a b s t r a c t

Objectives: This study describes the utilization of a pediatric emergency department (ED) during the early months of the COVID-19 pandemic in the initial U.S. epicenter, including the impact on visit acuity and incidences of com- mon diagnoses.

Study Design: We performed an observational retrospective review of patients younger than 18 years old seen in a New York City pediatric ED from March 7th to May 6th 2020, and during the same time period in 2018 and 2019. Demographics, visit details, diagnoses, and dispositions were compared. Validated algorithms were utilized to create practical diagnosis groupings and to determine the probability of a visit requiring emergent evaluation. Results: ED visits during the pandemic decreased by 56% to an average Daily census of 67 patients, from an antic- ipated 152. Admission rates rose from 13.3% to 17.4% (p<0.001), and the proportion of Triage emergency severity index level 1 and 2 patients increased by 23.7% (p<0.001). Non-emergent visits dropped from 32.3% to 27.5% (p<0.001). Several common, often low-acuity diagnoses saw disproportionate reductions in visits including headache, chest pain, and minor injuries. Concerningly, visits for suicidal ideation, suicide attempt, or self- harm increased by 100% (p<0.001) and visits for evaluating abuse or neglect decreased by 89% (p=0.01).

Conclusions: Pediatric ED utilization substantially deceased during the early months of the COVID-19 pandemic in New York City, but left relatively higher patient acuity. healthcare systems in early epicenters must also prepare for the disproportionate impact a pandemic has on the most vulnerable pediatric patients, particularly those at risk for self-harm or abuse.

(C) 2021

1. Introduction

Soon after the first patient in New York City (NYC) was diagnosed with the coronavirus disease of 2019 (COVID-19), the number of con- firmed cases in New York State (NYS) skyrocketed with NYC being la- beled the national epicenter of the pandemic [1]. State and city attempts to harness resources and stem the tide of infections escalated over the initial weeks, including a “NY on PAUSE” order limiting travel, business, and public gatherings.

Abbreviations: CCSR, Clinical Classification Software Refined; ED, Emergency Department; EMS, Emergency Medical Services; ESI, Emergency Severity Index; ICD-10- CM, International Classification of Diseases 10th Revision, Clinical Modification; ICU, Intensive Care Unit; LOS, Length of Stay; MERS, Middle East Respiratory Syndrome; NY, New York; NYC, New York City; PICU, pediatric intensive care unit; SARS, Severe Acute Respiratory Syndrome.

* Corresponding author at: Division of Pediatric Emergency Medicine, Cohen Children’s Medical Center, 269-01 76th Ave, New Hyde Park, NY 11040, USA.

E-mail address: [email protected] (W.C. Sokoloff).

Adult healthcare systems faced unparalleled challenges in patient vol- ume and acuity [2-5]. However, in line with prior coronavirus epidemics such as the 2003 severe acute respiratory syndrome (SARS) [6,7] and the 2014 Middle East respiratory syndrome [8] epidemics, pedi- atric emergency departments (ED’s) seemed to have been spared the same influx of patients [9-12]. Studies published to date in the U.S. have reported widespread reductions in pediatric volumes (59%-67%) and in- creases in acuity [13-16]. Notably though, the multicenter studies in the literature have overwhelmingly examined general ED’s rather than dedi- cated pediatric centers which have a higher proportion of medically com- plex pediatric patients [17]. Additionally, the studies to date consider a span of timepoints and a span of locations under varying levels of public health restrictions, but none focus on early epicenters of the U.S. pan- demic. The largest study by Hartnett et al. [13] did not include data from NYC while another study acknowledged as a limitation the low prevalence of COVID-19 in its location [18]. From an epidemiological and system preparedness standpoint, it is important to understand how the “first-wave” of a pandemic, as experienced in NYC where there

https://doi.org/10.1016/j.ajem.2021.02.029

0735-6757/(C) 2021

were public health restrictions and high community illness, will impact a pediatric healthcare system.

It was hypothesized that as a consequence of the increased isolation of children under the “NY on PAUSE” order, the prevalence of certain diag- noses would be more affected than others. This was particularly expected for various infectious illnesses, though Sheridan et al. [19] also described decreased pediatric ED visits for psychiatric complaints. It is unclear if these patterns hold true in a community with high disease prevalence.

