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. 2023 Feb 16;18(2):e0279105. doi: 10.1371/journal.pone.0279105

First and second wave dynamics of emergency department utilization during the COVID-19 pandemic: A retrospective study in 3 hospitals in The Netherlands

Robi Dijk 1,#, Patricia Plaum 2,#, Stan Tummers 3, Frits H M van Osch 4,5,*, Dennis G Barten 1, Gideon H P Latten 3
Editor: Yong-Hong Kuo6
PMCID: PMC9934309  PMID: 36795702

Abstract

Objective

During certain phases of the COVID-19 pandemic, a decrease was observed in emergency department (ED) utilization. Although this phenomenon has been thoroughly characterized for the first wave (FW), second wave (SW) studies are limited. We examined the changes in ED utilization between the FW and SW, compared to 2019 reference periods.

Study design and methods

We performed a retrospective analysis of ED utilization in 3 Dutch hospitals in 2020. The FW and SW (March-June and September–December, respectively) were compared to the reference periods in 2019. ED visits were labeled as (non-)COVID-suspected.

Results

During the FW and SW ED visits decreased by 20.3% and 15.3%, respectively, when compared to reference periods in 2019. During both waves high urgency visits significantly increased with 3.1% and 2.1%, and admission rates (ARs) increased with 5.0% and 10.4%. Trauma related visits decreased by 5.2% and 3.4%. During the SW we observed less COVID-related visits compared to the FW (4,407 vs 3,102 patients). COVID-related visits were significantly more often in higher need of urgent care and ARs were at least 24.0% higher compared to non-COVID visits.

Conclusion

During both COVID-19 waves, ED visits were significantly reduced. ED patients were more often triaged as high urgent, the ED length of stay was longer and ARs were increased compared to the reference period in 2019, reflecting a high burden on ED resources. During the FW, the reduction in ED visits was most pronounced. Here, ARs were also higher and patient were more often triaged as high urgency. These findings stress the need to gain better insight into the motives of patients to delay or avoid emergency care during pandemics, as well as to better prepare EDs for future outbreaks.

Introduction

Since the first cases of SARS-CoV-2 emerged in Wuhan in November 2019, the resultant coronavirus disease (COVID-19) has spread rapidly around the world. In March 2020, the World Health Organization (WHO) declared the outbreak a pandemic [1]. In response to the steep increase of COVID-19 cases in 2020, hospital organizations prepared for increasing patient volumes by changing workforce and infrastructure with particular focus on emergency departments (EDs) [2].

In the Netherlands, the first COVID-19 diagnosis was confirmed on February 27th, 2020. Government regulations were increased stepwise until a partial lockdown was imposed on March 23rd, 2020. This included the closure of public institutions (such as schools) and stay-at-home policies for those with possible COVID-19 infection.

At the end of the first wave (FW, March to June 2020) a total of 50,273 Dutch citizens had tested positive for COVID-19. However, the true number of infections probably was significantly higher because of restricted testing policies, caused by limited testing capability during the FW. 11,397 patients were admitted to a hospital (of which 2,939 (25.8%) to an intensive care unit (ICU)), and 10,067 people died due to COVID-19 [3–5].

Most restrictions were lifted after a rapid drop in COVID-19 infections and hospital admissions in July and August 2020. By September, however, infection rates started to spike again. As a consequence, a second lockdown was enforced [6]. During the second wave (SW, September to December 2020) a total of 726,314 had a confirmed SARS-CoV-2 infection. In the SW, 19,354 patients were admitted to a hospital (3,629 (18.8%) to an ICU), and 10,046 people died from a COVID-19 infection [3, 4].

In the early stages of the pandemic, citizens were advised to only seek care when absolutely necessary [7]. Concerns about non-COVID-19 emergencies were subsequently raised when a 30% reduction in ED visits was observed [8, 9]. It was hypothesized that this reduction was due to both COVID-19 fears and lockdown effects, including reduced exposure to injury-prone activities, improved hygiene measures in the community and downscaling of non-acute healthcare [10]. Other studies found that a relatively large proportion of ED patients reported delay in seeking emergency care [11, 12]. During the SW, elective-non-COVID-care was continued as long as hospital capacity allowed for. In contrast to the FW, studies on ED utilization during the SW are limited.

As the pandemic continues and subsequent waves arise, it is of utter importance to gain better insight into the causes and consequences of healthcare utilization patterns during this public health crisis. Only then we can deliver appropriate care and minimize loss of health due to avoiding urgent care consultations.

In this retrospective observational study, we investigated ED utilization and patient volumes during the FW and SW of the COVID-19 pandemic in the Netherlands, and examined differences between those waves and pre-COVID reference periods.

Methods

Design and setting

In this retrospective observational study, we investigated the utilization of 3 hospital-based EDs in the southeast of the Netherlands during the first and second wave of the COVID-19 pandemic (from March-June and September–December 2020, respectively). Identical periods in 2019 were used as a reference. The 3 EDs combined serve a population of 760,000 individuals. Annual census is 35,000 patients for ED 1, 25,000 for ED 2 and 25,000 for ED 3.

Patients

All patients who visited one of the EDs during the study period were eligible for inclusion.

Patients were excluded when it was unclear whether the ED visit was COVID-19 related and when patients refused participation in retrospective studies. In addition, we excluded patients in which ED length of stay was likely to be documented incorrectly, either 0 minutes or longer than 10 hours were considered to be outliers.

If patients previously declared they do not want to participate in any studies, it is documented in their patient records. These patient records were filtered out before we received the data. For all other patients, it was not reasonable to obtain informed consent due to the number of patients. Also, patients received standard treatment and they did not experience any benefits, harms or risks from this study. The ethics committee waived the need for informed consent.

