Introduction
The first diffusion wave of COVID-19 in early 2020 led to a steep decline in total Emergency Department (ED) visits, contradicting previous experience with seasonal influenza and ED overcrowding [
1‐
4]. This unpredicted phenomenon involved acute drops in the diagnoses and hospital admissions for time-dependent conditions, raising major clinical concerns [
5‐
8]. However, cross-sectional details regarding ED visit characteristics, diagnostic outcomes, and disposed hospital admissions, have been sparse, and reports have focused on the initial phase of the COVID-19 pandemic, when the first lockdown measures were disposed. In several countries, especially in Europe, an epidemiological post-wave nadir phase devoid of lockdown measures was registered during the summer of 2020. Trends in ED flows and activity after the first wave, beyond the initial “public fear and lockdown” response, are unknown. Understanding the dynamics and kinetics of this phenomenon is instrumental to guide organization of EDs, medical wards and hospital care at large, during and beyond the second wave of COVID-19.
In the city of Torino, a large northern Italian city (870,000 inhabitants), during the first wave of the pandemic, the number of daily COVID-19 diagnoses peaked in March–April 2020. Since June, a persistently low incidence was registered throughout the summer of 2020, when restrictive measures were withdrawn. We took advantage of this epidemiological scenario, characterized by a well-defined first wave and post-wave nadir phase, to evaluate ED flows, visit characteristics, diagnoses, and hospital admissions, during the first wave and in the post-wave phase. Our working hypothesis was that these variables would return to previous standards after the resolution of the first wave and withdrawal of lockdown measures. Persistent changes, instead, would prompt to structural and long-lasting effects of the pandemics on use of/referral to EDs.
Methods
Study design and setting
We conducted a multicenter, observational, retrospective study in five hospitals in the urban area of Torino, Italy, covering all medical and surgical specialties. Participating centers (ESM Appendix Table 1) were: one large tertiary university hospital (coordinating center), one tertiary non-university hospital, two secondary non-university hospitals and one smaller community hospital. All are public hospitals (except for the latter, which is private providing public healthcare). The overall census of the participating EDs is about 320.000 ED visits/year (pre-COVID-19 period), corresponding to ≈ 90% of ED visits in the urban area. Urban hospitals not participating to the present study were one small community hospital, a specialty trauma center, a specialty obstetrical/gynecological center and a specialty pediatric center.
Epidemiological scenario and lockdown timing
During the first wave of the pandemic, the national peak of COVID-19 cases was reached on 20–28th March 2020. To reduce viral diffusion, a national lockdown was imposed from 9th March to 17th May 2020. On 3rd June 2020, key restrictive measures were withdrawn, and from May, no excess mortality was registered across the nation [
9]. In the city of Torino, the number of daily COVID-19 diagnoses peaked at about 300/day from 20th March to 14th of April 2020, and stably returned at < 10/day from 18th of June, with low incidence persisting throughout the summer.
Measurements
The study period was 1st January to 31st August, 2020 and 2019. ED data were extracted in each center from the health record database in anonymized form. An automatic query was performed to extract the following data from each visit: patient gender, age, date of ED registration, triage priority, time of arrival, triage main symptom, date of discharge, patient destination (discharge vs hospital admission), and final diagnosis. Data extraction did not involve evaluation of individual medical charts or registration of additional personal/clinical information, and data treatment conformed to Italian D. Lgs. 196/2003 and European regulation 2016/679. Since the study focused on general ED flow analysis (system-level) and not on individual patients, only utilized anonymized data, and was retrospective observational in nature, Ethic Committee approval was waived, as confirmed by the Hospital Board (prot. 101035, 23rd October 2020).
Triage codes and symptoms
Triage priority was based on standard triage nurse evaluation using color-codes following national indications. Briefly, a red code is attributed when a patient is suspected of having a life-threatening condition or vital sign modification, implying immediate evaluation. A yellow code is given when a patient displays signs/symptoms that could underlie a serious illness with evolving risk, implying medical visit within 30 min. A green code is assigned when a patient does not present warning signs/symptoms, and whose medical evaluation can be deferred. A white code is attributed when a patient complains symptoms that could be evaluated during an ambulatory medical visit in the following hours.
Triage evaluation includes a structured interview by a trained nurse, also defining main triage symptom. From March 2020, systematic triage assessment of key COVID-19 symptoms was also applied, to allow early allocation of patients satisfying criteria to a dedicated ED area. Color code evaluation was unchanged. In data analysis, the following main triage symptoms were queried: dyspnea, chest pain, abdominal pain, psychiatric symptom.
Diagnostic classification
Discharge diagnoses were grouped using the ICD-9-CM classification, with few modifications based on clinical reasoning. Within the ICD group “16–symptoms, signs, and ill-defined conditions”, selected diagnoses were analyzed per se because frequently leading to ED visits (syncope, unspecific chest pain), or were grouped within organ-specific categories (ESM Appendix Table 2). Fever and sepsis/septic shock were grouped within infectious diseases, dyspnea was grouped within respiratory diseases, palpitations were grouped within cardiovascular diseases, and convulsions were grouped within neurological diseases. Pediatric patients were defined by age < 14 years. Based on the local practice of all participating centers, ICD-9-CM codes defining SARS-CoV-2 infection were: 79.82, 480.3 or V01.82.
