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Original Article
Infection Impact of negative-pressure room utilization in the emergency department on hospitalized pneumonia patients during the COVID-19 pandemic in Thailand

DOI: https://doi.org/10.4266/acc.003350
Published online: March 27, 2026

1Department of Emergency Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand

2Acute Care and Emergency Medicine (ACE) Research Cluster, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand

3Strategy to Achieve Emergency Medicine Research in Thailand (START) Working Group, Thailand

Corresponding author: Borwon Wittayachamnankul Department of Emergency Medicine, Faculty of Medicine, Chiang Mai University, 110 Inthawaroros Rd, Sribhumi, Amphoe Muang Chiang Mai, Chiang Mai 50200, Thailand Tel: +66-53-93-6722 Fax: +66-53-93-6722 Email: borwon.witt@cmu.ac.th
• Received: August 22, 2025   • Revised: December 6, 2025   • Accepted: December 25, 2025

© 2026 The Korean Society of Critical Care Medicine

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • Background
    During the coronavirus disease 2019 (COVID-19) outbreak, negative-pressure rooms were implemented to isolate high-risk COVID-19 patients. This study compared pneumonia patient outcomes before and after their implementation, focusing on in-hospital mortality as the primary outcome.
  • Methods
    We conducted a retrospective cohort study of adult pneumonia patients admitted to a tertiary hospital in Northern Thailand, excluding those with trauma-related illness, out-of-hospital cardiac arrest/in-hospital cardiac arrest, or incomplete data. The primary outcome was in-hospital mortality, and the outcomes were door-to-first doctor contact time, door-to-antibiotic time, emergency department (ED) length of stay (LOS), intensive care unit (ICU) admission, and 30-day mortality.
  • Results
    Data from 220 pneumonia patients (104 pre-pandemic, 116 pandemic) were analyzed. Of these, 58.6% were elderly males with comorbidities like hypertension and diabetes. Door-to-first doctor contact time was longer during the pandemic (median, 1 vs. 0 minutes; P<0.001), as was ED LOS (median, 5.9 vs. 4.1 hours; P<0.001). Door-to-antibiotic time was also longer in unadjusted comparisons (median, 60.0 vs 36.5 minutes; P<0.001), but the difference was attenuated and not statistically significant after adjustment (adjusted mean difference, 14.2 minutes; P=0.071). No significant differences in in-hospital mortality, 30-day mortality, or ICU admissions were observed.
  • Conclusions
    Negative-pressure rooms led to increased door-to-doctor contact time and ED LOS during COVID-19, although without significant differences in mortality. These findings highlight the need to improve ED workflows for future pandemic preparedness.
  • Key Words: antibiotics; COVID-19; mortality; patient isolation; pneumonia
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19) and spreads through droplets from an infected person's respiratory system [1,2]. Infection with COVID-19 can lead to pneumonia and can be particularly problematic during treatment procedures especially aerosol-generating procedures, such as nebulization and endotracheal intubation [3]. To prevent the spread of the virus during the pandemic, hospitals took measures to limit infection and reduce transmission, for example patient isolation in negative-pressure rooms for primary infection control and screening [4].
To protect other patients and attending staff from COVID-19 infection, the use of negative-pressure rooms in the emergency department (ED) was believed to be crucial [5]. These negative-pressure rooms were specifically utilized to screen patients with a history of respiratory infections or symptoms that require immediate medical attention [4-6]. Many patients presenting with respiratory symptoms are diagnosed with pneumonia, but during the pandemic period, it was essential to consider the possibility of COVID-19 infection as well [7,8]. Therefore, patients suspected of having COVID-19 were examined at a separate clinic designated for respiratory infection screening [5,6]. This approach helped to maintain a safe environment within the ED and minimize the risk of transmitting COVID-19 to other patients and healthcare staff. An important aspect of the utilization of negative-pressure rooms was their usefulness in the process of ruling out COVID-19 in patients [5,6,9]. Although negative COVID-19 screening test results using an antigen test kit did not totally rule out the ability of the patient to transmit COVID-19, the possibility of infection was considered reduced. In the case of negative screening test results for highly suspect patients negative in the screening test, polymerase chain reaction testing was subsequently performed to definitively rule out COVID-19. This additional step was essential due to the overlapping symptoms of pneumonia, COVID-19, and other respiratory illnesses.