Data was automatically extracted from the electronic health record from patients and only re-identifiable by the researchers.

Analysis and statistics

We retrieved information from standard digital patient records: age, gender, date of ED visit, possible COVID-19 infection, triage urgency (using the Manchester Triage System, MTS) [13], ED length of stay, referral route, admission and whether the ED visit was trauma related or not. Patients triaged red or orange using the MTS are classified as high urgency visits (seen by doctor within 10 minutes). Yellow, green and blue triage colours (seen by doctor within 1–3 hours) are classified as low urgency visits. From April-May 2020, the EDs prospectively labelled patients as COVID-19 suspected using the criteria in Table 1. We retrospectively retrieved the missing labels for possible COVID-19 infection in patients who presented before hospitals had implemented prospective tracking, using identical criteria (Table 1).

Table 1. Criteria for possible COVID-19 infection.

Criteria
Fever
Dyspnoea
Cough or respiratory complaints
Contact with positive patient
Chest pain
Unexplained nausea, vomiting or abdominal pain
Positive test or awaiting test result
Unexplained diarrhea
Sensory impact of taste and/or smell
Patients whereby history taking was not possible or reliable (e.g. cardiac arrest, unconscious or delirium)
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We compared the ED utilization between the FW and SW and between 2020 and their respective reference periods in 2019.

Data were analyzed using IBM Corp. Released 2020. IBM SPSS Statistics for Macintosh, Version 27.0. Armonk, NY: IBM Corp. Descriptive analyses were used for patient characteristics. Continuous data were reported as means with standard deviation (SD) and compared using Students’ T test, or as medians with interquartile ranges (IQR) and compared using the Mann Whitney U test. Categorial data was reported as absolute numbers and as valid percentages (to correct for missing data); they were compared using chi-square or Fisher exact tests. Since multiple comparisons were made in the analysis, after Bonferroni correction a p-value of 0.05/number of comparisons was considered statistically significant.

The study was approved by the medical ethical committee of Zuyderland Medical Center, Heerlen, the Netherlands (METCZ20210031).

Results

In total, 127,060 patients who visited any of the three EDs in 2019 and 2020 were eligible for inclusion; 4,403 (3.5%) were considered outliers and were excluded (4,362 0-minute visits and 41 more than 10 hours).

Of these eligible patients, 56,719 visited one of the three EDs in the year 2020, compared to 65,938 patients in 2019. Of all included patients, the median age was 60.5 years (IQR 34–76) and 50.7% was male. In total, 9,034 (16.0%) of the ED patients in 2020 were labelled as possible COVID-19 infected, of which 4,777 presented during the FW and 3,102 during the SW (Fig 1).

Fig 1. Overview of patients visiting the ED over 2019 and 2020.

Fig 1

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First wave compared to second wave

During the FW, 18,024 patients presented to the ED compared to 18,282 during the second wave. Compared to 2019, there was a decline of 20,3% during the first wave and a decline of 15.2% during the second wave as shown in Fig 1. When comparing the FW and SW, the number of patients with possible COVID-19 infections was higher during the FW (4,777, 26.5%) compared to the SW (3,102, 17.0%, p<0.001). Furthermore, an increase in trauma related visits (27.4% vs 28.7%, p<0.001) and a decrease in admission rates (AR) during the SW was observed (57.3% vs 56.7%, p<0.001).

Comparison between 2020 and 2019

The dynamics of ED utilization during the two waves and their respective reference periods in 2019 are shown in Table 2. Patients transported to the ED by ambulance increased by 6.6% (p<0.001) and 5.0% (p<0.001) in the FW and SW, respectively. Furthermore, the percentage of patients triaged as high urgency increased by 3.1% in the FW (p<0.001) and 2.1% in the SW (p<0.001). Trauma related visits decreased by 5.2% in the FW (p<0.001) During the SW we observed a decrease of 3.4% in trauma related visits, but this was not statistically significant after Bonferroni correction (p = 0.004).

Table 2. Overview of overall ED utilization during COVID waves and reference periods in 2019.

First wave Reference period first wave  Second wave Reference period second wave  p value first wave vs reference  p value second wave vs reference  p value first vs second wave
Total number of patients, n (%) 18,024 (14.7%) 22,607 (18.4%) 18,282 (14.9%) 21,557 (17.6%) <0.001 <0.001 0.608
Age in years, median (IQR)  62 (39–76) 59 (32–75) 62 (37–76) 60 (33–76) <0.001  <0.001 0.011 
Sex (missing = 23)          
Female, n (%) 8,722 (48.4%) 11,242 (49.7%) 8,867 (48.5%) 10,697 (49.7%) <0.001 <0.001 0.754
Male, n (%) 9,298 (51.6%) 11,363 (50.3%) 9,415 (51.5%) 10,856 (50.3%) <0.001 <0.001 0.866
Possible COVID, n (%) 4,777 (26.5%) 0 (0%)  3,102 (17.0%) 0 (0%)  - - <0.001
Transportation to ED: Ambulance
Self-referral, n (%) 3,801 (21.1%) 3,716 (16.7%) 4,053 (22.2%) 3,745 (17.8%) 0.811 <0.007 <0.044
GP, n (%) 2,924 (16.3%) 3,110 (14.0%) 2,744 (15.0%) 3,035 (14.4%) 0.125 <0.002 0.126
Transportation to ED: Own transport
Self-referral, n (%) 877 (4.9%) 1,402 (6.3%) 966 (5.3%) 1,287 (6.1%) <0.001 <0.001 0.231
GP, n (%) 8,324 (46.2%) 11,192 (50.4%) 8,079 (44.2%) 10,353 (49.1%) <0.001 <0.001 0.301
Other, n (%) 2,081 (11.6%) 4,222 (19.0%) 2,432 (13.3%) 2,675 (12.7%) <0.001 <0.009 <0.001
Urgency of ED visit*        
high urgency, n (%) 3,823 (22.9%) 4,247 (19.8%) 3,817 (22.6%) 4,169 (20.5%) <0.001 <0.001 >0.999
low urgency, n (%) 12,847 (77.1%) 17,125 (80.2%) 13,043 (77.4%) 16,182 (79.5%) <0.001 < 0.001 0.686
Trauma, n (%) (missing = 1) 4,933 (27.4%) 7,375 (32.6%) 5,251 (28.7%) 6,916 (32.1%) <0.001 <0.001 0.004
Median minutes spent in ED, m (IQR) 157 (105–219) 147 (94–208) 154 (99–215) 147 (96–207) <0.001 <0.001 <0.001
Admission after ED visit, n (%) (missing = 15650) 8,990 (57.3%) 10,490 (52.3%) 8,674 (56.7%) 10,146 (46.3%) <0.001 <0.001 0.218
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if the total number of patients does not match the total of inclusions, this is due to missing value

