BACKGROUND AND OBJECTIVES:

The coronavirus disease 2019 (COVID-19) pandemic has led to changes in health care use, including decreased emergency department visits for children. In this study, we sought to describe the impact of the COVID-19 pandemic on inpatient use within children’s hospitals.

METHODS:

We performed a retrospective study using the Pediatric Health Information System. We compared inpatient use and clinical outcomes for children 0 to 18 years of age during the COVID-19 period (March 15 to August 29, 2020) to the same time frame in the previous 3 years (pre-COVID-19 period). Adjusted generalized linear mixed models were used to examine the association of the pandemic period with inpatient use. We assessed trends overall and for a subgroup of 15 medical All Patient Refined Diagnosis Related Groups (APR-DRGs).

RESULTS:

We identified 424 856 hospitalizations (mean: 141 619 hospitalizations per year) in the pre-COVID-19 period and 91 532 in the COVID-19 period. Compared with the median number of hospitalizations in the pre-COVID-19 period, we observed declines in hospitalizations overall (35.1%), and by APR-DRG (range: 8.5%–81.3%) with asthma (81.3%), bronchiolitis (80.1%), and pneumonia (71.4%) experiencing the greatest declines. Overall readmission rates were lower during the COVID-19 period; however, other outcomes, including length of stay, cost, ICU use, and mortality remained similar to the pre-COVID-19 period with some variability by APR-DRGs.

CONCLUSIONS:

US children’s hospitals observed substantial reductions in inpatient admissions with largely unchanged hospital-level outcomes during the COVID-19 pandemic. Although the impact on use varied by condition, the most notable declines were related to inpatient admissions for respiratory conditions, including asthma, bronchiolitis, and pneumonia.

What’s Known on This Subject:

After the US declaration of a national emergency for the coronavirus disease 2019 pandemic, studies reported declines in pediatric emergency department visits and delayed presentations across health care settings for several conditions (eg, diabetes), leading to increased complication rates (eg, severe diabetic ketoacidosis).

What This Study Adds:

This study of US children’s hospitals revealed a near 40% reduction in pediatric inpatient admissions during the coronavirus disease 2019 pandemic, with even greater declines observed for some specific diagnoses compared with the same time frame in previous years.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, emerged as a global threat in early 2020 and has impacted patients and health systems. As the incidence of COVID-19 cases rose, reports of delays in access to emergency medical services and reductions in the provision of hospital care for non– COVID-related medical problems emerged.16  These delays or avoidances in care were associated with poorer health outcomes (eg, adults with myocardial infarction experienced more in-hospital complications when care was delayed).7  Social isolation recommendations coupled with public concern regarding risk of exposure while visiting health care facilities during the pandemic also contributed to these declines.3,4  At a systems level, changes in health care use during the COVID-19 pandemic led to fiscal strain and staffing concerns across hospitals and health care systems.810 

As the scope of the pandemic became apparent, a national emergency was declared and stay-at-home orders were issued in the United States in March 2020. Within weeks of this declaration, Hartnett et al11  observed a substantial decline of 42% in emergency department (ED) visits compared with the same time period the previous year, with greater reductions among children compared with adults. Declines in ED use were similarly observed across continents within 3 weeks of the start of the pandemic, with continued declines in use experienced 5 months later.12  Other studies reported delayed presentations of specific pediatric conditions, such as solid tumors, diagnosis of new onset diabetes leading to increased incidence of diabetic ketoacidosis, and increased complications related to appendicitis.1315  However, the broader impact of the COVID-19 pandemic on pediatric hospitalizations nationally and associated outcomes have not been described.

Better understanding the effects of the pandemic on children’s health care use may help inform policy makers and guide hospitals on potential interventions to impact health care access. Thus, the objective of this current study was to describe the impact of the COVID-19 pandemic on US pediatric inpatient admissions and hospital use. We hypothesized that we would observe reductions in overall pediatric hospital use but that these reductions may vary by condition.

This multicenter, cross-sectional study of hospitalized children (inpatient and observation status stays) used the Pediatric Health Information System (PHIS). PHIS is an administrative database of 49 tertiary care pediatric hospitals affiliated with the Children’s Hospital Association (Lenexa, KS). The PHIS database includes patient-level data, including demographic data, diagnosis and procedural codes, and resource use (eg, laboratory and diagnostic imaging). Encryption of patient identifiers allows for tracking of individual patients across multiple hospital visits. Four hospitals were excluded for data quality issues, including failure to report billing data through the end of the study period and for length of stay (LOS) data not reported in hours; the remaining 45 hospitals were included.