However, the implementation of negative-pressure rooms for pneumonia patients presented certain challenges, including delays in patient care due to the need for healthcare providers to don personal protective equipment (PPE) before entering these rooms [6,10,11]. This issue was particularly relevant when considering the similarities in symptoms between pneumonia and COVID-19 patients, as distinction between the two disease requires thorough screening and assessment. Although some studies have evaluated the effectiveness and efficiency of negative-pressure rooms in reducing hospitalization rates for patients with respiratory tract infections, their impact on patient care, particularly in the context of pneumonia, requires further research due to the limited number of studies reported in the literature [4-6]. Furthermore, there is a lack of research specifically addressing the challenges and potential delays associated with the utilization of negative-pressure rooms during the COVID-19 pandemic. To address these concerns and determine the optimal approach to balancing infection control measures and efficient patient care in the ED, we aimed to evaluate the impact of negative-pressure room utilization on pneumonia patient outcomes by comparing cases managed before and after their implementation. The primary outcome was in-hospital mortality, and the secondary outcomes were door-to-doctor time, door-to-antibiotic time, ED length of stay (LOS), intensive care unit (ICU) admission, and 30-day mortality.
This study complied with the Strengthening of the Reporting of Observational studies in Epidemiology (STROBE) statement recommendations and received ethical approval from the Research Ethics Committee, Faculty of Medicine, Chiang Mai University (No. EME-2565-09109) and the Thai Clinical Trials Registry Committee, Medical Research Foundation of Thailand (Permit No. TCTR20230819002). The requirement for informed consent was waived by the institutional ethics committee.
A retrospective observational study was conducted in the ED of Chiang Mai University Hospital, a teaching hospital in Northern Thailand. In Thailand, the COVID-19 outbreak started in early 2020. Any patient who visited the ED in 2019 was classified as being in the before COVID-19 pandemic group. Any patient attending between 2020 and 2022 was allocated to the during COVID-19 pandemic group.
The Chiang Mai University Hospital ED at the time of the pandemic contained four negative-pressure isolation rooms designed for airborne infection control that were established in May 2020. Each room was separated from other treatment areas with a dedicated ventilation system. The pressure differential was maintained at –15 Pa inside the patient room, –10 Pa in the anteroom, and –5 Pa at the corridor entrance, preventing contaminated air from escaping to adjacent areas. Ventilation provided at least 10 air changes per hour. The exhaust air underwent high efficiency particulate air filtration combined with ultraviolet C and ozone treatment before being released outside.
Patients aged 18 years old and older with an initial diagnosis of pneumonia (ICD-10 codes J12-J18) who were subsequently admitted to hospital were included in the study. In the COVID-19 pandemic group, all eligible patients were transferred to one of the four negative-pressure rooms next to the ED. Exclusion criteria were trauma-related illness, experience of out-of-hospital cardiac arrest or in-hospital cardiac arrest, other causes not related to pneumonia, and incomplete data regarding potential confounding factors. Pneumonia patients before the COVID-19 pandemic represented the group treated in the ED before the installation of negative-pressure rooms. In contrast, all patients during the COVID-19 pandemic who fulfilled the inclusion criteria were transferred to a negative-pressure room.
Data were collected from electronic medical records of patients diagnosed with pneumonia during the COVID-19 pandemic (between 2020 and 2022) and patients diagnosed with pneumonia in the year prior to the COVID-19 outbreak (of 2019) in Thailand using Digicard and SMI electronic medical record programs (Maharaj Nakorn Chiang Mai Hospital). Data were collected in the form of case record forms. Using the two independent proportion sample size estimation formula based on Fisher's exact test [12] for use in 2×2 comparative trials with low event rates [8] and data from Bologheanu et al.'s study [11], a sample size of 220 participants (110 participants per group) was found to be required with an alpha error of 0.05 and power of 0.8.