* using the MTS, red or orange triage colour are classified as high urgency (seen by doctor <10 minutes) and triage colour yellow, green or blue are classified as low urgency (1–3 hours before assessment)

**After Bonferroni correction a p-value of 0.003 was considered statistically significant.

IQR = interquartile range

Median ED length of stay was longer during both waves (P<0.001) compared to 2019, yet the median increase in length of stay was 3 minutes longer during the FW compared to the SW (P<0.001) Finally, AR increased by 5.0% (p<0.001) and 10.4% (p<0.001) during the first and second pandemic wave, respectively.

Possible COVID-19 versus non-COVID-19

Table 3 depicts a comparison between possible COVID-19 vs non-COVID-19 visits during the FW and SW. High urgent visits were 18.2% (p<0.001) and 26.4% (p<0.001) more common in patients with possible COVID-19 compared to non-COVID-19 visits during the first and second wave, respectively.

Table 3. Comparison of ED utilization between possible COVID vs non-COVID ED visits during first and second wave.

First wave (n = 18,024) Second wave (n = 18,282) Significance
COVID non-COVID COVID non-COVID first wave COVID vs non-COVID second wave COVID vs non- COVID first vs second wave COVID
Total number of patients (n) 4,777 (26.2%) 13,247 (73.8%) 3,102 (16.9%) 15,180 (83.1%) <0.001 <0.001 <0.001
Age in years, median (IQR)  67 (52–77) 60 (34–75) 69 (55–79) 60 (34–75) <0.001 <0.001 0.508
Sex (missing = 2)      
Female, n (%) 2,236 (46.8%) 6,471 (48.9%) 1,425 (45.9%) 7,435 (49.0%) <0.001 <0.001 <0.001
Male, n (%) 2,540 (53.2%) 6,774 (51.1%) 1,677 (54.1%) 7,743 (51.0%) <0.001 <0.001 <0.001
Transportation to ED: ambulance (missing n = 24)
Self-referral, n (%) 990 (20.8%) 2,841 (21.5%) 584(14.2%) 3,520(85.8%) <0.001 <0.001 <0.001
GP, n (%) 1,279 (26.8%) 1,592 (12.0%) 1,031(38.5%) 1,650(61.2%) <0.001 <0.001 <0.001
Transportation to ED: own transport
Self-referral, n (%) 142 (3.0%) 755 (5.7%) 73 (2.4%) 885 (5.8%) <0.001 <0.001 <0.001
GP, n (%) 2,023 (42.4%) 6,291 (47.5%) 1,091 (35.2%) 6,907 (45.6%) <0.001 <0.001 <0.001
Other, n (%) 336 (7.0%) 1,756 (13.3%) 321 (10.4%) 2,196 (14.5%) <0.001 <0.001 0.400
Urgency of ED visit* (missing = 1339)
    High urgency, n (%) 1,596 (36.3%) 2,227 (18.1%) 1,325 (44.3%) 2,492 (17.9%) <0.001 <0.001 <0.001
    Low urgency, n (%) 2,799 (63.7%) 10,048 (81.6%) 1,664 (55.6%) 11,379 (81.6%) <0.001 <0.001 <0.001
Median time spent in ED, m (IQR) 188 (140–243) 143 (93–207)  197 (147–253) 144 (92–204) <0.001 <0.001 <0.002
Admission after ED visit, n (%) (missing = 3072) 3,085 (74.9%) 5,760 (50.1%) 2,117 (79.9%) 6,466 (51.5%) <0.001 <0.002 0.777
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if the total number of patients does not match the total of inclusions, this is due to missing values

*using the MTS, red or orange triage colour are classified as high urgency (seen by doctor <10 minutes) and triage colour yellow, green or blue are classified as low urgency (1–3 hours before assessment)

**After Bonferroni correction a p-value of 0.004 was considered statistically significant.

IQR = interquartile range

During the first and second wave, the AR for suspected COVID-19 patients was significantly higher at 74.9% and 79.9% compared to 50.1% (p<0.001) and 51.5% (p<0.001) for non-COVID-19 suspected patients.

Discussion

During the first two COVID-19 waves in the Netherlands, ED utilization was significantly decreased, with 20,3% during the FW and 15.3% during the SW. When comparing the two waves with their reference periods in 2019, there was an increase in transportation by ambulance, more patients were triaged as high urgent, ED length of stay was prolonged and there were higher ARs, particularly in COVID-19 suspected patients. Furthermore, a decline in trauma-related ED visits was observed. The increased triage urgency, longer ED length of stay and higher ARs may reflect a higher workload of EDs during the pandemic waves in year 2020.