By understanding the acuity and the pathology that present in the initial months of an active pandemic, we may prepare a healthcare sys- tem for pediatric resource needs during a future event. That includes identifying the most vulnerable Pediatric populations and developing innovative methods for providing them care. This study examines the effect the COVID-19 pandemic had on the demographics, diagnoses, and acuity seen by a pediatric ED in the first U.S. epicenter.

1. Methods
   1. Settings and subjects

We conducted an observational, retrospective natural experiment study surrounding the COVID-19 pandemic in NYC. The pediatric ED at the focus of this study is located in the NYC borough of Queens, con- sidered part of the initial epicenter of the U.S. COVID-19 pandemic and serving communities prominently effected by governmental and self- imposed restrictions. It is a dedicated pediatric ED within a Tertiary care children’s hospital with a Level-1 pediatric trauma designation, car- ing for over 55,000 patients annually. The study period began March 7th, 2020, the day NYS announced a State of Emergency, and continued for two months until May 6th, 2020.

This study was approved by the Northwell Health Institutional Re- view Board and the Northwell Health COVID-19 Research Consortium.

• 1. Data collection

All patients younger than 18 years old evaluated in the pediatric ED during the study period in 2020 were identified and included (“COVID”). We also identified all patients younger than 18 years old eval- uated in the pediatric ED during the same period in 2018 and 2019 (“Pre- COVID”), to serve as a proxy for what was anticipated absent the pan- demic. Information regarding demographics, mode of arrival, triage infor- mation, primary diagnosis, length of stay and disposition were collected through routinely created hospital analytic reports. Data missing from these reports was manually collected through a chart review.

• 1. Acuity, urgency, and burden of illness

We used several variables to assess for patient acuity and burden of illness. One such tool is the Emergency Severity Index triage tool [20], which is a common five-level ED triage stratification assigning pa- tients level 1 (most urgent) to 5 (least urgent) on the basis of acuity and anticipated resource needs. We also classified visits as emergent and non-emergent using the NYU-ED Algorithm [21] developed by the New York University Center for Health and Public Service Research. This validated tool uses International Classification of Diseases 10th Revi- sion, Clinical Modification (ICD-10-CM) Diagnosis codes to estimate the probability of an ED visit requiring Emergent medical care within 12 h. The algorithm does not categorize the urgency of visits related to alco- hol use, substance abuse, injuries, or mental health as well as other diag- noses the developers felt were not prevalent enough to confidently designate as emergent or not. Disposition of patients was also used as a surrogate measure of acuity.

• 1. Diagnosis groupings

Based on a patient’s primary ICD-10-CM code, visits were stratified into practical diagnosis groups using the Healthcare Cost and Utilization

Project’s Clinical Classification Software Refined (CCSR), version 2020.2 [22], which categorizes the over 70,000 ICD-10-CM codes into established groupings. The authors pre-selected several groupings for further analysis as they were felt to either represent a substantial per- centage of ED visits, be of particular clinical interest, or anecdotaly af- fected by the pandemic. Several infectious diagnoses such as “Fever” and “upper respiratory infection“, though common, were not selected for further analysis to avoid confounding by potential COVID-19 positive patients who were not tested.

• 1. COVID-19 patients

During the early study period, the ability to test all suspected pa- tients for COVID-19 was severely limited and patients diagnosed with COVID-19 likely underrepresented the number of COVID-19 patients evaluated [23]. As such, for the purposes of the CCSR diagnosis group- ings, COVID-19 was recoded as ‘Viral Infection’, and for the NYU-ED Al- gorithm it was left as unclassified.

• 1. Statistical analysis

When comparing patient visits from the COVID and Pre-COVID periods, categorical values were compared using Fisher’s exact test. Continuous values and comparison of means were evaluated using 2- tailed unpaired t-tests for both parametric and non-parametric data due to the large sizes [24]. Mean values are described with standard de- viation while proportions are described with 95% confidence intervals. Statistical significance was designated at p of 0.05. Statistical analyses were performed using SPSS 25 (IBM Inc., Armonk, NY, USA).