Baseline characteristics are reported as numbers, percentages, means, medians, standard deviations, and interquartile ranges (IQRs) as appropriate. Fisher’s exact test was used to compare categorical data. Normally and non-normally distributed continuous data were compared using a t-test or Wilcoxon rank sum test, respectively. A complete-case analysis was used to compare the primary and secondary outcomes. Age, sex, endotracheal intubation, and initial blood lactate were included as variables in the multivariable model because these are known clinical factors associated with pneumonia severity and patient outcomes. These variables were selected a priori based on clinical importance rather than statistical significance to control for potential confounding effects. Univariable (unadjusted) and multivariable (adjusted) logistic regression and regression analysis of means were used to calculate the odds ratio and mean difference of the outcomes before and during the COVID-19 pandemic as appropriate. Stata version 16.0 (Stata Corp.) was used to analyze the data. A P-values <0.05 was considered to denote statistical significance.
A total of 220 patients were included, comprising 104 patients seen in the ED before the COVID-19 pandemic and 116 patients seen during the COVID-19 pandemic (Figure 1). Slightly more than half of the patients were males (58.6%) with hypertension (58.6%), dyslipidemia (38.2%), and/or diabetes (21.8%) as comorbidities. All baseline characteristics were similar before and during the COVID-19 pandemic, except for age, chronic kidney disease, chronic obstructive pulmonary disease, Glasgow coma scale, white blood cell count, and platelet count (Table 1). Door-to-first doctor contact time (median, 1 minute; IQR, 0–5 minutes vs. 0 minutes; IQR, 0–0 minutes), door-to-antibiotic time during the COVID-19 pandemic (median, 60 minute; IQR, 30–84.5 minutes vs. 36.5 minute; IQR, 25–72.5 minutes) (P<0.001), and ED LOS during the pandemic (median, 5.9 hours; IQR, 4.4–7.7 hours vs. 4.1 hours; IQR, 3.3–5.1 hours) were significantly longer during the COVID-19 pandemic than before the pandemic (P<0.001 for each).
After adjusting for confounding factors (age, sex, endotracheal intubation, and initial blood lactate) (Table 2), there were no significant differences in in-hospital mortality (adjusted odds ratio [aOR], 1.28; 95% CI, 0.72 to 2.26; P=0.406) or 30-day mortality (aOR, 0.89; 95% CI, 0.55 to 1.45; P=0.642) between the periods. Similarly, door-to-antibiotic time (adjusted mean difference [aMD], 14.20 minutes; 95% CI, –1.21 to 29.61 minutes; P=0.071) and ED-to-ICU admission (aOR, 1.35; 95% CI, 0.91 to 2.01; P=0.136) were not significantly different. However, door-to-first doctor contact time (aMD, 2.51; 95% CI 1.50 to 3.53; P<0.001) and ED LOS (aMD, 2.03; 95% CI, 1.18 to 2.88; P<0.001) were longer during the pandemic.
This study examined the impact of the utilization of negative-pressure rooms in the ED for pneumonia patients during the COVID-19 pandemic. Use of negative-pressure rooms did not significantly reduce in-hospital mortality rate when compared with the pre-pandemic period. Furthermore, there were no notable differences in important factors such as time to administer the first dose of antibiotics, duration from arrival to antibiotic treatment, LOS in the ED, or the rate of admission to the ICU between the two groups. However, it was observed that the door-to-first doctor contact time and overall ED LOS were prolonged during the COVID-19 pandemic, findings similar to those from previous studies [13,14]. Although the median door-to-doctor contact time increase of 1-2 minutes may be modest for an individual patient, its co-occurrence with a 21 minute delay to antibiotics and a 111 minute longer ED LOS indicates a system-level throughput impact attributable to isolation workflows rather than a trivial timing fluctuation.
While the mortality rate did not show a significant increase, the presence of negative-pressure rooms and the precautions taken during the pandemic might have impacted the efficiency of patient care, particularly in terms of timely access to healthcare providers and the overall duration of stay in the ED. Although the implementation of additional infection control measures did not result in a statistically significant difference in door-to-antibiotic time, these measures may have contributed to delays in antibiotic initiation for pneumonia patients, potentially exceeding the 1-hour target recommended by the Surviving Sepsis Campaign guidelines [15]. Previous studies have reported inconsistent results regarding whether infection control measures lead to delays in antibiotic administration [3,13,14]. These associations warrant further investigation in future studies.
The prolonged ED LOS observed in our study is consistent with isolation-related operational demands: additional infection-control steps including donning and doffing PPE, more comprehensive screening/diagnostics to exclude COVID-19, and downstream constraints in bed capacity and patient flow. While necessary for infection control, these processes create system-level throughput inefficiencies, aligning with the observed increases in door-to-doctor contact time, door-to-antibiotic time, and ED LOS. To mitigate such delays in future outbreaks, ED workflows should prioritize streamlined PPE pathways [5,10], targeted staff training, staffing models adapted for isolation areas, and digital tools for real-time coordination and monitoring. In addition to these operational inefficiencies, several specific factors likely contributed to the prolonged ED LOS during the pandemic. First, the time required for COVID-19 testing added to delays before final disposition. Second, logistical challenges in arranging safe patient transfer, including coordination of isolation transport routes and bed availability, created bottlenecks. Third, admission decision-making itself was prolonged, given the need to rule out COVID-19 before ward assignment. To improve efficiency in future outbreaks, cohort isolation strategies and streamlined testing protocols may help reduce unnecessary delays.