Previous studies corroborate our results and also report a significant drop in ED visits, increase in high urgent visits and a decline in trauma-related visits during both waves [7–9, 11–16]. Declines were observed in nearly all non-COVID conditions, although specific demographic groups, including children and older patients, showed disproportionate declines [17, 18]. However, to our knowledge, this is one of the first multicenter studies comparing ED utilization during the first and second wave as well as differences between COVID-19 and non-COVID related visits. One single-center study from the United Kingdom assessed ED attendances and acute medical admissions during the pandemic (2020–2021) and the prior year (2019). During the first wave of the pandemic, daily ED attendance fell by 37%, medical admissions by 30% and medical bed occupancy by 27%, but all returned to normal within a year. This normalization of ED utilization was not corroborated by our study.

The reduced ED utilization during the two pandemic waves could be attributed to several possible causes, including pure lockdown effects, fear and uncertainties about a novel infectious disease, and misperceptions about the accessibility of EDs [11]. The lockdowns, which included the closure of non-essential shops, offices and the leisure industry, were associated with lower mobility rates and less traffic or workplace accidents [15].

The decline of ED utilizations was more prominent during the FW than during the SW. This may be explained by a reduction of ‘viral fear’, the increasing knowledge about the virus and repeated encouragements by the government as well as healthcare organizations to seek care when necessary [7]. This observation might also be explained by the rebound effect of delayed healthcare seeking behavior, possibly leading to an exacerbation of the neglected pathological conditions and healthcare damage. Furthermore, the measurements taken by the government were less strict during the SW, which probably resulted in higher mobility rates and increased traffic, explaining the increase of trauma related visits [12]. Finally, during the SW, more elective, non-COVID care was provided. This may have been associated with higher rates of patients who suffered from complications, both postoperatively and medication related.

During the SW, ED utilization still was significantly lower compared to the reference period, possibly resulting from modified community spread of (viral) infections caused by the lockdown, social distancing and other measures during the pandemic [14]. This hypothesis is supported by the highly unusual respiratory syncytial-virus summer outbreak in July-August 2021, shortly after lockdown restrictions in the Netherlands were lifted [19].

The strengths of this study include its multicenter design, extensive number of patients included, mostly prospective labeling of (non-)COVID-suspection and preclusion of selection bias by including all patients presenting to the three EDs. Limitations include the retrospective nature of this study, prospective labeling may have been different between hospitals, the COVID waves continued past the end of our study period and 9,790 patients (17.3%) have been labeled retrospectively because there was no prospective labeling at the very beginning of the pandemic. Furthermore. we collected limited data on patient characteristics, which did not include comorbidities, performed procedures in the ED (e.g. intubation), ICU admission and survival. Finally, some reported differences, including ED length of stay and mode of transportation to ED, may be significantly different not always clinically significant due to the large sample size, even after Bonferroni correction.

Similar FW and SW dynamics were observed in all three EDs. It is often hypothesized that the reduction of ED visits during the pandemic was predominantly determined by a reduction in non-urgent ED visits [20, 21]. Although this may still be true, this study was performed in the Netherlands, a country with a well-developed primary care system and relatively low numbers of self-referrals. As the observed decline was similar to the declines found in studies performed in other healthcare systems, the role of non-urgent ED visits may be less significant than previously thought. As a result, this study adds to the body of literature about ED utilization during the global COVID-19 pandemic. Future studies should focus on characteristics of the subsequent waves of this ongoing pandemic, including those in the era of covid vaccinations. Furthermore, it would be desirable to know more about why patients delay or avoid emergency care during pandemics.

Conclusion

During both COVID-19 waves, ED visits were significantly reduced. ED patients were more often triaged as high urgent, the ED length of stay was longer and ARs were increased compared to the reference period in 2019, reflecting a high burden on ED resources. During the FW, the reduction in ED visits was most pronounced. Here, ARs were also higher and patient were more often triaged as high urgency. These findings stress the need to gain better insight into the motives of patients to delay or avoid emergency care during pandemics, as well as to better prepare EDs for future outbreaks.

Supporting information

S1 File

(DOCX)

Click here for additional data file. (13.4KB, docx)
S1 Dataset

(SAV)

Click here for additional data file. (2.9MB, sav)

Acknowledgments

The study was approved by the medical ethical committee of Zuyderland Medical Center, Heerlen, the Netherlands (METCZ20210031).

Abbreviation list

AR

admission rate

COVID-19

coronavirus disease

ED

emergency department

FW

first wave

GP

general practitioner

IQR

interquartile Range

MTS

Manchester Triage System

PPE

personal protective equipment

SARS-CoV-2

severe acute respiratory syndrome coronavirus 2

SW

Second wave

WHO

World Health Organization

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

The VieCuri Corona Foundation and Regio Noord-Limburg have supported this study by funding part of the Open Access cost associated with publication.

References

Decision Letter 0

Yong-Hong Kuo

8 Aug 2022

PONE-D-22-15700First and Second Wave Dynamics of Emergency Department Utilization during the COVID-19 Pandemic: a retrospective study in 3 hospitals in The NetherlandsPLOS ONE

Dear Dr. van Osch,

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Reviewer #1: Thank the authors very much for this work. Although the COVID-related topic is critically important, I think this work cannot reach the standard of publication.

Major reason:

1. The results and conclusions are not sufficiently innovative. In the past two years, lots of scholars worldwide have already revealed similar trends in ED visits and utilization. This trend is too general.