1. Results

During the study period (COVID), there were 4068 patient visits in the pediatric ED, with an average daily census of 67 patients (range 30-164) (Fig. 1). This was 56.1% fewer visits than anticipated (9256 ex- pected visits with a Pre-COVID average daily census of 152, range 102-206). Demographic information for visits during the COVID period and Pre-COVID period is shown in Table 1. Mean age was not signifi- cantly different, though there were slight but statistically significant changes in age groups (p < 0.001) marked by a greater proportion of in- fants and adolescents compared to Pre-COVID. Table 2 displays assess- ments of acuity and illness burden. During the pandemic, the highest acuity ESI level 1 and 2 patients made up 18.8% of visits, compared to 15.2% of patients Pre-COVID (p < 0.001). The proportion of non- emergent visits had a 14.6% relative decrease from 32.3% of visits to 27.5% of visits (p < 0.001).

Overall admission rate during COVID was 17.4% with a relative risk of a patient being admitted 1.31 (CI_95%: 1.21-1.41) compared to prior years, though this still equates to an absolute Reduction in admissions by 57%. Of those admitted, there was not a statistically significant differ- ence in the percentage of patients requiring ICU admissions (ICU: COVID 16.9% vs Pre-COVID 19.4%, Medical/surgical units: COVID 83.1% vs Pre- COVID 80.6%, p = 0.17).

Twenty-seven patients were given a diagnosis code for COVID-19 and recoded as earlier described. Table 3 displays the incidences of sev- eral pre-selected diagnoses, with some incidences disproportionately lower than the 56.1% decrease in overall visits. This was particularly true for generally low-acuity complaints including non-specific chest pain (-72%, p = 0.031), headaches (-79%, p < 0.001), minor injuries

(-73%, p < 0.001), and nausea/vomiting/diarrhea (-76%, p < 0.001). The largest decrease was for maltreatment and abuse (-89%, p = 0.01). Visits for suicidal ideation, suicide attempt or self-harm increased by 100% (p < 0.001) despite overall visits for psychiatric disorders de- creasing by 64% (p = 0.015).

Fig. 1. Average daily census. Study Period includes March 7th to May 6th. The solid line marks the daily census from the first reported COVID-19 case in NYS to six days after the COVID study period. The dashed line marks the average daily census during the Pre-COVID period.

0

10-May

1-Mar

8-Mar

15-Mar

22-Mar

29-Mar

5-Apr

12-Apr

19-Apr

26-Apr

3-May

Study Period

80

60

40

20

Pre-COVID Avg Daily Census

‘NYS on PAUSE’ order in effect

COVID Daily Census

120

100

NYC schools closed

140

Restrictions on Mass gatherings; Broadway closes

180

160

State of Emergency Declared for NYS

200

Table 1

Demographics

	Pre-COVID (2018/19)		COVID (2020)	P-value
	% (n = 18,513)		% (n = 4068)
Age, mean (SD) Age group (years), (%)	7.3 years (5.5)		7.1 years (5.8)	0.07 <0.001
<1	12.5% (2319)	16.2% (658)

1-5 36.6% (6780) 36.6% (1487)

6-12 29.9% (5536) 24.7% (1003)

13-17 20.9% (3878) 22.6% (920)

Gender, Male (%) 54.0% (9997) 53.2% (2164) 0.36

Race (%)^a <0.001

White/Caucasian 27.0% (4991) 25.3% (1029)

Black/African American 25.6% (4741) 22.1% (897)

Asian 15.6% (2887) 14.3% (580)

Other/Multiracial 30.0% (5562) 34.8% (1414)

Unknown/Declined 1.8% (332) 3.6% (148)

Ethnicity (%)^a 0.038

Hispanic 18.1% (3342) 19.5% (793)

Non-Hispanic 78.9% (14607) 77.9% (3170)

Unknown/Declined 3.0% (564) 2.6% (105)

Insurance (%) <0.001

Private 41.0% (7590) 39.7% (1615)

Public 53.1% (9838) 56.4% (2296)

Self-pay/Uninsured 5.9% (1085) 3.9% (157)

^a Self-reported.

1. Discussion

During prior coronavirus epidemics (e.g., SARS, MERS) decreased pediatric ED visits were believed to be a result of the low pediatric dis- ease burden and the perceived risk of accessing healthcare during a

As the pandemic continues, the focus has been placed on how pedi- atric ED’s can best reallocate resources while also strategizing for a fu- ture pandemic [16,30]. Acuity and urgency are key factors. Similar to other sites, the early months of the pandemic in NYC saw acuity rise. The proportion of ESI 1 and 2 visits increased by 24% and admission rates increased by 31%. As ESI does not reflect final diagnoses, we also utilized the NYU-ED algorithm to evaluate how urgently patients re- quired an ED visit and found the number of visits that did not require emergent medical evaluation decreased by 14.6%.