In the overall cohort, we included children 0 to 18 years of age with an index hospitalization (medical or surgical) at a PHIS-participating hospital. We excluded birth hospitalizations and maternal obstetrical hospitalizations because most of these stays are not related to acute illness, and children’s hospitals have variable admission practices for these patients. We excluded transfers in and out of children’s hospitals, those who left against medical advice, and hospitalizations with data quality concerns because of the inability to capture use data for the entire episode of care and readmission period. We excluded children with a complex chronic condition to identify a generally healthy cohort of children who would be of similar risk of hospitalization and readmission.16  Finally, because we were examining hospitalizations and readmissions across different years, we included only the first admission and readmission (if one occurred) per patient within a given index year and excluded subsequent readmissions within the same year as the index admission year.

The COVID-19 period was defined as index hospitalizations and discharges occurring between March 15, 2020, and August 29, 2020. Notably, the beginning of the COVID-19 period corresponded approximately to the US declaration of a national emergency, which occurred on March 13, 2020. Index admissions that occurred after August 29th were excluded from analyses to allow a full 30-day readmission window. To define the pre-COVID-19 period, we examined hospitalizations during the same time frame within the preceding 3 years (ie, March 15 to August 29 of 2017, 2018, and 2019). To account for fluctuations in inpatient admissions and severity of diseases across seasons and years, we describe the pre-COVID-19 period using the median number of inpatient admissions for the preceding 3 years of hospitalizations. Because we examined the same dates over multiple years, we normalized all dates using 7-day increments (ie, day of the week was not considered in describing weeks).

In addition to describing overall hospitalizations, we describe hospitalizations for 15 selected medical All Patient Refined Diagnosis Related Groups (APR-DRGs) (version 36; 3M Corporation, St Paul, MN). We defined hospitalizations within remaining APR-DRG categories as “all other.” APR-DRGs are a patient classification scheme that groups patients on the basis of the principal diagnosis for medical patients and incorporates severity of illness and risk of mortality by using demographics and comorbidities.17  Individual APR-DRG categories were chosen on the basis of prevalence within the top 80% of discharges annually and/or frequency of admissions across a majority of hospitals during the study period (eg, APR-DRGs with admissions in >90% of included hospitals, Supplemental Table 4). Within the COVID-19 period, we also describe the number of children hospitalized with COVID-19.

Our primary outcome was the number of inpatient admissions. In addition to examining numbers of admissions, we identified a group of clinical and financial outcomes. The clinical outcomes included LOS measured in hours, 14- and 30-day readmission rates within the same major diagnostic category, ICU use, mortality, and mechanical ventilation. We examined LOS for the index admission and the total episode of care (index and readmission) and describe the days between index admissions and readmissions. Both initial ICU use (ie, admission to the ICU on day 0) and any ICU use were examined. The financial outcomes included standardized costs in US dollars for the index hospitalization and the total episode of care (index hospitalization and any readmission). Standardized costs remove the high interhospital variation in item costs and thus allow for a meaningful comparison of resource use and costs across hospitals. We used previously described methods for calculating standardized costs using billing data.17  In PHIS, standardized unit costs are calculated yearly, and, for this analysis, standardized costs from previous years were inflated to 2020 dollars by using the medical component of the consumer price index.

We examined demographic characteristics, including age, sex, race and ethnicity, primary payer, and median household income quartile. Race and ethnicity was included as a covariate within analyses because authors of multiple studies have reported the differential impacts of the COVID-19 pandemic based on race and ethnicity.1821  Race and ethnicity data are collected at the patient-level within PHIS. We examined patient characteristics, including the number of noncomplex chronic conditions and the mean Hospitalization Resource Intensity Score for Kids (H-RISK).22  Noncomplex chronic conditions were identified by using the Healthcare Cost and Utilization Project chronic condition indicator, and patients were classified on the basis of the number of chronic conditions.23  The chronic condition indicator describes conditions that last ≥12 months and result in the need for ongoing health care services. H-RISK was developed to quantify severity of illness among hospitalized children and assigns relative weights to each APR-DRG and severity of illness level, facilitating comparison across APR-DRG groups. We also examined hospitalization characteristics, including hospital region and source of admission (through the individual hospital’s ED versus direct admission).