To enhance ED efficiency and improve patient care, a multifaceted approach focusing on negative-pressure rooms and overall workflow optimization is crucial. This involves streamlining PPE protocols, including optimizing donning/doffing procedures, and ensuring readily available, high-quality PPE [5,10]. For example, implementing a "buddy system" for PPE doffing [16] or video-based education [17] may help reduce errors, contamination risk, and improve door-to-first doctor contact times. Ensuring a robust supply chain for PPE, as highlighted by Lau et al. [18], is also essential for maintaining adequate stock and minimizing disruptions to care. Furthermore, comprehensive staff training on proper and efficient PPE usage is essential to equip healthcare providers with the necessary skills to minimize delays and optimize patient care. Simulation-based training can be particularly effective in improving provider confidence and performance in emergency situations [19]. Improving overall workflow efficiency is equally vital. This can be achieved by identifying and addressing the root causes of delays in door-to-first doctor contact time. Applying lean methodology to ED workflows can help identify and eliminate these bottlenecks [20]. Investigating the staffing implications of negative-pressure rooms and PPE requirements and subsequently adjusting staffing levels or roles can significantly enhance patient flow [3]. Dedicating staff specifically for PPE procedures and ensuring proper resource allocation can facilitate prompt patient care. Finally, leveraging digital tools such as electronic health records, real-time communication platforms, and automated monitoring systems can further streamline processes and minimize delays in the ED. For instance, incorporating telemedicine for initial patient assessments can help triage patients effectively and reduce the burden on in-person ED services [21].
Further investigations should aim to address the limitations of this study by increasing sample sizes and conducting multi-center trials. This would enhance the generalizability of the findings and provide a more comprehensive understanding of the impact of negative-pressure rooms on patient care. Future studies should also explore innovative technologies and process improvements that can optimize the patient care process in negative-pressure rooms. These may include advancements in PPE design, more efficient workflow, and the utilization of digital tools or automation to minimize delays and enhance efficiency. It is also necessary to investigate the specific factors contributing to extended ED stays and evaluate the effectiveness of interventions aimed at reducing these delays, ultimately improving patient flow, mitigating ED overcrowding, and enhancing overall patient care and experience in the context of negative-pressure room utilization.
Several limitations should be acknowledged when interpreting the findings of this study. First, the single-center setting limits generalizability of the results to a broader population as the findings may not be representative of other healthcare settings or patient populations. Second, the retrospective nature of the design may have affected data collection and outcomes such as timestamps for ED-to-ward transfer; therefore, differences in ED-to-ward admission time could not be robustly evaluated. Although we adjusted for confounding factors using statistical methods, this may not have been sufficient to address the impacts of all measurable and unmeasurable confounding factors. Third, the analysis was restricted to admitted pneumonia patients. As such, non-admitted cases (e.g., discharged, transferred, or ED deaths) could not be evaluated. Future research with broader ethical approval and complete ED-level datasets is warranted to fully assess the operational impact of negative-pressure room use across all patient dispositions.
Negative-pressure room utilization was associated with longer door-to-doctor contact time (+2 minutes), and prolonged ED LOS (+111 minutes) during the pandemic, supporting the presence of operational delays and underscoring the need for protocolized efficiency measures to mitigate delays and improve care. Strategies to optimize PPE protocols, enhance staff training, address staffing models, and leverage digital tools may help minimize delays and improve care in the context of negative-pressure room use.