To be prepared, pediatric ED’s monitor patterns of acuity, but also anticipate trends in diagnoses. Because children were confined home for much of the early pandemic, we expected increases in certain diag- noses such as accidental ingestions, burns, and foreign bodies. Though

Table 2

ED Burden of Severity and Acuity

Pre-COVID COVID P-value

% (n) % (n)

Mode of Arrival <0.001

Walk-In	85.8% (15875)	84.5% (3439)
EMS/Transport	13.7% (2532)	15.5% (629)
Unknown	0.6% (106)	0.0% (0)
ESI 1	0.4% (69)	0.2% (9)	<0.001
2	14.8% (2743)	18.6% (756)
3	39.2% (7262)	37.9% (1543)
4	39.7% (7349)	38.4% (1564)
5 Disposition Transfer	5.9% (1090) 0.4% (68)	4.8% (196) 0.5% (21)	<0.001
Discharge	86.3% (15975)	82.1% (3339)

public health crisis [6,25,26]. The U.S. has not experienced such a signif-	Admission	13.3% (2470)	17.4% (708)
icant public health state of emergency prior to the COVID-19 pandemic.	Admit-Medical/Surgical	9.5% (1756)	12.5% (510)
In NYC, the pandemic uniquely compounded the reduced need for med-	Admit-PICU	2.3% (423)	2.6% (104)

ical evaluations due to milder pediatric disease [27-29], the perceived risk of exposure to the virus by presenting to an ED, hesitancy to utilize limited medical resources, and the comprehensive restrictions set by	Admit-OR Admit-Psychiatry NYU-ED Urgency Emergent	1.0% (178) 0.6% (113) 67.8% (6449)	1.4% (57) 0.9% (37) <0.001 72.5% (1313)
the “NY on PAUSE” order. In the course of our study period, there was	Non-emergent	32.2% (3064)	27.5% (499)

a 56% decrease in average daily volume as compared to prior years, within the range of the published literature to date [13-16].

Daily Census

Abbreviations: EMS, Emergency Medical Services; ESI, Emergency Severity Index; PICU, Pediatric Intensive Care Unit; OR, Operating Room.

Table 3

Visits per 2-month study period by diagnosis

Diagnosis group(s) Pre-COVID (naverage)

COVID

(n)

Relative change

P-value

options for the most at-risk children. The charts of our suicidal patients included quotes such as “having stressors with current pandemic situa- tion and has not been able to see therapist” as well as “feeling anxious about online schoolwork since school has been cancelled.”

All diagnoses	9256	4068	-56%	n/a Our findings are consistent with literature examining children in
Injuries, severea	549	318	-42%	<0.001 China [36] and the Netherlands [37] during the COVID-19 pandemic,
Injuries, minorb	677	181	-73%	<0.001 quarantined individuals during the 2003 Toronto SARS epidemic [38],
Abdominal pain	550	196	-64%	0.005 and individuals in NYS following the 9/11 terrorist attacks [39]: proximity
Nausea, vomiting, diarrheac,e	760	184	-76%	<0.001 to a pandemic or event epicenter and relationships with people afflicted
Appendicitis	80	85	+6.3%	<0.001
Asthma	368	103	-72%	<0.001 by an event are associated with higher behavioral health concerns and
Foreign body	86	62	-28%	0.001 ED utilization for behavioral health symptoms. These patterns suggest
Otitis media	194	66	-66%	0.051 that as social restrictions and disease prevalence rise during an epidemic,
Urinary tract infections	103	48	-53%	0.74 healthcare systems and mental health providers should seek out their
Headache, including migraine	155	32	-79%	<0.001
Non-specific chest pain	93	26	-72%	0.031 most high-risk patients to ensure continuity and resource availability,
Convulsions or epilepsy	167	89	-47%	0.10 whether through telemedicine or behavioral health urgent care centers.
Suicidal ideation/attempt or self-harm	11	22	+100%	<0.001 This study faces many of the common limitations of a retrospective re-
Psychiatric disordersd,e	497	180	-64%	0.015 view including dependence on data collection systems that may have
Poisoning by drugs	21	14	-33%	0.15 missing or incorrect information. Additionally, the single-center nature
Hemolytic jaundice and perinatal jaundice	27	22	-19%	0.011 of the study limits generalizability; though our broader findings of de-

^a Includes fractures, open wounds and lacerations.