In this work, the authors studied two specific COVID waves, the conclusions and findings could be more specific and detailed, in order to address some clinical problems, rather than just giving such a general trend.

2. As the authors mentioned in the conclusion, the data closer to the current date would be more attractive and meaningful. The data for 2019 and 2020 are relatively old and could be less guiding.

3. Some statements lack compact logic. Such as Line.198-199, What metric can quantitatively reflect the burden on ED resources?

Minor reason:

The following problems are actually not minor. The authors should be more careful and do the proofreading before submitting.

1. Line.127 & 131, please use a uniform format to cite the figure or table, rather than "Figure 1" and "Fig 1", "table 1" and "Table 1".

2. The tables are significant results, but I can find two "Table 1", and cannot find "Table 3".

Some other problems are also in the figures and tables. This can be summarized that some information in the paragraph was not shown in the figure, but some other important information in the figure and tables was not studied in the paragraph.

I suggest authors can follow their conclusion in this work. Tracking the latest COVID, and making some comparisons among the latest and previous ones.

Reviewer #2: The subject is interesting and topical.

I would advise the author to add data about ICU admission and if it is not possible, to at least discuss it.

I would also ask the author to add to the discussion a comparaison with what has been reported in other EDs/settings.

Reviewer #3: Dear editor,

Thank you for the opportunity to review this manuscript. My recommendation is minor revision:

1- Please mention the weak and strong points of your study

2- The authors do discuss the specifics of the hospital involved in the study regarding comparison of annual admission in the ED with the past COVID-19 period

3- Literature review is so incomplete. Please discuss the following article in the discussion:

Bagi HM, Soleimanpour M, Abdollahi F, Soleimanpour H. Evaluation of clinical outcomes of patients with mild symptoms of coronavirus disease 2019 (COVID-19) discharged from the emergency department. PLoS One. 2021 Oct 21;16(10):e0258697. doi: 10.1371/journal.pone.0258697

4- Discussion should be improved.

5- How did the authors delete the effect of confounding factors from the study outcome?

6- What is the new finding of this study compared to previous ones this field?

7- How did the authors delete the effect of confounding factors from the study outcome?

Reviewer #4: Thanks for the opportunity to review this article written by Osch et al. The authors analysed the data during the FW and SW of COVID-19 lockdowns in three EDs in Netherlands and compared the results with reference points in 2019. The study showed a significant reduction in ED presentations and trauma-related presentations during this time which were shown in other similar studies. They have also reported an increased rate of higher acuity of covid-19 presentations and higher hospital admission.

Although this is an interesting study and reflects on changes in ED presentations during the FW and SW, there are some major issues regarding the statistical reporting and presentation of the results. I suggest the authors revise the manuscript based on the suggestion and re-submit again. In particular, the numbers reported as AR during the FW and SW are not correct and are misrepresented. I have calculated the percentage based on the numbers given in Table 1 and the admission rates between the SW and the reference time point in 2019 were the same at 47%

One of the most critical points is that the authors presented lots of p-values and comparisons in this study. They have to adjust their p-value of 0.05 using Bonferroni’s correction. The study will be elevated if a statistician will be used to assist authors in data analyses, statistical comparisons and data reporting.

The other main issue was the consideration of “chest pain” as one of the symptoms of possible COVID-19 in this study. Chest pain also reported as one of the symptoms, was not a common presentation of possible COVID-19 patients. I wonder if authors are able to see how many presentations were included as “possible COVID presentations” due to chest pain and re-analyse the data?

introduction: paragraph 2:

10,067 died due to COVID-19 during the first wave out of 50,273 infected COVID-19 patients. Would this be a typo? or the mortality rate was around 25% during the first wave (~50K cases / ~ 10K death). This is very high mortality in comparison to other studies reporting between 1 to 10% based on their health care services.

can the authors explain how "patis were able to refuse participation in retrospective studies?" The next paragraph, it is stated that "the ethics committee waived the need for informed consent.” Please explain?

Line 98-101: This is suggested to use the term “re-identifiable data” instead of “pseudonymized”. The last sentence is redundant and can be deleted.

Table1:

Chest pain was not a common COVID-19 presentation during the FW and SW. This was more likely that a patient presented to an ED with a non-covid chest pain rather than covid-19 chest pain. This could potentially skew the data and covid-19 presentation in this study

Line 124: could the author clarify that the results presented in the first line of the result are for the entire 2019 and 2020 or only for the duration of lockdowns in 2020. Please clarify

The first paragraph of the result section is very confusing. As the authors reported ED utilisation during the FW and SW of COID-19, it is highly suggested to only report the data during these two-time points. In addition, it reported 56,719 presentations to the EDs during 2020 (most likely less during the stud period), while 127,060 patients were eligible for inclusion. If the authors included all consecutive presentations to the EDs, why there is a significant discrepancy between ED presentations and eligible patients?

9,034 reported possible covid-19 patients were for the entire 2020 or only the duration of the study (FW and SW?)

Results for FW and SW: should report the actual ED presentations during each lockdown first.

What is the dominator for the calculation of the percentage in FW (26.5%) and SW (17%).

Table 1:

A total of 18,204 presented during the FW, however the exact number of males and females during this period is adding up to 18,020. Please report the missing number or explain the differences between these two sections?

Age: although it is reported that the Age of ED presentations during the FW and SW were statistically different and also in comparison to the 2019 reference point, it is important to note that the difference between the FW and SW is not clinically important.