CONFLICT OF INTEREST

No potential conflict of interest relevant to this article was reported.

FUNDING

This work was supported by a grant from the Faculty of Medicine, Chiang Mai University (grant No. 9190-65 awarded on 5 May, 2022).

ACKNOWLEDGMENTS

We would like to thank Miss Rudklao Sairai in the Research Unit of Department of Emergency Medicine, Faculty of Medicine, Chiang Mai University for facilitating this study. This study was supported by a grant from the Faculty of Medicine, Chiang Mai University Research Fund (No. 9190-65).

AUTHOR CONTRIBUTIONS

Conceptualization: TD, TT, WW, BW. Methodology: TD, TT, WW, BW. Software: TT. Validation: TT, WW. Formal analysis: TD, TT, WW. Investigation: TD, TT, WW, BW. Resources: WW. Data curation: TD, TT. Visualization: TD. Supervision: WW. Project administration: WW. Funding acquisition: BW. Writing - original draft: TD, TT, WW, BW. Writing - review & editing: TD, TT, WW, BW. All authors read and agreed to the published version of the manuscript.

Figure 1.
Flow diagram of the patient data. ED: emergency department; COVID-19: coronavirus disease 2019; ICD-10: International Classification of Diseases, 10th Revision.
acc-003350f1.jpg
Table 1.
Baseline characteristics
Characteristics Overall (n=220) Before COVID-19 pandemic(n=104) During COVID-19 pandemic (n=116) P-value
Age (yr) 73±16 76±15 69±17 0.001a)
 ≥ 60 180 (81.8) 94 (90.4) 86 (74.1) 0.003b)
Male 129 (58.6) 57 (54.8) 72 (62.1) 0.337b)
EMS use 8 (3.6) 1 (1.0) 7 (6.0) 0.069b)
Comorbidity
 Hypertension 129 (58.6) 64 (61.5) 65 (56.0) 0.415b)
 Dyslipidemia 84 (38.2) 45 (43.3) 39 (33.6) 0.165b)
 Diabetes 48 (21.8) 29 (27.9) 19 (16.4) 0.050b)
 Chronic kidney disease 41 (18.6) 13 (12.5) 28 (24.1) 0.037b)
 Cancer 39 (17.7) 21 (20.2) 18 (15.5) 0.382b)
 COPD 26 (11.8) 20 (19.2) 6 (5.2) 0.001b)
 CAD 20 (9.1) 13 (12.5) 7 (6.0) 0.106b)
 Bedridden 20 (9.1) 11 (10.6) 9 (7.8) 0.491b)
 Tuberculosis 11 (5.0) 2 (1.9) 9 (7.8) 0.063b)
Temperature (°C) 37.6±1.2 37.7±1.1 37.6±1.2 0.491a)
 <36 10 (4.6) 4 (3.9) 6 (5.3) 0.708b)
 36–38 129 (59.5) 60 (57.7) 69 (61.1)
 >38 78 (35.9) 40 (38.4) 38 (33.6)
Pulse rate (beats per minute) 105±23 105±23 105±23 0.939a)
 ≤90 60 (27.3) 27 (26.0) 33 (28.5) 0.762b)
 >90 160 (72.7) 77 (74.0) 83 (71.5)
Systolic blood pressure (mm Hg) 129±25 126±27 132±24 0.073a)
 ≤100 26 (11.8) 16 (15.4) 10 (8.6) 0.145b)
 >100 194 (88.2) 88 (84.6) 106 (91.4)
Respiratory rate (breaths per minute) 31±8 31±7 31±9 0.647a)
 <22 23 (10.5) 13 (12.5) 10 (8.6) 0.384b)
 ≥22 197 (89.5) 91 (87.5) 106 (91.4)
Oxygen saturation (%) 87±10 87±11 87±9.9 0.995a)
 <89 96 (43.6) 44 (42.3) 52 (44.8) 0.883b)
 89–93 70 (31.8) 33 (31.7) 37 (31.9)
 ≥94 54 (24.6) 27 (26.0) 27 (23.3)
GCS 15 (14–15) 15 (12–15) 15 (12–15) 0.009c)
NEWS 8±3 8±3 8±2 0.530a)
Hemoglobin (g/dl) 11.3±2.5 11.1±2.3 11.5±2.7 0.194a)
Hematocrit (%) 34.5±7.4 34.0±6.9 34.9±7.8 0.351a)
White blood cell count (×103/µl) 11.0 (7.7–15.0) 11.6 (9.1–16.1) 10.3 (6.4–13.8) 0.012c)
 <4 (leukopenia) 13 (5.9) 4 (3.9) 9 (7.8) 0.262b)
Neutrophil (%) 79.2±13.3 79.6±13.6 78.8±13.0 0.635a)
Platelet count (×103/µl) 251.4±126.5 273.9±134.0 231.3±116.3 0.012a)
 < 150 41 (18.6) 15 (14.4) 26 (22.4) 0.165b)
Serum creatinine (mg/dl) 1.03 (0.67–1.58) 0.98 (0.66–1.43) 1.03 (0.70–1.66) 0.439c)
 ≤1.5 163 (74.4) 79 (76.7) 84 (72.4) 0.536b)
 >1.5 56 (25.6) 24 (23.3) 32 (27.6)
Albumin (g/dl) 3.4±0.6 3.3±0.5 3.4±0.6 0.302a)
Aspartate aminotransferase (IU/L) 27 (19–45) 25 (19–36) 30 (20–54) 0.095c)
Total bilirubin (mg/dl) 0.6 (0.4–0.9) 0.6 (0.4–0.9) 0.5 (0.4–1.0) 0.705c)
Initial blood lactate (mmol/L) 2.1 (1.6–3.2) 1.9 (1.5–3.1) 2.3 (1.6–3.6) 0.30c)
COVID-19 test -
 Positive - - 38 (32.8)
 Negative - - 78 (67.2)
Lobar pneumonia based on CXR 214 (97.3) 102 (98.1) 112 (96.6) 0.686b)
Endotracheal intubation 65 (29.6) 36 (34.6) 29 (25.0) 0.139b)
Door-to-first doctor contact time (min) 0 (0–2) 0 (0–0) 1 (0–5) <0.001c)
Door-to-antibiotic time (min) 50 (30–84.5) 36.5 (25–72.5) 60.0 (30–84.5) <0.001c)
ED length of stay (hr) 4.8 (3.8–6.6) 4.1 (3.3–5.1) 5.9 (4.4–7.7) <0.001c)
ED disposition
 Admit ward 164 (74.6) 80 (76.9) 84 (72.4) 0.536b)
 ICU admission 56 (25.4) 24 (23.1) 32 (27.6)
In-hospital mortality 40 (18.2) 17 (16.4) 23 (19.8) 0.600b)
30-Day mortality 50 (22.7) 27 (26.0) 23 (19.8) 0.334b)

