Inter-hospital variation in COVID-19 era pediatric hospitalizations by age group and diagnosis

Abstract

Background and objectives

Mitigation strategies and public responses to COVID-19 varied geographically and may have differentially affected burden of pediatric disease and hospitalization practices. We aimed to quantify hospital-specific variation in hospitalizations during the COVID-19 era.

Methods

Using Pediatric Health Information Systems data from 44 Children’s Hospitals, this retrospective multicenter analysis compared hospitalizations of children (1 day - 17 years) from the COVID-19 era (3/1/2020–6/30/2021) to pre-pandemic (1/1/2017–12/31/2019). Percent change in monthly hospitalizations between eras were calculated for each hospital, using binomial probability tests to determine significance. Variation in the magnitude of hospital-specific decline between eras was determined using coefficients of variation (CV). Spearman’s test was used to assess correlation of variation with community and hospital factors.

Results

The COVID-19 era decline in hospitalizations varied between hospitals (CV 0.41) and was moderately correlated with declines in respiratory infection hospitalizations (r=0.69, P<0.001). There was no correlation with community or hospital factors. COVID-19 era changes in hospitalizations for mental health conditions varied widely between centers (CV 2.58). Overall, 22.7% of hospitals saw increased admissions for adolescents, and 29.5% saw increases for newborns 1–14 days, representing significant center-specific variation (CV 2.30 for adolescents and 1.98 for newborns).

Conclusions

Pandemic-era change in hospitalizations varied across institutions, partially due to hospital-specific changes in respiratory infections. Residual variation exists for mental health conditions and in groups least likely to be admitted for respiratory infections, suggesting that non-infectious conditions may be differentially and uniquely affected by local policies and hospital-specific practices enacted during the COVID-19 era.

Background

The coronavirus disease 2019 (COVID-19) pandemic dramatically altered pediatric healthcare delivery in the United States (US). Nationwide pandemic-era decline in pediatric care utilization^1–3 was attributed to pandemic-related mitigation strategies and behavior change that interrupted transmission of other respiratory infections.⁴ Resurgence in pediatric hospitalizations due to increased respiratory infections temporally correlated with reopening and rollback of mitigation strategies.⁵ Implementation, stringency, and enforcement of viral-mitigation polices varied at both state and local levels and likely influenced admission patterns within communities.^6–8 Nationwide analyses have identified COVID-19 era variation in hospitalizations between US Census Geographic Regions,⁹ which represent large, heterogenous areas and likely do not reflect the geographic scale at which many pandemic-related policies and responses were enacted. . Given the local variation of COVID-19 related viral-mitigation practices and community-specific responses, pandemic-era pediatric hospitalization patterns also may have varied between hospitals. Moreover, multi-center analyses have connected pandemic-era factors to changing prevalence of certain non-infectious conditions, such as mental health conditions in adolescents,^10–12 but have not explored variations in these changes by hospital or geographic location.

Our objective was to examine variation across pediatric hospitals in COVID-19 era change in hospitalizations overall and by diagnoses and age groups. We hypothesized that pandemic-era hospitalization changes varied across hospitals, driven by local differences in respiratory infections.

Methods:

This multicenter, retrospective study utilized the Pediatric Health Information System (PHIS) database, which contains deidentified clinical and administrative information from 44 not-for-profit pediatric hospitals within the Children’s Hospital Association (CHA). Data quality and validity are ensured through a multi-step, collaborative effort between CHA and participating institutions prior to their release. The use of de-identified PHIS data was considered non-human subjects research by the institutional review board of Children’s Hospital of Philadelphia. .

Study Population and Period

We analyzed inpatient hospitalizations within PHIS for patients ages 1 day to 17 years. Only admissions from home were evaluated; transfers between hospitals and birth hospitalizations were excluded. Our study evaluated hospitalizations from 01/01/2017–06/30/2021. Given a rapid increase in SARS-Cov-2 infections, a national emergency was declared on 03/31/2020.⁶ At time of analysis, data through June 2021 were available. Therefore, we defined the “pre-pandemic era” as 01/01/2017–02/29/2020 and the “COVID-19 era” as 03/01/2020–06/30/2021.