In addition, it is important that the authors check whether there were any differences between the reference point for FW and SW in 2019. If there is any difference, they have to adjust their data prior to stating there are any statistical differences between FW and SW in 2020. For example, it is better to compare the percentage of changes of the “FW to 2019 reference point” to the “SW to 2019 reference point”. As an example, looking at Table 1, the number of trauma presentations in the reference period first wave is higher than in the second wave reference period. This doesn’t do anything with COVID and could be seasonal changes. The same can be extrapolated from the percentage of admission in 2019 between the two-time points.

The authors stated that “ the admission rate was increased by 5% during the FW and 10% during the SW”. I think this is an oversight when reporting this admission rate (also authors focused on these numbers as a very important finding). ED presentations during the FW were 18,204 and 8,990 patients got admitted (8,990 / 18,204 = 49% and not 57% reported by the authors) and ED presentations during the second wave were 18,282 and 8,674 got admitted (rate of 47%) which is actually the same admission rate in comparison with the 2019 reference point. I urge the authors to check all numbers, percentage and analysis.

Discussion:

It is important to also discuss the higher length of stay in ED for COVID patients in comparison to non-COVID patients

Line 183: what do the authors mean by “This conception is reinforced by a highly unusual respiratory syncytial-virus outbreak in July-August 2021 after loosening of the lockdown measures”?

Figure 1: mark the end of the SW on the X axis

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

Reviewer #4: Yes: A/Prof Hamed Akhlaghi

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Attachment

Submitted filename: Dear editor.doc

Click here for additional data file. (25KB, doc)
PLoS One. 2023 Feb 16;18(2):e0279105. doi: 10.1371/journal.pone.0279105.r002

Author response to Decision Letter 0

21 Oct 2022

(also included as "Cover letter" in the submission)

Dear Editors,

We would like to thank the reviewers for their valuable and generous comments on the manuscirpt.

All the comments were taken into account and have been adjusted.

We believe that the manuscript is now suitable for publication in PlosOne.

On behalf of all the authors,

Frits H.M. van Osch

 

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Adjusted.

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.3. Please include a copy of Table 3 which you refer to in your text on page 8.

Now included

 

Reviewer #1: Thank the authors very much for this work. Although the COVID-related topic is critically important, I think this work cannot reach the standard of publication.

Major reason:

1. The results and conclusions are not sufficiently innovative. In the past two years, lots of scholars worldwide have already revealed similar trends in ED visits and utilization. This trend is too general.

In this work, the authors studied two specific COVID waves, the conclusions and findings could be more specific and detailed, in order to address some clinical problems, rather than just giving such a general trend.

We agree that we are not the first to describe this phenomenon. However, to our knowledge this is one of the first multicenter studies that assess the impact of 2 different waves. Furthermore, this study was performed in the Netherlands, a country with a well-developed primary care system and relatively low numbers of self-referrals. Therefore, we believe this study still is a valuable contribution to the literature. We adjusted the conclusion and made our findings more specific in the new manuscript.

2. As the authors mentioned in the conclusion, the data closer to the current date would be more attractive and meaningful. The data for 2019 and 2020 are relatively old and could be less guiding.

Data for 2019 and 2020 might be relatively old, but this period was the start of the COVID-19 pandemic whit the greatest influence on society wich makes this data the most valuable. Unfortunately, it is not feasible for us to add data for 2021 and 2022 to this analysis.

3. Some statements lack compact logic. Such as Line.198-199, What metric can quantitatively reflect the burden on ED resources?

Burden on ED resources can be reflected by significant increase in high urgent visits (determined by triage following the Manchester Triage System), higher admission rates and longer ED length of stay.

Minor reason:

The following problems are actually not minor. The authors should be more careful and do the proofreading before submitting.

1. Line.127 & 131, please use a uniform format to cite the figure or table, rather than "Figure 1" and "Fig 1", "table 1" and "Table 1".

Adjusted

2. The tables are significant results, but I can find two "Table 1", and cannot find "Table 3".

Table 3 is now added

Some other problems are also in the figures and tables. This can be summarized that some information in the paragraph was not shown in the figure, but some other important information in the figure and tables was not studied in the paragraph.

I suggest authors can follow their conclusion in this work. Tracking the latest COVID, and making some comparisons among the latest and previous ones.

Thank you for this suggestion. In our opionion, the most relevant findings in the figure and tables are explained in the paragraph. We have deliberately chosen not to describe all data in the tables, only the most relevant. We have added a sentence abouut ED length of stay, which is of course very significant to our daily practice.

 

Reviewer #2: The subject is interesting and topical.

I would advise the author to add data about ICU admission and if it is not possible, to at least discuss it.

I would also ask the author to add to the discussion a comparaison with what has been reported in other EDs/settings

Thank you for this suggestion. As much as we would like to add data from intensive care admissions, this is unfortunately not feasible for this study because we do not have this data. We therefore added the lack of these data to the limitations of the study.

Reviewer #3:

My recommendation is minor revision:

1- Please mention the weak and strong points of your study

We added our weak and strong points of the study to the discussion

2- The authors do discuss the specifics of the hospital involved in the study regarding comparison of annual admission in the ED with the past COVID-19 period

We would like to apologize, but we do not fully understand this sentence/suggestion.

3- Literature review is so incomplete. Please discuss the following article in the discussion:

Bagi HM, Soleimanpour M, Abdollahi F, Soleimanpour H. Evaluation of clinical outcomes of patients with mild symptoms of coronavirus disease 2019 (COVID-19) discharged from the emergency department. PLoS One. 2021 Oct 21;16(10):e0258697. doi: 10.1371/journal.pone.0258697

Thank you for this reference. Although we enjoyed reading this study, we believe the scope of this study is totally different from our study, and we do not see how we can refer to this study in our discussion.