Descriptive statistics described demographic, patient, and hospital characteristics. A χ2 test compared differences in categorical characteristics and unadjusted outcomes between pre-COVID-19 and COVID-19 periods. A Wilcoxon rank test compared nonnormally distributed continuous variables between the COVID-19 and pre-COVID-19 eras, and an independent Student’s t test compared normally distributed continuous variables. Generalized linear mixed models (GLMMs) were used to examine the association of COVID-19 period and outcomes, adjusting for age, race and ethnicity, payer, median household income, presence of a chronic condition, admission through the ED, census region, and severity. GLMMs for readmission assumed an underlying binomial distribution and a logit link; GLMMs for LOS and cost assumed underlying log-linear distribution. All GLMMs included a random hospital effect to account for clustering. In a subanalysis, we divided the COVID-19 period into early (March 15 to May 31, 2020) and extended (June 1 to August 29, 2020) periods to assess for differences in outcomes over time. All statistical analyses were performed by using SAS 9.4 (SAS Institute, Inc, Cary, NC), and P values <.001 were considered statistically significant. The Office of Research Integrity at Children’s Mercy Kansas City (Kansas City, MO) deemed this study using deidentified data exempt from institutional board review.

Our study included a total of 516 388 hospitalizations for 501 459 children, of which 424 856 hospitalizations occurred in the pre-COVID-19 period (mean: 141 619 hospitalizations per year) and 91 532 hospitalizations in the COVID-9 period (Table 1, Supplemental Fig 2, and Supplemental Table 5 present pre-COVID-19 characteristics by year). During the COVID-19 period, we observed declines in the percentage of all hospitalizations classified as medical hospitalizations (pre-COVID-19: 76.2%; COVID-19: 72.4%). Overall, demographic and patient characteristics were similar between periods, with some small differences observed. For example, we observed a decreased proportion of hospitalizations during the COVID-19 period for children 1 to 9 years of age (Table 1). Small differences were also observed for patient characteristics, such as number of chronic conditions, with higher rates of hospitalizations observed during the COVID-19 period for children with no chronic conditions and for those with ≥2 chronic conditions. The mean H-RISK was greater among children presenting in the COVID-19 period (0.734 vs 0.642, P < .001). A total of 1062 children (1.2% of hospitalizations in the COVID-19 period) had COVID-19, with the majority of hospitalizations mapped to APR-DRG 137 (major respiratory infections). The 15 specific medical APR-DRG categories examined accounted for 37.4% of all hospitalizations (2017 N = 54 231; 2018 N = 54 307; 2019 N = 57 818; 2020 N = 26 585).