Outcomes of Interest

The primary outcome was hospital-specific change in monthly hospitalizations during the COVID-19 era, compared to analogous months pre-pandemic. Pre-pandemic hospitalizations were defined as average monthly counts from the three preceding years to account for annual variability in seasonal infections. We stratified by PHIS-defined age categories: <30 days (newborns), 30–364 days (infants), 1–4 years (young children), 5–12 years (older children), 13–17 years (adolescents). We subdivided newborns into 1–14 days and 15–29 days, as admissions of newborns <14 days from home were likely secondary to birth-related diagnoses and birth hospitalization management.

To collect hospitalization indication, we used Clinical Classifications Software Refined (CCSR) groups corresponding to principal diagnosis code. CCSR groupings aggregate related diagnosis codes into clinically meaningful categories and are common in PHIS studies.^2,13 Patients without CCSR data were excluded from secondary analysis of admission diagnoses. Given that some CCSR codes are highly related (e.g., pneumonia and other lower respiratory disease) and may be prone to mis-categorization, groupings of related CCSR codes were developed where applicable (Supplemental Table 1).

Patient, hospital, and community characteristics were available through PHIS. We included insurance type, age, Census region, freestanding children’s hospital status, average pre-pandemic-era admission counts, and city population. Policy scores were determined from a publicly available dataset of county-level COVID-19 policy interventions.⁷ Because PHIS hospitals may serve patients from multiple counties,¹⁴ mean policy scores were calculated by state.

Statistical analysis

Descriptive statistics were calculated using chi-square tests for categorical data and analyses of variance for continuous data. Given the large sample size, standardized differences were used to test for differences between eras, with 0.1 as the significance threshold.^15,16

Percent change in hospitalizations was calculated from the monthly COVID-19 era hospitalization count compared to the month-matched pre-pandemic average. Binomial probability tests determined differences between eras,¹⁷ with two-sided p-values <0.05 considered significant. The hospital-specific variation in magnitude of decline in hospitalizations during the pandemic compared to pre-pandemic was calculated using coefficients of variation (CV), a standardized measure of variability.¹⁸ Calculated by dividing the standard deviation by the mean, larger CV values indicate greater variation. Spearman’s test was used to determine correlation. Statistical analyses were performed using Stata 16 (College Station, TX).

Results:

In the 1,624,755 hospitalizations analyzed (1,236,074 pre-COVID era and 388,681 COVID-19 era), overall monthly hospitalizations declined (−25.3%, P<0.001) in the COVID-19 era, compared to pre-pandemic (Table 1). Hospitalizations were relatively stable for newborns (−8.0%; P=0.007 and adolescents (−6.0%, P<0.001). In the 1,623,244 (>99.9%) hospitalizations with CCSR codes, there was significant decline in hospitalizations with respiratory infections (−68.4%, (P<0.0001) and asthma (−63.5%, P<0.001). Smaller, but significant declines in hospitalizations were also noted for seizures/epilepsy, chemotherapy, and congenital cardiac anomalies (Table 1).

Table 1:

Mean monthly hospitalizations by era^a

	Pre-pandemic Era (%)	COVID-19 Era (%)	Standardized Differencesb
Hospitalizations	32528	24293
Insurance type			0.07
Private	12687 (39.0)	9575 (39.4)
Medicaid	17604 (54.1)	13251 (54.5)
Self-Pay	568 (1.8)	544 (2.2)
Other	1670 (5.1)	922 (3.8)
Region (# PHIS hospitals)			0.05
East North Central (9)	5596 (17.0)	4134 (17.0)
East South Central (4)	3131 (9.6)	2439 (10.0)
Middle Atlantic (2)	2103 (6.5)	1693 (7.0)
Mountain (3)	2690 (8.3)	2070 (8.5)
New England (3)	1563 (4.8)	1236 (5.1)
Pacific (8)	6068 (18.7)	4300 (17.7)
South Atlantic (5)	3541 (10.9)	2771 (11.4)
West North Central (4)	2836 (8.7)	1921 (7.9)
West South Central (6)	5001 (15.4)	3728 (15.4)
Age			0.16
1 – 14 days	982 (3.0)	901 (3.7)
15 – 29 days	632 (1.9)	385 (1.6)
30 – 364 days	5504 (16.9)	3406 (14.0)
1 – 4 years	8420 (25.9)	5494 (22.6)
5 – 12 years	9519 (29.3)	7103 (29.2)
13 – 17 years	7471 (23.0)	7003 (28.8)
CCSRc Categories
Respiratory infections	5556 (17.1)	1754 (7.2)	0.31
Seizures/Epilepsy	1571 (4.8)	1291 (5.3)	0.02
Mental Health Conditions	1489 (4.6)	1522 (6.2)	0.07
Chemotherapy	1364 (4.2)	1278 (5.3)	0.05
Asthma	1180 (3.6)	430 (1.8)	0.11