Values are presented as mean±standard deviation, number (%), or median (interquartile range).

COVID-19: coronavirus disease 2019; EMS: emergency medical services; COPD: chronic obstructive pulmonary disease; CAD: coronary-artery disease; GCS: Glasgow coma scale; NEWS: National Early Warning Score; CXR: chest radiography; ED: emergency department; ICU: intensive care unit.

a)Analyzed by t-test;

b)Analyzed by Fisher’s exact test;

c)Analyzed by Wilcoxon rank sum test.

Table 2.
Clinical outcomes before and during the COVID-19 pandemic
Outcome Unadjusted Adjusteda)
Effect estimate (95% CI) P-value Effect estimate (95% CI) P-value
In-hospital mortalityb) 1.21 (0.69 to 2.14) 0.505 1.28 (0.72 to 2.26) 0.406
Door-to-first doctor contact time (min)c) 2.94 (2.01 to 3.87) <0.001 2.51 (1.50 to 3.53) <0.001
Door-to-antibiotic time (min)c) 16.84 (2.11 to 31.58) 0.025 14.20 (–1.21 to 29.61) 0.071
ED length of stay (hr)c) 2.02 (1.26 to 2.79) <0.001 2.03 (1.18 to 2.88) <0.001
ED disposition to the ICU (ICU admission)b) 1.20 (0.76 to 1.89) 0.445 1.35 (0.91 to 2.01) 0.136
30-Day mortalityb) 0.76 (0.47 to 1.25) 0.280 0.89 (0.55 to 1.45) 0.642

COVID-19: coronavirus disease 2019; ED: emergency department; ICU: intensive care unit.

a)Adjusted for age, sex, endotracheal intubation, initial blood lactate using patients who visited the ED before the COVID-19 pandemic as the reference group;

b)Presented as odds ratio;

c)Presented as mean difference.