Diabetes mellitus with complication	16	13	-19%	0.046	creased visits and higher acuity reflect national patterns and our more
Burns Maltreatment/abuse	15 28	11 3	-27% -89%	0.12 0.01	granular results highlight the unique severity of restrictions and disease prevalence initial epicenters may face during a pandemic. Unique to this

^b Includes contusions, superficial injuries, concussions, sprains and strains, musculo- skeletal pain, and low back pain.

^c Includes nausea and vomiting, non-infectious gastroenteritis, and intestinal infection.

^d Includes anxiety disorders, bipolar disorders, Depressive disorders, conduct disorders, Mood disorders, schizophrenia spectrum disorders, psychotic disorders, and trauma re- lated disorders.

^e Not a routine CCSR grouping.

these visits did not increase as hypothesized, they did not drop nearly as much as the overall ED volume.

As predicted, low acuity complaints such as chest pain, headache, minor injuries, and nausea/vomiting/diarrhea decreased substantially. Interestingly, the diagnosis of abdominal pain considerably decreased while appendicitis did not. Therefore, children presenting with undiffer- entiated abdominal pain were more likely to have a true appendicitis.

One dramatic and concerning change in presentations is the 89% decrease in primary diagnoses for child abuse or maltreatment. This pattern has yet to be described elsewhere in the literature and unmis- takably should not be affected by changes in ED volume alone. Indeed, during a similar time period, NYC’s Administration for Children’s Ser- vices received 51% fewer reports of neglect or abuse [31]. Though the cause is likely multifactorial, it is predominantly attributable to children’s lack of exposure to mandated reporters, rather than such a dramatic decrease in incidences of abuse and neglect [32,33]. Data on this population and potentially missed sentinel events will need to be followed closely as the pandemic continues. Public health agencies must keep a heightened awareness of this trend to drive Novel methods for intervening and monitoring children early in pandemics or crises.

An additional concerning discovery is the doubling of visits for sui- cidal ideation, suicide attempts, or self-injury. Though comparatively small in absolute numbers, the 100% relative increase is in stark contrast to the considerable decrease in overall behavioral health visits seen in our ED and in others’ [15,19]. Children across the country are socializing less and enduring new pandemic-related stressors on their families. We postulate our unique finding of increased suicidality and self-harm is in- part a consequence of the relatively higher media attention, severity of stressors such as parental job loss, and high prevalence of COVID-19 in the NYC area during the study period. For reference, by the end of July 2020, 1 in 520 children in Queens experienced the death of a parent or caregiver to COVID-19, more than any other county in NYS [34]. In addition, access to mental health services in NYC communities was se- verely restricted, particularly for those who receive school-based ser- vices [35]. As many telehealth opportunities had not yet been initiated, this meant removing preventative and crisis management

study is the inclusion of the NYU-ED Algorithm which, though previously validated [40] and utilized in the pediatric literature [41], does have inher- ent limitations in excluding particular diagnoses. However, as our study compares findings from year-to-year, the relative change is more mean- ingful than the absolute findings of one year’s numbers.

Timing of the study must also be considered. As Fig. 1 displays, pa- tient volume was higher during the earliest weeks of the pandemic, thus potentially skewing our results towards earlier trends. The COVID study period also preceded the Surge of patients in NYS with Multisys- tem Inflammatory Syndrome of Childhood (MIS-C) [42] who would likely increase the acuity and illness burden in the ED.

1. Conclusions

During the early months of the COVID-19 pandemic in NYC, our pe- diatric ED saw unprecedented decreases in volume. However, the resulting patient population seeking ED care was of higher acuity, more likely to warrant emergent evaluation, and more likely to require hospitalization. As healthcare systems develop resource strategies for the current and potential future pandemics, community outreach and vigilance should target the most vulnerable pediatric patients, particu- larly those at high risk for self-harm or abuse who have been dispropor- tionately affected.

Disclosure

The authors declare no conflicts of interest.

Funding

This research did not receive any specific grant from funding agen- cies in the public, commercial, or not-for-profit sectors.

Declaration of Competing Interest

None.

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