^aData are presented by average monthly counts for each era.

^b>0.10 is considered a statistically significant difference.

^cCCSR – Clinical Classification Software Refined

Among adolescents, COVID-19 era monthly hospitalizations for all mental health conditions increased 9.9%, from 1023 to 1124 (P=0.002) (Supplemental Table 2). In contrast, average monthly hospitalizations of adolescents for other conditions declined or were unchanged (Supplemental Table 2). Among newborns 1–14 days, hospitalizations for hyperbilirubinemia, feeding disorders, respiratory conditions, and other perinatal disorders did not change, though hospitalizations for perinatal infections declined (−23.2%, P=0.02) (Supplemental Table 2).

Median center-specific pandemic-era decline in overall hospitalizations was −24.4% (interquartile range [IQR] −29.2%, −19.9%), with substantial variation across centers (CV 0.41) (Figure 1). Though the decline in respiratory conditions was large (−69.5% [IQR −74.2%, −63.7%]), variation between hospitals was small (CV 0.12). In contrast, variation in the magnitude of change in hospitalizations for mental health was larger (+9.3% [IQR −13.4%, 44.0%], CV 2.58). Twenty-four hospitals (54.5%) saw an increase in mental health-related hospitalization during the COVID-19 era.

Figure 1: Variation in inter-era differences in hospitalization by PHIS-participating Children’s Hospitals^a.

^aChange in COVID-19 era hospitalizations from pre-pandemic average for each hospital participating in the PHIS database (A through RR). Quartiles of change in overall hospitalizations are represented by colored bars: Q1 (black, greatest decline), Q2 (dark gray), Q3 (light gray), Q4 (white, least decline); the color scheme is maintained in Panel B and C to demonstrate correlation between changes in overall hospitalization and change in specific diagnosis.

^bAll hospitals had significant inter-era change (P<0.05) in overall hospitalizations (Panel A), except RR (denoted by ^).

^cAll hospitals had significant (P<0.05) inter-era change in hospitalizations for respiratory infections (Panel B)

^dHospitals with significant inter-era changes in hospitalizations for mental health conditions (Panel C) are denoted by an asterisk (*), P<0.05

By age group, 22.7% and 29.5 % of hospitals had COVID-19 era increases in hospitalizations for adolescents and newborns 1–14 days, respectively, whereas all hospitals had declines in other age groups (Figure 2). Thus, hospital-specific variation in COVID-19 era hospitalizations was greatest for adolescents (CV 2.30) and newborns (CV 1.98), compared to other age groups (newborns 15–29 days [CV 0.36], infants [CV 0.32], young children [CV 0.29] and older children [CV 0.42]).

Figure 2: Variation in inter-era differences in hospitalization of PHIS-participating Children’s Hospitals by age group^a.

^aChange in COVID-19 era hospitalizations compared to the pre-pandemic average for each institution participating in the PHIS database (bars A through RR), stratified by age group (panels A-F).

Variation in pandemic-era changes in hospitalizations was not explained by hospital factors, community factors or state-level policy score (Supplemental Table 3). Centers from the same states differed from one another with respect to change in hospitalizations (data not shown to maintain institutional anonymity). COVID-19 era change in hospitalizations was most strongly correlated with change in respiratory infections (r=0.69, P<0.001), and to a lesser extent, mental health conditions (r=0.32, P=0.037). Adolescent hospitalizations were correlated with mental health conditions (r=0.65, P<0.001) and respiratory infections (0.46, P=0.002).

