  et al.  Inter-hospital transport of critically ill patients to manage the intensive care unit surge during the COVID-19 pandemic in France.   Ann Intensive Care. 2021;11(1):54.PubMedGoogle ScholarCrossref
6.
Kadri  SS, Gundrum  J, Warner  S,  et al.  Uptake and accuracy of the diagnosis code for COVID-19 among US hospitalizations.   JAMA. 2020;324(24):2553-2554.PubMedGoogle ScholarCrossref
Research Letter
January 28, 2022

Frequency and Risk of Emergency Medical Service Interhospital Transportation of Patients With Acute Lower Respiratory Tract Illness During the COVID-19 Pandemic in the US

Author Affiliations
  • 1Critical Care Medicine Department, National Institutes of Health Clinical Center, Bethesda, Maryland
  • 2University of Utah School of Medicine, National Emergency Medical Services Information System Technical Assistance Center, Salt Lake City
JAMA. 2022;327(9):874-877. doi:10.1001/jama.2022.0812

Surges in hospital COVID-19 caseloads are detrimental to patients hospitalized with COVID-191 and other conditions.2 Transporting patients out of hospitals before reaching critically high caseloads might improve outcomes. However, patients with COVID-19 requiring transfer are often unstable3; evidence on the safety of transporting patients with COVID-19 is scarce.4,5 We leveraged a national emergency medical services (EMS) database to compare the frequency of interhospital transportation events and associated life-threatening deterioration during transport among patients with acute lower respiratory tract illness (LRTI) during (vs before) the pandemic.

Methods

A retrospective cohort study was conducted using the National Emergency Medical Services Information System database. This database is composed of standardized data on EMS activations from 48 US states, including data from some individual health systems and private ambulance services. Unique interhospital ground and air transports by EMS agencies that reported continuously for each month from January 1, 2019, through February 28, 2021, were identified. Trends in daily count of transports for patients with EMS-documented primary or secondary impressions of acute LRTI (eTables 1-4 in the Supplement) were calculated for a prepandemic period (January 2019-February 2020) and 3 US pandemic waves (first wave: March-May 2020, second wave: June-August 2020, and third wave: September 2020-February 2021). The change in the aggregate count of transports during each pandemic wave relative to corresponding months in the prior year enabled determination of temporal patterns while accounting for seasonality.

Decompensation during transport of patients with acute LRTI was identified using cardiac arrest resuscitation, advanced airway placement, and initiation of noninvasive positive pressure ventilation (NIPPV) (eTables 5-7 in the Supplement). Logistic regression models were used to determine the adjusted odds ratio (aOR) of each decompensation indicator during the pandemic (vs prepandemic) period by transport method, while controlling for age, sex, baseline acuity, transport unit level of care, and Census region. Python version 3.9.6 (Python Software Foundation) and SAS version 9.4 (SAS Institute) were used for analysis. Given the use of deidentified data, the study was deemed not to require ethics board approval by the Office of Human Subjects Research Protection, National Institutes of Health, under the revised Common Rule.

Results

Of 1 099 351 interhospital transports by 1252 US EMS agencies between January 2019 and February 2021, 85 359 (7.8%) occurred for patients with acute LRTI. Of these, 76 510 (89.6%) were ground and 8849 (10.4%) were air transport. The proportion of transported patients categorized as low, emergent, or critical acuity at transport onset were similar before and during the pandemic (Table).6 Interhospital ground transports for acute LRTI declined from 8512 before the pandemic to 7728 during the first wave (difference, 784; –9.2%; Figure, A and B), but subsequently increased in the second wave from 6261 before the pandemic to 8018 (difference, 1757; 28.1%) and in the third wave from 18 348 before the pandemic to 21 371 (difference, 3023; 16.5%). Air transports increased during all 3 waves (Figure, C) and maximally during the second wave from 702 before the pandemic to 1181 (difference, 479; 68.2%; Figure, D). Yet, air transports continued to represent less than 12% of acute LRTI transports (Figure, C).

The odds of intratransport cardiac arrest resuscitation, advanced airway placements, and NIPPV initiation did not increase during the pandemic (vs prepandemic) period for both ground and air transports (Table). The odds were lower for NIPPV initiation in ground transports (1280 [3.2%] before the pandemic vs 1003 [2.7%] during the pandemic; aOR, 0.68 [95% CI, 0.62-0.74]) and for cardiac arrest resuscitations in air transports (163 [4.1%] before the pandemic vs 162 [3.3%] during the pandemic; aOR, 0.76 [95% CI, 0.60-0.95]).