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        Impact of negative-pressure room utilization in the emergency department on hospitalized pneumonia patients during the COVID-19 pandemic in Thailand
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      Impact of negative-pressure room utilization in the emergency department on hospitalized pneumonia patients during the COVID-19 pandemic in Thailand
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      Figure 1. Flow diagram of the patient data. ED: emergency department; COVID-19: coronavirus disease 2019; ICD-10: International Classification of Diseases, 10th Revision.

      Figure 1.

      Impact of negative-pressure room utilization in the emergency department on hospitalized pneumonia patients during the COVID-19 pandemic in Thailand
      Characteristics Overall (n=220) Before COVID-19 pandemic(n=104) During COVID-19 pandemic (n=116) P-value
      Age (yr) 73±16 76±15 69±17 0.001a)
       ≥ 60 180 (81.8) 94 (90.4) 86 (74.1) 0.003b)
      Male 129 (58.6) 57 (54.8) 72 (62.1) 0.337b)
      EMS use 8 (3.6) 1 (1.0) 7 (6.0) 0.069b)
      Comorbidity
       Hypertension 129 (58.6) 64 (61.5) 65 (56.0) 0.415b)
       Dyslipidemia 84 (38.2) 45 (43.3) 39 (33.6) 0.165b)
       Diabetes 48 (21.8) 29 (27.9) 19 (16.4) 0.050b)
       Chronic kidney disease 41 (18.6) 13 (12.5) 28 (24.1) 0.037b)
       Cancer 39 (17.7) 21 (20.2) 18 (15.5) 0.382b)
       COPD 26 (11.8) 20 (19.2) 6 (5.2) 0.001b)
       CAD 20 (9.1) 13 (12.5) 7 (6.0) 0.106b)
       Bedridden 20 (9.1) 11 (10.6) 9 (7.8) 0.491b)
       Tuberculosis 11 (5.0) 2 (1.9) 9 (7.8) 0.063b)
      Temperature (°C) 37.6±1.2 37.7±1.1 37.6±1.2 0.491a)
       <36 10 (4.6) 4 (3.9) 6 (5.3) 0.708b)
       36–38 129 (59.5) 60 (57.7) 69 (61.1)
       >38 78 (35.9) 40 (38.4) 38 (33.6)
      Pulse rate (beats per minute) 105±23 105±23 105±23 0.939a)
       ≤90 60 (27.3) 27 (26.0) 33 (28.5) 0.762b)
       >90 160 (72.7) 77 (74.0) 83 (71.5)
      Systolic blood pressure (mm Hg) 129±25 126±27 132±24 0.073a)
       ≤100 26 (11.8) 16 (15.4) 10 (8.6) 0.145b)
       >100 194 (88.2) 88 (84.6) 106 (91.4)
      Respiratory rate (breaths per minute) 31±8 31±7 31±9 0.647a)
       <22 23 (10.5) 13 (12.5) 10 (8.6) 0.384b)
       ≥22 197 (89.5) 91 (87.5) 106 (91.4)
      Oxygen saturation (%) 87±10 87±11 87±9.9 0.995a)
       <89 96 (43.6) 44 (42.3) 52 (44.8) 0.883b)
       89–93 70 (31.8) 33 (31.7) 37 (31.9)
       ≥94 54 (24.6) 27 (26.0) 27 (23.3)
      GCS 15 (14–15) 15 (12–15) 15 (12–15) 0.009c)
      NEWS 8±3 8±3 8±2 0.530a)
      Hemoglobin (g/dl) 11.3±2.5 11.1±2.3 11.5±2.7 0.194a)
      Hematocrit (%) 34.5±7.4 34.0±6.9 34.9±7.8 0.351a)
      White blood cell count (×103/µl) 11.0 (7.7–15.0) 11.6 (9.1–16.1) 10.3 (6.4–13.8) 0.012c)
       <4 (leukopenia) 13 (5.9) 4 (3.9) 9 (7.8) 0.262b)
      Neutrophil (%) 79.2±13.3 79.6±13.6 78.8±13.0 0.635a)
      Platelet count (×103/µl) 251.4±126.5 273.9±134.0 231.3±116.3 0.012a)
       < 150 41 (18.6) 15 (14.4) 26 (22.4) 0.165b)