TABLE 1

Clinical and Demographic Characteristics

OverallPre-COVID-19COVID-19
Index admissions 516 388 424 856 91 532 
 Medical 390 069 (75.5) 323 845 (76.2) 66 224 (72.4) 
 Surgical 126 319 (24.5) 101 011 (23.8) 25 308 (27.6) 
Age at index admission, y    
 <1 110 335 (21.4) 90 470 (21.3) 19 865 (21.7) 
 1–4 138 247 (26.8) 117 553 (27.7) 20 694 (22.6) 
 5–9 99 923 (19.4) 83 379 (19.6) 16 544 (18.1) 
 10–14 100 659 (19.5) 80 748 (19.0) 19 911 (21.8) 
 15–18 67 224 (13.0) 52 706 (12.4) 14 518 (15.9) 
Sex    
 Female 237 175 (45.9) 193 917 (45.6) 43 258 (47.3) 
 Male 278 883 (54.0) 230 679 (54.3) 48 204 (52.7) 
 Missing 330 (0.1) 260 (0.1) 70 (0.1) 
Payer    
 Government 286 149 (55.4) 236 379 (55.6) 49 770 (54.4) 
 Private 201 635 (39.0) 165 742 (39.0) 35 893 (39.2) 
 Self-pay 13 394 (2.6) 10 271 (2.4) 3123 (3.4) 
 Other 15 210 (2.9) 12 464 (2.9) 2746 (3.0) 
Race    
 Non-Hispanic white 249 171 (48.3) 203 882 (48.0) 45 289 (49.5) 
 Non-Hispanic Black 97 372 (18.9) 81 516 (19.2) 15 856 (17.3) 
 Hispanic 111 412 (21.6) 91 162 (21.5) 20 250 (22.1) 
 Other 58 433 (11.3) 48 296 (11.4) 10 137 (11.1) 
Median household income    
 Quartile 1 125 464 (24.3) 103 760 (24.4) 21 704 (23.7) 
 Quartile 2 123 913 (24.0) 102 048 (24.0) 21 865 (23.9) 
 Quartile 3 127 445 (24.7) 104 529 (24.6) 22 916 (25.0) 
 Quartile 4 128 952 (25.0) 105 705 (24.9) 23 247 (25.4) 
 Missing 10 614 (2.1) 8814 (2.1) 1800 (2.0) 
Chronic conditions    
 0 254 350 (49.3) 208 693 (49.1) 45 657 (49.9) 
 1 178 398 (34.5) 148 529 (35.0) 29 869 (32.6) 
 2–3 77 873 (15.1) 63 146 (14.9) 14 727 (16.1) 
 ≥4 5767 (1.1) 4488 (1.1) 1279 (1.4) 
Hospital region    
 Midwest 140 659 (27.2) 116 627 (27.5) 24 032 (26.3) 
 Northeast 65 791 (12.7) 53 932 (12.7) 11 859 (13.0) 
 South 205 393 (39.8) 169 404 (39.9) 35 989 (39.3) 
 West 104 545 (20.2) 84 893 (20.0) 19 652 (21.5) 
H-RISK 0.658 (0.001) 0.642 (0.001) 0.734 (0.003) 
Admission source    
 Direct admission 169 955 (32.9) 139 649 (32.9) 30 306 (33.1) 
 ED 346 433 (67.1) 285 207 (67.1) 61 226 (66.9) 
OverallPre-COVID-19COVID-19
Index admissions 516 388 424 856 91 532 
 Medical 390 069 (75.5) 323 845 (76.2) 66 224 (72.4) 
 Surgical 126 319 (24.5) 101 011 (23.8) 25 308 (27.6) 
Age at index admission, y    
 <1 110 335 (21.4) 90 470 (21.3) 19 865 (21.7) 
 1–4 138 247 (26.8) 117 553 (27.7) 20 694 (22.6) 
 5–9 99 923 (19.4) 83 379 (19.6) 16 544 (18.1) 
 10–14 100 659 (19.5) 80 748 (19.0) 19 911 (21.8) 
 15–18 67 224 (13.0) 52 706 (12.4) 14 518 (15.9) 
Sex    
 Female 237 175 (45.9) 193 917 (45.6) 43 258 (47.3) 
 Male 278 883 (54.0) 230 679 (54.3) 48 204 (52.7) 
 Missing 330 (0.1) 260 (0.1) 70 (0.1) 
Payer    
 Government 286 149 (55.4) 236 379 (55.6) 49 770 (54.4) 
 Private 201 635 (39.0) 165 742 (39.0) 35 893 (39.2) 
 Self-pay 13 394 (2.6) 10 271 (2.4) 3123 (3.4) 
 Other 15 210 (2.9) 12 464 (2.9) 2746 (3.0) 
Race    
 Non-Hispanic white 249 171 (48.3) 203 882 (48.0) 45 289 (49.5) 
 Non-Hispanic Black 97 372 (18.9) 81 516 (19.2) 15 856 (17.3) 
 Hispanic 111 412 (21.6) 91 162 (21.5) 20 250 (22.1) 
 Other 58 433 (11.3) 48 296 (11.4) 10 137 (11.1) 
Median household income    
 Quartile 1 125 464 (24.3) 103 760 (24.4) 21 704 (23.7) 
 Quartile 2 123 913 (24.0) 102 048 (24.0) 21 865 (23.9) 
 Quartile 3 127 445 (24.7) 104 529 (24.6) 22 916 (25.0) 
 Quartile 4 128 952 (25.0) 105 705 (24.9) 23 247 (25.4) 
 Missing 10 614 (2.1) 8814 (2.1) 1800 (2.0) 
Chronic conditions    
 0 254 350 (49.3) 208 693 (49.1) 45 657 (49.9) 
 1 178 398 (34.5) 148 529 (35.0) 29 869 (32.6) 
 2–3 77 873 (15.1) 63 146 (14.9) 14 727 (16.1) 
 ≥4 5767 (1.1) 4488 (1.1) 1279 (1.4) 
Hospital region    
 Midwest 140 659 (27.2) 116 627 (27.5) 24 032 (26.3) 
 Northeast 65 791 (12.7) 53 932 (12.7) 11 859 (13.0) 
 South 205 393 (39.8) 169 404 (39.9) 35 989 (39.3) 
 West 104 545 (20.2) 84 893 (20.0) 19 652 (21.5) 
H-RISK 0.658 (0.001) 0.642 (0.001) 0.734 (0.003) 
Admission source    
 Direct admission 169 955 (32.9) 139 649 (32.9) 30 306 (33.1) 
 ED 346 433 (67.1) 285 207 (67.1) 61 226 (66.9) 