Discussion

This study of hospital-to-hospital transports for patients with acute LRTI (a population likely enriched for patients with COVID-19 during the pandemic) found no increases in intratransport cardiac arrest, advanced airway placements, or NIPPV initiations during the pandemic (vs prepandemic) period. These findings persisted even as total transports increased in the second and third waves.

Study limitations include a potential lack of national representativeness of the database, an absence of database-specific comorbidity and COVID-19 codes for the study period, and risk of unmeasured confounding given the potential subjectivity in EMS reporting of initial acuity.

These findings increase confidence in the safety of transferring patients with LRTI during the pandemic.

Section Editors: Jody W. Zylke, MD, Deputy Editor; Kristin Walter, MD, Associate Editor.
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Article Information

Accepted for Publication: January 18, 2022.

Published Online: January 28, 2022. doi:10.1001/jama.2022.0812

Corresponding Author: Sameer S. Kadri, MD, MS, Clinical Epidemiology Section, Critical Care Medicine Department, National Institutes of Health, 10 Center Dr, Bldg 10-2C145, Bethesda, MD 20892 (sameer.kadri@nih.gov).

Author Contributions: Mr Mancera and Dr Kadri had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Sarzynski, Warner, Kadri.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Sarzynski, Mancera, Kadri.

Critical revision of the manuscript for important intellectual content: Sarzynski, Mann, Dai, Sun, Warner, Kadri.

Statistical analysis: Sarzynski, Mancera, Mann, Dai, Sun, Warner.

Obtained funding: Kadri.

Administrative, technical, or material support: Mann, Warner.

Supervision: Kadri.

Conflict of Interest Disclosures: None reported.

Funding/Support: This work was supported by the Intramural Research Program of the National Institutes of Health (NIH) Clinical Center.

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The findings and conclusions in this study are those of the authors and do not necessarily represent the official position of the NIH.

Additional Contributions: We thank Skyler Peterson, MS, and Eric Chaney, MS, MBA, NREMT (both from National Emergency Medical Services Information System [NEMSIS], Salt Lake City, Utah), for their insightful feedback on the NEMSIS database. Ms Peterson and Mr Chaney did not receive financial compensation for their contribution. We thank Kelly Byrne, AA (Critical Care Medicine Department, NIH Clinical Center, Bethesda, Maryland), for assistance with formatting the manuscript. Ms Byrne did not receive financial compensation for her contribution.

References
1.
Kadri  SS, Sun  J, Lawandi  A,  et al.  Association between caseload surge and COVID-19 survival in 558 US hospitals, March to August 2020.   Ann Intern Med. 2021;174(9):1240-1251.PubMedGoogle ScholarCrossref
2.
Payet  C, Polazzi  S, Rimmelé  T, Duclos  A.  Mortality among noncoronavirus disease 2019 critically ill patients attributable to the pandemic in France.   Crit Care Med. 2022;50(1):138-143.PubMedGoogle ScholarCrossref
3.
Troncoso  RD  Jr, Garfinkel  EM, Leon  D,  et al.  Decision making and interventions during interfacility transport of high-acuity patients with severe acute respiratory syndrome coronavirus 2 infection.   Air Med J. 2021;40(4):220-224.PubMedGoogle ScholarCrossref
4.
Allen  R, Wanersdorfer  K, Zebley  J, Shapiro  G, Coullahan  T, Sarani  B.  Interhospital transfer of critically ill patients because of coronavirus disease 19–related respiratory failure.   Air Med J. 2020;39(6):498-501.PubMedGoogle ScholarCrossref
5.
Painvin  B, Messet  H, Rodriguez  M,  et al.  Inter-hospital transport of critically ill patients to manage the intensive care unit surge during the COVID-19 pandemic in France.   Ann Intensive Care. 2021;11(1):54.PubMedGoogle ScholarCrossref
6.
Kadri  SS, Gundrum  J, Warner  S,  et al.  Uptake and accuracy of the diagnosis code for COVID-19 among US hospitalizations.   JAMA. 2020;324(24):2553-2554.PubMedGoogle ScholarCrossref
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