4- Discussion should be improved.

We have improved our discussion. For example we have added why this study adds body to the already existing literature and why our study is different from other studies. We also did more literature research to improve our discussion. We also we expanded the study's strengths and weaknesses.

5- How did the authors delete the effect of confounding factors from the study outcome?

The study is of a descriptive nature with multiple comparisons of patient characteristics and ED care parameters between waves, and does not (and cannot) aim to predict an outcome. The ‘outcome’ in this case is in which wave the number originated and whether the exposure sex is equally distributed among the first and second wave. When considering this example, looking at the distribution of sex between the first and second wave, there is no possible confounder that we could have measured, as the distribution of males and females that visit the ED could only be influenced by internal patient factors or factors related to primary care referrals.

6- What is the new finding of this study compared to previous ones this field?

To our knowledge this is one of the first multicenter studies that assess the impact of 2 different waves. Furthermore, this study was performed in the Netherlands, a country with a well-developed primary care system and relatively low numbers of self-referrals. Therefore, we believe this study still is a valuable contribution to the literature

7- How did the authors delete the effect of confounding factors from the study outcome?

See answer question 5.

 

Reviewer #4: Thanks for the opportunity to review this article written by Osch et al. The authors analysed the data during the FW and SW of COVID-19 lockdowns in three EDs in Netherlands and compared the results with reference points in 2019. The study showed a significant reduction in ED presentations and trauma-related presentations during this time which were shown in other similar studies. They have also reported an increased rate of higher acuity of covid-19 presentations and higher hospital admission.

Although this is an interesting study and reflects on changes in ED presentations during the FW and SW, there are some major issues regarding the statistical reporting and presentation of the results. I suggest the authors revise the manuscript based on the suggestion and re-submit again. In particular, the numbers reported as AR during the FW and SW are not correct and are misrepresented. I have calculated the percentage based on the numbers given in Table 1 and the admission rates between the SW and the reference time point in 2019 were the same at 47%

One of the most critical points is that the authors presented lots of p-values and comparisons in this study. They have to adjust their p-value of 0.05 using Bonferroni’s correction. The study will be elevated if a statistician will be used to assist authors in data analyses, statistical comparisons and data reporting.

The other main issue was the consideration of “chest pain” as one of the symptoms of possible COVID-19 in this study. Chest pain also reported as one of the symptoms, was not a common presentation of possible COVID-19 patients. I wonder if authors are able to see how many presentations were included as “possible COVID presentations” due to chest pain and re-analyse the data?

Thanks a lot for your suggestions. We adjusted our p-value using the Bonferroni’s correction and adjusted our manuscript. The Bonferroni’s correction is also stated underneath table 2 and table 3.

We are not able to remove ‘chest pain’ as one of the symptoms of possible covid-19 infections, this is due to the fact that most of the data is labeled prospectively. One of the criteria in that time, to mark a patients as a suspected covid-19 infection, included chest pain. We can not see in our data based on which criteria someone was labeled as a suspected covid-19 infection.

introduction: paragraph 2:

10,067 died due to COVID-19 during the first wave out of 50,273 infected COVID-19 patients. Would this be a typo? or the mortality rate was around 25% during the first wave (~50K cases / ~ 10K death). This is very high mortality in comparison to other studies reporting between 1 to 10% based on their health care services.

We have checked these numbers and they are correct. We can explain the difference due to our restrictive testing policy during the first because of a lack of testing recourses (with other words: patients who were tested predominantly concerned patients who were critically ill or admitted). We have adjusted the text to explain this situation.

can the authors explain how "patis were able to refuse participation in retrospective studies?" The next paragraph, it is stated that "the ethics committee waived the need for informed consent.” Please explain?

We explained this suggestion in our manuscript.

Line 98-101: This is suggested to use the term “re-identifiable data” instead of “pseudonymized”. The last sentence is redundant and can be deleted.

Adjusted

Table1:

Chest pain was not a common COVID-19 presentation during the FW and SW. This was more likely that a patient presented to an ED with a non-covid chest pain rather than covid-19 chest pain. This could potentially skew the data and covid-19 presentation in this study

Please see the comment we made on your suggestion earlier in this rebuttal letter.

Line 124: could the author clarify that the results presented in the first line of the result are for the entire 2019 and 2020 or only for the duration of lockdowns in 2020. Please clarify

Adjusted

The first paragraph of the result section is very confusing. As the authors reported ED utilisation during the FW and SW of COID-19, it is highly suggested to only report the data during these two-time points. In addition, it reported 56,719 presentations to the EDs during 2020 (most likely less during the stud period), while 127,060 patients were eligible for inclusion. If the authors included all consecutive presentations to the EDs, why there is a significant discrepancy between ED presentations and eligible patients?

9,034 reported possible covid-19 patients were for the entire 2020 or only the duration of the study (FW and SW?)

The total of 127,060 patients eligible for inclusion are the patients visited in 2019 and 2020. In 2019 there where 65,938 visits and in 2020 56,719 visits. We hope this is more clear in the first paragraph in the new manuscript.

The total of 9034 possible covid-19 patients were for the entire 2020, of of which 4,777 presented during the FW and 3,102 during the SW. That means 1155 possible covid-19 patients presented to the ED in 2020 outside the intended study period (FW + SW)

Results for FW and SW: should report the actual ED presentations during each lockdown first.

In the new manuscript we implementend this suggestion.

What is the dominator for the calculation of the percentage in FW (26.5%) and SW (17%).

This is from the total amount of patients visiting the ED

Table 1:

A total of 18,204 presented during the FW, however the exact number of males and females during this period is adding up to 18,020. Please report the missing number or explain the differences between these two sections?