      Serum creatinine (mg/dl) 1.03 (0.67–1.58) 0.98 (0.66–1.43) 1.03 (0.70–1.66) 0.439c)
       ≤1.5 163 (74.4) 79 (76.7) 84 (72.4) 0.536b)
       >1.5 56 (25.6) 24 (23.3) 32 (27.6)
      Albumin (g/dl) 3.4±0.6 3.3±0.5 3.4±0.6 0.302a)
      Aspartate aminotransferase (IU/L) 27 (19–45) 25 (19–36) 30 (20–54) 0.095c)
      Total bilirubin (mg/dl) 0.6 (0.4–0.9) 0.6 (0.4–0.9) 0.5 (0.4–1.0) 0.705c)
      Initial blood lactate (mmol/L) 2.1 (1.6–3.2) 1.9 (1.5–3.1) 2.3 (1.6–3.6) 0.30c)
      COVID-19 test -
       Positive - - 38 (32.8)
       Negative - - 78 (67.2)
      Lobar pneumonia based on CXR 214 (97.3) 102 (98.1) 112 (96.6) 0.686b)
      Endotracheal intubation 65 (29.6) 36 (34.6) 29 (25.0) 0.139b)
      Door-to-first doctor contact time (min) 0 (0–2) 0 (0–0) 1 (0–5) <0.001c)
      Door-to-antibiotic time (min) 50 (30–84.5) 36.5 (25–72.5) 60.0 (30–84.5) <0.001c)
      ED length of stay (hr) 4.8 (3.8–6.6) 4.1 (3.3–5.1) 5.9 (4.4–7.7) <0.001c)
      ED disposition
       Admit ward 164 (74.6) 80 (76.9) 84 (72.4) 0.536b)
       ICU admission 56 (25.4) 24 (23.1) 32 (27.6)
      In-hospital mortality 40 (18.2) 17 (16.4) 23 (19.8) 0.600b)
      30-Day mortality 50 (22.7) 27 (26.0) 23 (19.8) 0.334b)
      Outcome Unadjusted Adjusteda)
      Effect estimate (95% CI) P-value Effect estimate (95% CI) P-value
      In-hospital mortalityb) 1.21 (0.69 to 2.14) 0.505 1.28 (0.72 to 2.26) 0.406
      Door-to-first doctor contact time (min)c) 2.94 (2.01 to 3.87) <0.001 2.51 (1.50 to 3.53) <0.001
      Door-to-antibiotic time (min)c) 16.84 (2.11 to 31.58) 0.025 14.20 (–1.21 to 29.61) 0.071
      ED length of stay (hr)c) 2.02 (1.26 to 2.79) <0.001 2.03 (1.18 to 2.88) <0.001
      ED disposition to the ICU (ICU admission)b) 1.20 (0.76 to 1.89) 0.445 1.35 (0.91 to 2.01) 0.136
      30-Day mortalityb) 0.76 (0.47 to 1.25) 0.280 0.89 (0.55 to 1.45) 0.642
      Table 1. Baseline characteristics

      Values are presented as mean±standard deviation, number (%), or median (interquartile range).

      COVID-19: coronavirus disease 2019; EMS: emergency medical services; COPD: chronic obstructive pulmonary disease; CAD: coronary-artery disease; GCS: Glasgow coma scale; NEWS: National Early Warning Score; CXR: chest radiography; ED: emergency department; ICU: intensive care unit.

      Analyzed by t-test;

      Analyzed by Fisher’s exact test;

      Analyzed by Wilcoxon rank sum test.

      Table 2. Clinical outcomes before and during the COVID-19 pandemic

      COVID-19: coronavirus disease 2019; ED: emergency department; ICU: intensive care unit.

      Adjusted for age, sex, endotracheal intubation, initial blood lactate using patients who visited the ED before the COVID-19 pandemic as the reference group;

      Presented as odds ratio;

      Presented as mean difference.

      Table 1.

      Table 2.

      ACC : Acute and Critical Care
      © The Korean Society of Critical Care Medicine.
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