Impact of the COVID-19 pandemic and its associated public health and social measures on emergency department utilization in Germany between March 2017 and June 2021

doi:10.21203/rs.3.rs-1630734/v1

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Research Article

Impact of the COVID-19 pandemic and its associated public health and social measures on emergency department utilization in Germany between March 2017 and June 2021

https://doi.org/10.21203/rs.3.rs-1630734/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 02 May, 2023

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Background: During the COVID-19 pandemic and associated public health and social measures, decreasing patient numbers have been described in various healthcare settings in Germany, including emergency care. This could be explained by changes in disease burden, e.g. due to contact restrictions, but could also be a result of changes in utilization behaviour of the population. To better understand those dynamics, we analysed routine data from emergency departments to quantify changes in consultation numbers, age distribution, disease acuity and day and hour of the day during different phases of the COVID-19 pandemic.

Methods: We used interrupted time series analyses to estimate relative changes for consultation numbers of 20 emergency departments spread throughout Germany. For the study period of 06-03-2017 to 13-06-2021 four different phases of the COVID-19 pandemic were defined as interruption points.

Results: The most pronounced decreases were visible in the first and second wave of the pandemic, with changes of -30.0% (95%CI: -32.2%; -27.7%) and -25.7% (95%CI: -27.4%; -23.9%) for overall consultations, respectively. The decrease was even stronger for the age group of 0-19 years, with -39.4% in the first and -35.0% in the second wave. Regarding acuity levels, consultations assessed as urgent, standard and non-urgent showed the largest decrease, while the most severe cases showed the smallest decrease.

Conclusions: The number of emergency department consultations decreased rapidly during the COVID-19 pandemic, without extensive variation in the distribution of patient characteristics. Smallest changes were observed for the most severe consultations and older age groups, which is especially reassuring regarding concerns of possible long-term complications due to patients avoiding urgent emergency care during the pandemic.

syndromic surveillance

emergency department

COVID-19 pandemic

routine data

interrupted time series analyses

public health and social measures

The COVID-19 pandemic and associated public health and social measures have influenced population health and various aspects of healthcare in Germany [1–2]. Decreasing patient and case numbers have been observed in different settings of acute care, across all age groups, levels of acuity, and chief complaints. Among the most severe diagnoses, especially the number of patients presenting with cardiovascular emergencies and stroke have decreased during the first wave of the COVID-19 pandemic [1–3]. Following the first introduction of nation-wide public health measures in 2020, emergency department consultations in Germany decreased by about 40% [1, 4]. Similar trends were observed in other countries [5–7]. Those observed changes in the number of emergency department consultations might have been due to actual changes in disease burden, e.g. with fewer consultations for traumas (injuries, accidents) due to reduced mobility and cancellation of mass gatherings [1]. On the other hand, they could have been the result of changes in utilization behavior, as e.g. patients avoided seeking healthcare concerned of getting infected with COVID-19 [8, 9]. Especially with the reduced consultations for acute events like myocardial infarction and stroke, concerns arose that patients would forego essential emergency treatment or lack the access to healthcare due to lockdown measures. In turn, this could lead to a later “rebound” effect of long-term complications and a higher number of deaths outside the healthcare system [1, 10, 11] and could call for increased risk communication and public health messaging, to raise awareness of the importance of emergency care, even in pandemic situations.

Syndromic surveillance can contribute to the understanding of this rather indirect impact of the COVID-19 pandemic and associated measures on public health by monitoring the population’s healthcare seeking behavior [10]. This monitoring can be based on the analysis of routinely collected data from emergency departments (EDs), without creating additional burden for the staff on site. The Robert Koch Institute (RKI) has been developing an emergency department surveillance system using data from about 35 emergency departments spread over 11 federal states in Germany. In reaction to the COVID-19 pandemic and its possible influences on healthcare seeking behavior, and to inform the RKI and other German public health authorities, a situation report has been implemented starting from June 2020, displaying the overall emergency department consultations, stratified by age group, disease acuity, and certain presenting complaints [4]. The report is published on the RKI website on a weekly basis [12] and has been part of RKI’s COVID-19 situation reports [13]. The report gives a descriptive overview of the general situation in participating emergency departments. However, a deeper understanding of the utilization behavior can only be achieved by further analyses of patient dynamics during the pandemic.