Statistical analysis
For statistical analysis, the study focused on four 14-day periods in 2020, which were compared to the corresponding periods in 2019: 31st March–13th April (climax of the first wave), 16th–29th June (early post-wave), 14th–27th July (mid post-wave) and 18th–31st August (late post-wave period). The last three study periods were chosen a priori to be evenly distributed, allowing two weeks of adaptation after withdrawal of lockdown measures.
Count data were expressed with absolute number and proportion. Using the Poisson regression, we estimated the percent change and its 95% confidence interval (CI) from the exponentiated Poisson regression coefficient. Type-III P values were used to assess whether the Poisson regression model with a specific variable was statistically significant (P value < 0.05). Data were displayed using locally estimated scatterplot smoothing (LOESS), in order better show data trend (smoothing span conservatively set at 14%). Extraction of count data and graphs were done with Microsoft Excel (Microsoft Corp., ver. 16.0), MedCalc (MedCalc Software Ltd, ver. 19.5.2), and all statistical analyses were performed using SPSS (IBM Corp., ver. 25.0).
Discussion
This is the first study analyzing the long-term effects of COVID-19 on ED flows beyond the early diffusion phase and throughout the epidemiological nadir observed during the summer of 2020 in European countries [
2,
4,
5]. Reductions, during and after the first wave peak, mostly derived from non-urgent codes, i.e. cases amenable to deferrable evaluation and potentially indicative of ED misuse. Instead, the number of urgent codes was unchanged. During the wave peak, changes were more pronounced during daytime and in younger patients, also indicating a prevalent effect on deferrable cases. The drop was very substantial and persistent for pediatric patients, as previously reported [
10,
11]. In the post-wave periods, the reduction in ED visits was also more pronounced for female patients, indicating gender-specific differential effects.
In line with previous reports, we also found a major reduction in cardiovascular and neurologic diagnoses during the wave peak, but moderate reductions also persisted in the post-wave phase [
5‐
8]. Related hospital admissions normalized after the peak, potentially indicating a prevalent reduction in milder cases. For several other conditions, the post-wave period was also characterized by a long-lasting reduction in ED diagnoses, while admissions were normalized. Overall, these data indicate potential ED undertreatment as a COVID-19 side effect, but also that several patients may have been managed outside EDs [
12]. Both ED diagnoses and admissions for onco-hematological and metabolic/endocrine diseases returned to pre-COVID-19 standards early after the first wave, potentially indicating lower disposal or efficiency of alternative care to EDs for these conditions.
Admission data indicate that, in spite of a long-lasting decline in ED visits, the number of hospital beds needed for non-COVID-19 diseases after a wave is largely unchanged, especially for patients affected by metabolic/endocrine and hematologic diseases. Results also show that during a pandemic peak, the admission rate for non-COVID-19 conditions reaches a climax, likely due to burn-out of ED resources by COVID-19, increased difficulties in outpatient management, loss of beds in ED-driven observation units, and increased proportion of patients with more severe conditions seeking ED care.
While facing a second COVID-19 wave worldwide, study results have practical implications. Reduced numbers of patients accessing EDs constitutes an unprecedented opportunity to preserve or even increase the quality of ED care. However, additional barriers may counterbalance the potential benefits of visit reduction, such as the necessity of pre-triage, additional testing, and patient distancing. Unless well designed strategies are put in place, insufficient ED facilities and long turnaround times for testing will prevail, leading to dangerous overcrowding and increased boarding time.
The current study does not provide data on the causes leading to ED visit reduction, and quantification of patients inappropriately avoiding or delaying ED visits was not possible. Differential effect on women, pediatric patients and triage codes indicate that this is likely a multifactorial phenomenon, warranting further category-specific investigation.
The study has limitations. First, results essentially apply to areas experiencing a clear-cut viral wave followed by nadir. Second, sub-analyses of ED discharge diagnosis must be interpreted with caution. Such diagnosis, chosen by the attending physician as the prevalent diagnosis, may not correspond to subsequent medical evaluations and may represent the prevalent, but not the only, clinically meaningful condition. Third, sub-analyses are less powered for infrequent disease categories (thus leading to type II error). Fourth, visits for most severe obstetrical/gynecological diagnoses, traumas and pediatric patients may be under-represented (selection bias), because locally, these cases are frequently conducted to the corresponding specialty ED not included in the present study. In general, reductions in ED visits, diagnoses and hospital admissions may be less pronounced in referral centers accepting most severe cases from large areas.
In conclusion, we found that the first wave of COVID-19 modified ED flows in the long-term, with measurable changes during the summer of 2020, after withdrawal of lockdown measures and return of local COVID-19 incidence to a minimum. Reductions in total visits were dragged by non-urgent triage codes, and more pronounced for female and pediatric patients. Hospital admissions acutely declined during the first wave, but rapidly returned post-peak almost to previous standards. Admissions for certain conditions (metabolic/endocrine and hematologic diseases), however, were unchanged even during the peak, indicating that a sufficient number of hospital beds for non-COVID-19 diseases must be guaranteed throughout a peak, rapidly reverting to standard numbers after the peak resolution. Finally, this unprecedented reduction in ED visits should be regarded as a proof-of-concept that ED overuse and overcrowding are hard yet affordable endpoints for strong healthcare policies.
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