This was a mistake in the manuscript and is now adjusted. As stated under table 2 and 3, if the total number of patients does not match the total of inclusions, this is due to missing value . We have added the number of missings in the tables.

Age: although it is reported that the Age of ED presentations during the FW and SW were statistically different and also in comparison to the 2019 reference point, it is important to note that the difference between the FW and SW is not clinically important.

In addition, it is important that the authors check whether there were any differences between the reference point for FW and SW in 2019. If there is any difference, they have to adjust their data prior to stating there are any statistical differences between FW and SW in 2020. For example, it is better to compare the percentage of changes of the “FW to 2019 reference point” to the “SW to 2019 reference point”. As an example, looking at Table 1, the number of trauma presentations in the reference period first wave is higher than in the second wave reference period. This doesn’t do anything with COVID and could be seasonal changes. The same can be extrapolated from the percentage of admission in 2019 between the two-time points.

Thank you for this suggestion, however we believe there are no seasonal changes ecause we compared the study period with the exact same period as a reference.

The authors stated that “ the admission rate was increased by 5% during the FW and 10% during the SW”. I think this is an oversight when reporting this admission rate (also authors focused on these numbers as a very important finding). ED presentations during the FW were 18,204 and 8,990 patients got admitted (8,990 / 18,204 = 49% and not 57% reported by the authors) and ED presentations during the second wave were 18,282 and 8,674 got admitted (rate of 47%) which is actually the same admission rate in comparison with the 2019 reference point. I urge the authors to check all numbers, percentage and analysis.

We added missing values to table 2 and 3.

Discussion:

It is important to also discuss the higher length of stay in ED for COVID patients in comparison to non-COVID patients

Length of stay in the ED for COVID-19 patients is added to the discussion

Line 183: what do the authors mean by “This conception is reinforced by a highly unusual respiratory syncytial-virus outbreak in July-August 2021 after loosening of the lockdown measures”?

We agree that this sentence was not very clear. We have rephrased it, so it hopefully makes more sense now.

Figure 1: mark the end of the SW on the X axis

We did not mark the end of the SW on X-axis on purpose because officially the end of 2020 is not the end of the second wave. It is just the end of our study period.

Decision Letter 1

Yong-Hong Kuo

7 Nov 2022

PONE-D-22-15700R1First and Second Wave Dynamics of Emergency Department Utilization during the COVID-19 Pandemic: a retrospective study in 3 hospitals in The NetherlandsPLOS ONE

Dear Dr. van Osch,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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We look forward to receiving your revised manuscript.

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Yong-Hong Kuo

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

All the referees are satisfied with the revision. However, there are some minor suggestions which the authors shall incorporate into the revision.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: (No Response)

Reviewer #2: (No Response)

Reviewer #3: All comments have been addressed

Reviewer #4: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: (No Response)

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: (No Response)

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: (No Response)

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #1: (No Response)

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank the authors for responses.

Further comments:

The current Conclusion part is relatively casual.

Please enhance the Conclusion part, and summarize more details of the characteristics of both FW and SW, respectively.

Reviewer #2: Even if the authors did not provide data according to ICU admission, at least they included it in the limits sections.

Reviewer #3: Thank you so much for your response. The respected authors can discuss and cite the following article in the discussion line 161 (Previous study....,)

Bagi HM, Soleimanpour M, Abdollahi F, Soleimanpour H. Evaluation of clinical outcomes of patients with mild symptoms of coronavirus disease 2019 (COVID-19) discharged from the emergency department. PLoS One. 2021 Oct 21;16(10):e0258697. doi: 10.1371/journal.pone.0258697

Reviewer #4: I have found the authors' responses adequate and can concur that the study has some merits to get published.

I would like to thank the authors for this work and the opportunity to review their article.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

Reviewer #4: Yes: A/Prof Hamed Akhlaghi

**********

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PLoS One. 2023 Feb 16;18(2):e0279105. doi: 10.1371/journal.pone.0279105.r004

Author response to Decision Letter 1

25 Nov 2022

See included cover letter:

Reviewer #1: Thank the authors for responses.

Further comments:

The current Conclusion part is relatively casual.

Please enhance the Conclusion part, and summarize more details of the characteristics of both FW and SW, respectively.

Thank you for the suggestion. The conclusion (as well as the abstract) was amended in the new version.

Reviewer #2: Even if the authors did not provide data according to ICU admission, at least they included it in the limits sections.

Reviewer #3: Thank you so much for your response. The respected authors can discuss and cite the following article in the discussion line 161 (Previous study....,)

Bagi HM, Soleimanpour M, Abdollahi F, Soleimanpour H. Evaluation of clinical outcomes of patients with mild symptoms of coronavirus disease 2019 (COVID-19) discharged from the emergency department. PLoS One. 2021 Oct 21;16(10):e0258697. doi: 10.1371/journal.pone.0258697

This reference has been added to the discussion section.

Reviewer #4: I have found the authors' responses adequate and can concur that the study has some merits to get published.

I would like to thank the authors for this work and the opportunity to review their article.

Decision Letter 2

Yong-Hong Kuo

1 Dec 2022

First and Second Wave Dynamics of Emergency Department Utilization during the COVID-19 Pandemic: a retrospective study in 3 hospitals in The Netherlands

PONE-D-22-15700R2

Dear Dr. van Osch,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Acceptance letter

Yong-Hong Kuo

23 Jan 2023

PONE-D-22-15700R2

First and second wave dynamics of emergency department utilization during the COVID-19 pandemic: a retrospective study in 3 hospitals in The Netherlands

Dear Dr. van Osch:

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on behalf of

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