This study therefore aims to assess trends in the number of overall emergency department consultations, their age distribution and acuity, and timing of consultation (including day of the week and time of day) throughout different phases of the pandemic.

Study setting and variables

We conducted a time series analyses based on routine data from emergency departments, which either participated in the ESEG project [14] or are part of the AKTIN emergency department data registry [15, 16], whose data are sent to RKI in daily data exports. For both projects, inclusion of the EDs is based on voluntary participation. Each observation represents an electronic health record of a single emergency department consultation, multiple consultations of a specific patient cannot be identified in our dataset. The patient-level data is anonymized and pre-processed according to a generic data model (NotaufnahmeKernDatensatz, NoKeDa), which ensures usability of the data across different ED information systems and reporting standards [17]. For the present study, the following variables were included for analysis: age in groups of 0–19 years, 20–39 years, 40–59 years, 60–79 years, 80 + years (originally collected as: 0–4 years in 1-year age groups, 5–79 in 5-year age groups, 80 + years), acuity level (1 = immediate, 2 = very urgent, 3 = urgent, 4 = standard, 5 = non urgent) according to primary assessment stemming either from the Manchester Triage System [18] or the Emergency Severity Index [19], as well as weekday and hour of each consultation.

Study population

As reference data we included data on three years prior to the pandemic starting with 06-03-2017. Data for the pandemic could be included until 13-06-2021 which marked the end of the ESEG project. We included data from emergency departments which provided at least one consultation recorded for each day of the study period. Every consultation recorded within this period fulfilling a minimal requirement for data transfer was included, i.e. information on age, day and hour of consultation provided.

Statistical Analyses

Descriptive analyses included the visualisation of the overall number of consultations over time, as well as their distribution of age, acuity levels, and consultation timing.

To quantify the changes in patient dynamics during the COVID-19 pandemic, we conducted interrupted time series analyses using negative binomial regression (Eq. 1).

Equation 1 – Negative binomial regression model used to estimate relative change in number of consultations

From the exponential of the regression coefficients ß_i for the pandemic variables we derived the relative differences between the reference pre-pandemic phase and the respective pandemic phases. The interruptions over time were defined by the pandemic phases, as proposed by Tolksdorf et al. [20]:

First COVID-19 wave between weeks 10-2020 and 20-2020
Summer plateau between weeks 21-2020 and 39-2020
Second COVID-19 wave between weeks 40-2020 and 08-2021
Third COVID-19 wave between weeks 09-2021 and 23-2021

The dependent variable was the number of overall weekly consultations, the interruptions (independent variable) were defined as the pre-pandemic period (start of study period until start of wave 1) and the respective pandemic phases. For the categorical variables age, acuity level, weekday and hour of consultation, stratified regression analyses were performed for each value of the respective variable. Using the pre-pandemic period as the reference category in all regression models, we herewith obtain the relative change for each category, irrespective of trends or changes in the other categories.

To account for the potentially not immediate change in emergency department utilisation at the start of the pandemic phases, we investigated the model fit of three different models with the Akaike Information Criterion (AIC): fitting the interruption with A) a two-week delay, B) a one-week, and C) no delay from the starting point of each phase. The model using a two-week delay period from the start of each pandemic phase as interruption points showed the best fit (Supplementary Fig. 1). We additionally modelled all analyses including time as a linear variable up to the first interruption, and looked at its effect size and statistical significance to decide, whether or not to include time in the final models. Only small changes (between 0.04% and − 0.01%) could be observed across the stratified analyses (Supplementary Table 1), indicating that consultation numbers did not show major trends before the start of the COVID-19 pandemic. We therefore decided not to include time in the final model.

All analyses were performed using R version 4.1.2 [21] and the packages tidyverse [22], MASS [23], finalfit [24], xlsx [25], Table1 [26], and ggpubr [27].