Discussion:

Among over 1.6 million hospitalizations in 44 Children’s Hospitals across the US, hospitalizations declined markedly during the COVID-19 era. Similar to prior studies, we found a decline in overall hospitalizations and hospitalizations for respiratory infections, signaling decreased circulation of respiratory pathogens which cause bronchiolitis, pneumonia, and asthma exacerbations.^1,3,9

Our study highlights the variation in the magnitude of COVID-19 era decline in hospitalizations. Though some variation is explained by hospital-specific changes in admissions for respiratory infections, residual variation persisted for mental health conditions. Moreover, adolescents and newborns 1–14 days, who were least likely to be hospitalized for respiratory conditions, had the largest between-center variation in pandemic-era changes. These findings emphasize that pandemic policies and changes in hospital practices may have had spillover effects extending beyond mitigation of respiratory pathogen transmission.

Variation in COVID-19 era decline in hospitalizations was not explained by Census region, likely because these areas are large and heterogeneous. Furthermore, there were wide differences in admission hospital rates within the same state, and no correlation with state policy score, suggesting that drivers of variation act on a local level. We found no correlation of hospital specific factors with declines in overall hospitalizations or changes by age group. Given data limitations, we were unable to investigate community factors (e.g., scope or adherence to COVID-related policies) or hospital-specific practices (e.g., admission thresholds) that could account for the variation across hospitals.

We found marked variation across hospitals in pandemic-era changes in hospitalizations for adolescents, which was partially explained by hospitalizations for mental health conditions. While recent reports have shown an increase in hospitalizations for mental health concerns,^10–12,19 we found that these admissions declined in some centers, suggesting that this trend may not be uniform across the country. Community-specific investigation is needed to determine if this decline was due to local protective factors or barriers in accessing necessary care.

Newborns 1–14 days also had large hospital-specific variation in pandemic-era hospitalization. Shifts in diagnosis prevalence may occur differentially between hospitals, as prior single-center analyses have noted COVID-19 era fluctuations in infectious and non-infectious conditions.^20,21 However, our multicenter analysis found that hospitalizations with non-infectious conditions remained stable during the pandemic, making it difficult to attribute the increased hospitalizations at 29.5% of centers studied solely to pandemic-related changes in diagnosis frequency. Pandemic-related modifications to birth hospitalizations practices also differ across the nation²² but have not been associated with increased newborn readmissions.²³ Additional hypotheses for variation across hospitals, such as differential access to outpatient services²⁴ and changing admission thresholds for the youngest patients, are plausible.

This retrospective study is subject to diagnosis misclassification, though rigorous data quality monitoring in PHIS ensures minimal error-induced bias. We aggregated the policy score at the state level to reflect the multi-county referral bases typical of many PHIS hospitals; however, even this broad classification is subject to miscategorization bias given that some PHIS hospitals border multiple states and have even larger, regional referral bases.²⁵ This cohort does not include small pediatric hospitals and community hospitals, which may have unique hospitalization patterns due to different COVID-19 caseloads or local resource allocation. Previous work suggests that pediatric hospitals (compared to community hospitals) had higher than expected mental health care use during the pandemic;²⁶ the association with respiratory infections and infant hospitalizations has not been examined. However, given pediatric care regionalization,^{27, 28} PHIS captures a large and generalizable pediatric population, which can inform national priorities and efforts.

Conclusion

In this novel study of hospital-specific changes in hospitalizations during the COVID-19 pandemic, we found wide variation especially among newborns and adolescents. Variation was not explained by hospital or regional factors, indicating that hospitalization patterns may be influenced by pandemic-related factors and practices at the community or institutional level. Though some variability is attributed to COVID-19 policies and strategies affecting respiratory infections, non-infectious conditions - particularly in the youngest and oldest children - may be uniquely sensitive to pandemic-era factors that differentially influence hospitalization patterns across communities. To prepare for future pandemics and viral surges, further work should incorporate local policies, mitigation strategies, and disease burden to elucidate drivers of geographic variation, understand their downstream effects, and identify populations most vulnerable to hospitalization.