Data are presented as n (%) with the exception of H-RISK, which is presented as mean (SD). All comparisons between pre-COVID-19 and COVID-19 periods are significant at P < .001, except for admission source.

Compared with the median number of inpatient admissions in the pre-COVID-19 period, the overall admissions were reduced 35.1% during the COVID-19 period. Admissions began to decline after the 10th week of the year, corresponding to March 11 to 17 (Fig 1). The most substantial reductions in overall admissions were observed at approximately the 15th week of the year (April 8 to 14). By the end of the study period, overall admissions remained below pre-COVID-19 numbers.

FIGURE 1

Trends in numbers of inpatient admissions during the pre-COVID-19 versus COVID-19 periods. GI, gastrointestinal.

FIGURE 1

Trends in numbers of inpatient admissions during the pre-COVID-19 versus COVID-19 periods. GI, gastrointestinal.

Close modal

Inpatient admissions varied across the 15 specific APR-DRGs, with declines in hospital admissions during COVID-19 ranging from 8.5% to 81.3% compared with median admissions in the pre-COVID-19 period. The largest reductions were observed for asthma (81.3% reduction), bronchiolitis (80.1% reduction), pneumonia (71.4% reduction), and upper respiratory tract infections (URTIs) (68.9% reduction). The smallest admission reductions were observed for diabetes (8.5% reduction) and urinary tract infections (14.2% reduction).

In examinations of trends over time, we observed that changes in inpatient admissions varied by APR-DRG (Fig 1). Diagnoses such as diabetes and seizure experienced substantial initial declines with return toward pre-COVID-19 numbers of admissions between weeks 18 and 24, whereas diagnoses such as asthma, bronchiolitis, pneumonia, URTI, and nonbacterial gastroenteritis experienced sustained declines through the end of the study period.

Overall adjusted LOS (index and total) and costs were similar during the COVID-19 period compared with the pre-COVID-19 period (Table 2). ICU use, mortality, and mechanical ventilation also remained similar between time periods, although adjusted readmission rates were lower during the COVID-19 period at both 14 and 30 days. Unadjusted outcomes are presented within Supplemental Table 6. In a subanalysis of the early versus extended COVID-19 period, LOS and ICU use were slightly higher during the early COVID-19 period (Supplemental Table 7).