Table 1

Relative change in % and 95% confidence interval for all emergency department consultations, consultations by age group, acuity level, weekday, and hour of day, comparing every pandemic phase with the pre-pandemic reference period
	% change [95% CI]
	Pre-Pandemic	Wave 1	Summerbreak	Wave 2	Wave 3
All attendances
	Reference	-29.98% [-32.21% ; -27.69%]	-8.30% [-10.57% ; -5.97%]	-25.66% [-27.38% ; -23.89%]	-14.49% [-17.00% ; -11.91%]
Age group
0–19	Reference	-39.37% [-43.83% ; -34.56%]	-7.74% [-13.04% ; -2.13%]	-35.01% [-38.53% ; -31.29%]	-16.01% [-21.71% ; -9.89%]
20–39	Reference	-32.86% [-35.50% ; -30.10%]	-11.56% [-14.26% ; -8.78%]	-31.57% [-33.55% ; -29.54%]	-18.95% [-21.89% ; -15.90%]
40–59	Reference	-26.56% [-28.93% ; -24.11%]	-7.30% [-9.60% ; -4.93%]	-24.47% [-26.25% ; -22.64%]	-13.29% [-15.86% ; -10.64%]
60–79	Reference	-23.95% [-26.37% ; -21.45%]	-5.00% [-7.33% ; -2.60%]	-18.72% [-20.61% ; -16.79%]	-9.80% [-12.43% ; -7.09%]
80+	Reference	-27.71% [-30.15% ; -25.18%]	-10.15% [-12.49% ; -7.75%]	-17.43% [-19.46% ; -15.35%]	-14.39% [-17.04% ; -11.66%]
Severity level
1 (immediate)	Reference	-24.30% [-29.39% ; -18.83%]	-3.82% [-8.60% ; 1.20%]	-11.05% [-15.27% ; -6.62%]	-1.48% [-7.23% ; 4.63%]
2 (very urgent)	Reference	-25.02% [-27.95% ; -21.98%]	-6.42% [-9.22% ; -3.53%]	-13.52% [-15.96% ; -11.00%]	-8.16% [-11.42% ; -4.77%]
3 (urgent)	Reference	-26.54% [-29.06% ; -23.94%]	-3.96% [-6.51% ; -1.34%]	-18.52% [-20.56% ; -16.43%]	-7.73% [-10.63% ; -4.72%]
4 (standard)	Reference	-37.23% [-40.06% ; -34.26%]	-11.98% [-15.07% ; -8.77%]	-35.49% [-37.63% ; -33.28%]	-20.96% [-24.26% ; -17.53%]
5 (non urgent)	Reference	-31.93% [-37.69% ; -25.64%]	-3.17% [-9.51% ; 3.61%]	-29.21% [-33.62% ; -24.50%]	-17.86% [-24.25% ; -10.92%]
Missing	Reference	-8.28% [-13.81% ; -2.40%]	-18.60% [-22.47% ; -14.53%]	-27.06% [-30.34% ; -23.63%]	-25.75% [-29.70% ; -21.59%]
Weekday
Monday	Reference	-28.93% [-31.77% ; -25.96%]	-6.47% [-9.35% ; -3.50%]	-22.72% [-24.97% ; -20.39%]	-13.11% [-16.29% ; -9.81%]
Tuesday	Reference	-28.27% [-30.94% ; -25.50%]	-5.85% [-8.53% ; -3.09%]	-22.25% [-24.35% ; -20.08%]	-12.02% [-15.01% ; -8.93%]
Wednesday	Reference	-28.79% [-31.47% ; -26.00%]	-7.56% [-10.24% ; -4.81%]	-24.08% [-26.16% ; -21.93%]	-12.92% [-15.92% ; -9.82%]
Thursday	Reference	-28.88% [-31.80% ; -25.84%]	-8.24% [-11.15% ; -5.24%]	-24.93% [-27.18% ; -22.60%]	-11.61% [-14.93% ; -8.16%]
Friday	Reference	-29.93% [-33.07% ; -26.65%]	-10.37% [-13.47% ; -7.16%]	-29.43% [-31.74% ; -27.04%]	-16.96% [-20.37% ; -13.41%]
Saturday	Reference	-34.04% [-37.12% ; -30.82%]	-11.90% [-15.07% ; -8.61%]	-33.35% [-35.63% ; -30.99%]	-20.14% [-23.56% ; -16.57%]
Sunday	Reference	-31.08% [-33.85% ; -28.20%]	-7.83% [-10.68% ; -4.90%]	-23.29% [-25.53% ; -20.98%]	-14.90% [-18.02% ; -11.65%]
Hour
0	Reference	-32.26% [-36.70% ; -27.50%]	-11.00% [-15.38% ; -6.40%]	-34.45% [-37.62% ; -31.11%]	-26.99% [-31.38% ; -22.33%]
1	Reference	-33.65% [-38.47% ; -28.45%]	-12.69% [-17.44% ; -7.67%]	-33.59% [-37.14% ; -29.85%]	-26.90% [-31.74% ; -21.71%]
2	Reference	-33.53% [-38.26% ; -28.43%]	-14.30% [-18.83% ; -9.53%]	-31.61% [-35.16% ; -27.86%]	-27.48% [-32.17% ; -22.46%]
3	Reference	-30.25% [-35.20% ; -24.93%]	-10.48% [-15.16% ; -5.55%]	-30.52% [-34.14% ; -26.70%]	-23.62% [-28.52% ; -18.37%]
4	Reference	-27.22% [-32.48% ; -21.55%]	-10.43% [-15.24% ; -5.34%]	-26.16% [-30.06% ; -22.04%]	-20.49% [-25.70% ; -14.91%]
5	Reference	-19.90% [-26.26% ; -12.98%]	5.07% [-1.18% ; 11.72%]	-21.68% [-26.28% ; -16.79%]	6.62% [-0.85% ; 14.65%]
6	Reference	-10.86% [-18.10% ; -2.97%]	14.54% [7.44% ; 22.10%]	-9.93% [-15.32% ; -4.20%]	45.17% [34.81% ; 56.33%]
7	Reference	-16.13% [-22.14% ; -9.65%]	14.03% [7.80% ; 20.62%]	-0.90% [-6.04% ; 4.53%]	30.57% [22.24% ; 39.46%]
8	Reference	-27.39% [-31.18% ; -23.39%]	-3.44% [-7.26% ; 0.54%]	-16.53% [-19.68% ; -13.26%]	-1.71% [-6.31% ; 3.12%]
9	Reference	-31.98% [-34.65% ; -29.21%]	-7.25% [-9.96% ; -4.45%]	-21.52% [-23.72% ; -19.25%]	-11.04% [-14.15% ; -7.83%]
10	Reference	-30.23% [-33.02% ; -27.32%]	-10.63% [-13.34% ; -7.84%]	-20.76% [-23.04% ; -18.41%]	-14.24% [-17.34% ; -11.03%]
11	Reference	-31.52% [-34.12% ; -28.83%]	-10.01% [-12.57% ; -7.37%]	-20.78% [-22.93% ; -18.57%]	-13.70% [-16.62% ; -10.67%]
12	Reference	-28.67% [-31.32% ; -25.92%]	-10.48% [-12.98% ; -7.89%]	-21.66% [-23.76% ; -19.51%]	-14.21% [-17.08% ; -11.24%]
13	Reference	-28.69% [-31.40% ; -25.88%]	-7.85% [-10.48% ; -5.15%]	-20.98% [-23.14% ; -18.76%]	-15.79% [-18.68% ; -12.81%]
14	Reference	-28.39% [-31.20% ; -25.46%]	-7.03% [-9.77% ; -4.20%]	-21.69% [-23.91% ; -19.40%]	-14.19% [-17.22% ; -11.04%]
15	Reference	-28.82% [-31.53% ; -25.99%]	-8.38% [-10.99% ; -5.68%]	-22.79% [-24.92% ; -20.61%]	-12.34% [-15.33% ; -9.25%]
16	Reference	-28.95% [-31.55% ; -26.25%]	-8.84% [-11.33% ; -6.29%]	-22.34% [-24.39% ; -20.25%]	-13.60% [-16.42% ; -10.69%]
17	Reference	-29.57% [-32.39% ; -26.64%]	-9.10% [-11.83% ; -6.29%]	-25.73% [-27.89% ; -23.52%]	-17.22% [-20.20% ; -14.12%]
18	Reference	-31.73% [-34.75% ; -28.57%]	-10.16% [-13.15% ; -7.06%]	-30.69% [-32.93% ; -28.38%]	-17.47% [-20.76% ; -14.04%]
19	Reference	-32.29% [-35.35% ; -29.08%]	-9.22% [-12.31% ; -6.02%]	-33.62% [-35.83% ; -31.34%]	-17.99% [-21.35% ; -14.50%]
20	Reference	-32.93% [-36.52% ; -29.12%]	-8.95% [-12.66% ; -5.08%]	-37.74% [-40.21% ; -35.17%]	-22.06% [-25.87% ; -18.05%]
21	Reference	-31.90% [-36.36% ; -27.12%]	-9.28% [-13.84% ; -4.47%]	-40.02% [-42.94% ; -36.94%]	-24.66% [-29.20% ; -19.82%]
22	Reference	-34.68% [-38.96% ; -30.09%]	-12.86% [-17.23% ; -8.27%]	-40.59% [-43.48% ; -37.55%]	-27.66% [-32.02% ; -23.02%]
23	Reference	-36.34% [-40.69% ; -31.67%]	-13.34% [-17.81% ; -8.62%]	-39.93% [-42.97% ; -36.74%]	-27.75% [-32.25% ; -22.95%]

Between 06-03-2017 and 13-06-2021, a total of 35 emergency departments transferred data from a total of 3,991,480 consultations to the RKI. Of these, 20 emergency departments fulfilled the inclusion criteria, leading to a final study sample of 3,143,273 consultations. The included emergency departments spread throughout 9 German federal states and cover all three levels of care according to Federal Joint Committee [28] (comprehensive care: 13 EDs, extended care: 5 EDs, basic care: 1 ED). Average consultation numbers per emergency department range from about 200 up to 1,600 per week. For 5.6% of consultations (n = 176,747) primary assessment of acuity was missing, i.e. it was not carried out or not recorded.

Overall consultations

Compared to the pre-pandemic period, a 30.0% (95%CI: -32.2%; -27.7%) decrease in emergency department consultations was detected during the first wave. Consultation numbers increased again during the summer plateau, however not reaching those recorded the year before, staying at -8.3% [95%CI: -10.6%; -6%] compared to the reference period. During the second pandemic wave, consultations dropped again, with a relative change of -25.7% (95%CI: -27.4%; -23.9%) compared to the pre-pandemic period, followed by an increase during the third wave, with a relative change of -14.5% [95%CI: -17.0%; -11.9%] compared to the pre-pandemic period (Fig. 1, Supplementary Table 2, Supplementary Fig. 4).

Age distribution

Before the beginning of the first wave of the COVID-19 pandemic (week 10-2020), 18.5% of all consultations were younger than 20 years and 16.0% over 80. Similar distributions were visible in the first and third wave. The number of consultations increased among the older age groups during the summer plateau, where the 0-19-year-olds made up between 16.5% and 17.2% of consultations while 60-79-year-olds increased to 23.4% and 24.0% (Fig. 2, Supplementary Table 2).

The relative changes in the number of consultations for each age group showed similar trends as compared to the overall consultations. The decrease was most pronounced among young people (0–19 years), especially during the first and second waves (-39.4% and − 35.0%, respectively). The smallest decrease in consultations was seen among those aged 60–79, with decreases between − 24% and − 5% throughout (Table 1, Fig. 4).

Acuity level

Before the pandemic, most consultations were assessed as 3-urgent (37.2%) or 4-standard (40.5%) level of acuity. Those two levels also had the highest numbers in all pandemic phases. The category with the fewest observations was 1-immediate, with 1.1–1.4% of consultations. Acuity levels 5-non-urgent accounted for around 4% of consultations. (Fig. 3, Supplementary Table 2)

A reduction of cases compared to the pre-pandemic time was especially visible for the acuity levels 3-urgent, 4-standard and 5-non-urgent, during the first wave of COVID-19. The most severe cases (acuity level 1) reduced by -24.3% [95%CI: -29.4%; -18.8%] in the first and − 11.1% [95%CI: -15.3%; -6.6%] in the second wave, but were at a similar level as in the reference period during the summer plateau (-3.8% [95%CI: -8.6%; 1.2%]) and the third wave (-1.5% [95%CI: -7.2%; 4.6%]) (Table 1, Fig. 5).

Weekday and hour of consultation

While consultations on Fridays and Saturdays were slightly fewer during the summer plateau, they were slightly increased for Tuesdays and Wednesdays during the second and third wave. Overall however, consultations were evenly distributed with 12.3–15.8% across all days of the week prior to the COVID-19 pandemic and in each pandemic phase. Prior to the pandemic, just as within all pandemic phases, most consultations occurred between 9 am and 1 pm, the fewest patients were recorded between 3 am and 5 am (Supplementary Table 2).

Based on the results from the interrupted time series analyses, consultations decreased by about − 30% for all days of the week in the first and second waves of the pandemic. Also, for the time of consultation, a reduction of about − 30% on average was recorded during the first COVID-19 wave (Table 1, Supplementary Fig. 5). As the only exception, the numbers dropped by -10.9% and − 16.1% at 6 am and 7 am, while in the second and third wave of the pandemic the number of consultations increased during those hours up to 14.5% and 14.0% (second wave) and up to 45.2% and 30.6% (third wave), compared to pre-pandemic times (Supplementary Fig. 6).

Key results:

The COVID-19 pandemic and the associated public health and social measures have impacted emergency department consultations in Germany. During the first wave of the COVID-19 pandemic a substantial and rapid decrease of emergency department consultations was observed, this change presented across all age groups and all acuity levels, weekdays, and hours of consultation. Similar trends were observed in the second wave. However, the decrease was much smaller during the summer plateau and the third wave. The drastic decrease of consultations at the start of the public health and social measures in Germany beginning in week 10-2020 is in accordance with studies and reports from other countries like the UK and the US [7, 29, 30]. In our analysis, the COVID-19 pandemic and associated measures had the most impact on moderately severe and non-urgent cases (acuity levels 3, 4, and 5). This might indicate that less urgent emergency department consultations were avoided. Similar findings were also described in a study from the UK, analysing the change in consultation counts during the first pandemic wave [6]. Generally, the number of most severe consultations were similar to the pre-pandemic phase, except for a decrease in the first wave, which is disconcerting and might further underpin the fear of unmet needs for acute events in the emergency department during the COVID-19 pandemic. In turn the older age groups (60–79 years, 80 + years) showed the smallest decrease in the number of consultations, which could indicate that those more vulnerable groups did not change their utilisation behaviour or were not lacking access due to public health and social measures. Meanwhile, the great and rapid decrease in the youngest age group could point towards parents not taking their children into emergency departments, possibly being concerned of an infection with SARS-CoV-2 [31]. In addition, the reduction of consultations in that age group might be related to a reduction of trauma-related injuries due to lockdown measures, suspension of sports activities and school closures [32]. Studies conducted in the US and UK during the first pandemic wave showed similar results, with the biggest reduction in consultations described for the age groups 0–19 [7], 5–14 [6], and children younger than 14 [30], and the smallest decrease in older age groups. The changes described for the timing of the consultations (i.e. weekday and time of day) are in accordance with the overall decrease in consultation numbers of about − 30%. This is contrary to findings from the UK, where the biggest reductions were reported for Monday through Wednesday [6]. This however may also be due to differences in COVID-19 measures, in the healthcare structure and access to emergency departments in these two countries.

Strengths and Limitations:

The present study is using interrupted time series analyses to quantify the impact of public health and social measures associated with the COVID-19 pandemic. This gives additional insights into changes in emergency department utilisation as compared to descriptive analyses previously done [4]. We included 20 emergency departments across 9 states in Germany of different sizes and levels of care. However, the sample might not be representative of all emergency departments in Germany. As with all routinely collected secondary data, the quality of the data is dependent on documentation practice in the respective emergency department, which might for example lead to missing values in certain variables. While this can be challenging in many use cases of emergency department surveillance, it is assumed to be a minor problem for the present analyses. The only used variable used in the present study that is affected by this is acuity level, where about 5% of all consultations either had no acuity level documented or were not assessed in triage as they had immediate physician contact.

The pandemic phases used to determine the interruption points and defined by Tolksdorf et al. [20] are based on different parameters like notified cases of COVID-19, number of tests, hospitalisation incidence, and intensive care capacities. The public health and social measures in Germany were largely also driven by those parameters, but were, apart from the first “lockdown” in March 2020, not uniform across different German states. This might affect the interpretability of the present results concerning the impact of public health and social measures. Additionally, there is no substantial evidence to back up assumptions about delay periods between the introduction of specific public health and social measures and healthcare utilisation. In the present study, the two-week delay period was therefore chosen based on the best model fit. The pandemic phases include different seasons. However, we were able to include data since March 2017, allowing us to use three pre-pandemic years as a reference period, where there was no substantial seasonal variation visible.

Analysing data from a syndromic surveillance system using emergency department data can contribute to the wider understanding of the impact of the COVID-19 pandemic and associated public health and social measures. A first step towards this aim is to analyse changes in consultation numbers and the distribution of patient characteristics. The presented results show that while the overall number of consultations decreased during each phase of the COVID-19 pandemic, the distribution of patient characteristics did not vary extensively. It is especially reassuring that patient groups assumed to be more vulnerable (older age groups) and those presenting with more severe complaints showed the smallest relative decrease in each pandemic phase. To finally address the concerns that the pandemic and its associated measures led to a delayed or non-appearance of patients with specific, more acute health events (e g. myocardial infarction or stroke), further analyses of specifically those cases are needed. Better understanding of the population’s reasons for emergency care avoidance could in the future help target public health messaging and the development of strategies to increase confidence in the safety of healthcare institutions despite pandemic situations.

AIC Akaike information criterion

AKTIN Aktionsbündnis zur Verbesserung der Kommunikations- und InformationsTechnik in der Intensiv- und Notfallmedizin (AKTIN emergency department data registry)

CI Confidence Interval

COVID-19 Coronavirus Disease 2019

ED emergency department

ESEG Erkennung und Sicherung epidemischer Gefahrenlagen

NoKeDa NotaufnahmeKernDatenmodell

RKI Robert Koch Institute

SARS-CoV-2 severe acute respiratory syndrome coronavirus 2

UK United Kingdom

US United States

Ethics approval and consent to participate

The use of routine emergency department data according to the NoKeDa data model for surveillance and research purposes was assessed and approved by RKI’s data protection officer. For data from the ESEG-project, an ethics vote was not necessary as disclosed by the ethics committee of the physician’s chamber Hessen, due to the anonymized nature of the data. The AKTIN emergency department data registry received a positive ethics vote from the Otto von Guericke University Magdeburg (160/15). Additionally, the use of data from emergency departments from AKTIN for syndromic surveillance was approved by the AKTIN scientific committee (Project-ID 2019-003), each of the included emergency departments has consented to be included in the present study. Individual patient consent is not required and not feasible for this type of study and the setting of emergency department care, this has been addressed by AKTIN’s data protection concept [16]. All of the research described in this manuscript was performed in accordance with the Declaration of Helsinki.

Consent of publication

Not applicable.

Availability of data and materials

The data used and analysed during the current study are available on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

The ESEG project was funded by the Innovation Committee of the Federal Joint Committee (grant number 01VSF17034, project period 07/2018–06/2021]). The development of the AKTIN emergency department data registry was funded by the Federal Ministry of Education and Research. Both funding bodies had no role in the design of the study, the collection analysis and interpretation of the data or the writing of the manuscript.

Authors’ contributions

MS, LG and TSB conceptualised the study and research question. MS, AU and AA developed the study design and analysis plan. FG and JB ensured coordinated data sourcing from the AKTIN emergency department data registry. MS performed the analysis with support from AU. MS wrote the initial draft of the manuscript. All authors revised and approved the final manuscript.

Acknowledgements

We want to thank our partners from the ESEG-project and AKTIN emergency department data registry and especially the emergency departments that provided their data for this study.

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No competing interests reported.

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Impact of the COVID-19 pandemic and its associated public health and social measures on emergency department utilization in Germany between March 2017 and June 2021

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Abstract

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Background

Methods

Study setting and variables

Study population

Statistical Analyses

Results

Overall consultations

Age distribution

Acuity level

Weekday and hour of consultation

Discussion

Key results:

Strengths and Limitations:

Conclusions

List of abbreviations

Declarations

Ethics approval and consent to participate

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Availability of data and materials

Competing interests

Funding

Authors’ contributions

Acknowledgements

References

Additional Declarations

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