TABLE 2

Overall Adjusted Clinical and Financial Outcomes

Pre-COVID-19COVID-19P
LOS, geometric mean (99.9% CI)    
 Index admission, h 44.9 (42.3–47.7) 44.4 (41.8–47.2) <.001 
 Total episode of care, h 47.5 (44.7–50.4) 46.8 (44.1–49.8) <.001 
 Days between index admission and readmission 9.0 (8.3–9.7) 9.0 (8.2–9.8) .93 
Readmission rates (99.9% CI), %    
 14 d 3.2 (2.8–3.5) 2.9 (2.6–3.3) <.001 
 30 d 4.9 (4.4–5.4) 4.5 (4.0–5.0) <.001 
Geometric mean cost (99.9% CI), $ (US dollars)    
 Index admission 6038 (5252–6942) 6174 (5369–7098) <.001 
 Total episode of care 6345 (5514–7300) 6473 (5624–7449) <.001 
ICU use (99.9% CI), %    
 Any ICU 8.9 (6.9–11.2) 8.8 (6.9–11.2) .56 
 ICU on day 0 7.9 (6.2–10.0) 8.0 (6.3–10.1) .29 
Mechanical ventilation (99.9% CI), % 1.6 (1.1–2.1) 1.5 (1.1–2.0) .07 
Mortality (99.9% CI), %    
 Index admission 0.0 (0.0–0.1) 0.0 (0.0–0.1) .08 
 Total episode of care 0.0 (0.0–0.1) 0.0 (0.0–0.1) .06 
Pre-COVID-19COVID-19P
LOS, geometric mean (99.9% CI)    
 Index admission, h 44.9 (42.3–47.7) 44.4 (41.8–47.2) <.001 
 Total episode of care, h 47.5 (44.7–50.4) 46.8 (44.1–49.8) <.001 
 Days between index admission and readmission 9.0 (8.3–9.7) 9.0 (8.2–9.8) .93 
Readmission rates (99.9% CI), %    
 14 d 3.2 (2.8–3.5) 2.9 (2.6–3.3) <.001 
 30 d 4.9 (4.4–5.4) 4.5 (4.0–5.0) <.001 
Geometric mean cost (99.9% CI), $ (US dollars)    
 Index admission 6038 (5252–6942) 6174 (5369–7098) <.001 
 Total episode of care 6345 (5514–7300) 6473 (5624–7449) <.001 
ICU use (99.9% CI), %    
 Any ICU 8.9 (6.9–11.2) 8.8 (6.9–11.2) .56 
 ICU on day 0 7.9 (6.2–10.0) 8.0 (6.3–10.1) .29 
Mechanical ventilation (99.9% CI), % 1.6 (1.1–2.1) 1.5 (1.1–2.0) .07 
Mortality (99.9% CI), %    
 Index admission 0.0 (0.0–0.1) 0.0 (0.0–0.1) .08 
 Total episode of care 0.0 (0.0–0.1) 0.0 (0.0–0.1) .06 

Total episode of care = index admission and readmission.

Index (adjusted ratio of means [aRM] 0.86–0.88, all P < .0001) and total episode of care LOS (aRM 0.85–0.89, all P < .0001) were shorter during the COVID-19 period for bronchiolitis, asthma, pulmonary edema and respiratory failure, and other gastrointestinal diagnoses, although absolute differences in LOS were small (Table 3). URTI was the only condition associated with longer index (aRM 1.12 [99.9% confidence interval (CI) 1.04–1.20]) and total episode of care LOS (aRM 1.10 [99.9% CI 1.02–1.19]) during the COVID-19 period. ICU use was lower during COVID-19 for bronchiolitis. Readmissions were similar during pre-COVID-19 and COVID-19 periods for all APR-DRG categories.

TABLE 3

Adjusted Clinical and Financial Outcomes by APR-DRG

APR-DRGIndex LOSTotal LOSReadmission, 14 dReadmission, 30 dCostICU Use
Ratio (99.9% CI)PRatio (99.9% CI)PRatio (99.9% CI)PRatio (99.9% CI)PRatio (99.9% CI)PRatio (99.9% CI)P
Seizure 0.97 (0.94–1.01) .005 0.97 (0.93–1.01) .0006 0.83 (0.55–1.25) .07 0.89 (0.65–1.20) .12 0.96 (0.92–1.01) .002 0.96 (0.72–1.28) .54 
URTI 1.12 (1.04–1.20) <.0001 1.10 (1.02–1.19) <.0001 0.73 (0.33–1.60) .11 0.75 (0.40–1.42) .07 1.13 (1.05–1.22) <.0001 0.76 (0.39–1.48) .10 
Pulmonary edema and respiratory failure 0.91 (0.84–0.98) <.0001 0.89 (0.82–0.97) <.0001 0.68 (0.23–2.03) .16 0.42 (0.16–1.10) .0003 0.90 (0.83–0.98) <.0001 1.03 (0.72–1.47) .73 
Bronchiolitis 0.84 (0.78–0.91) <.0001 0.82 (0.76–0.89) <.0001 0.65 (0.27–1.58) .05 0.50 (0.24–1.04) .0001 0.86 (0.80–0.94) <.0001 0.53 (0.32–0.85) <.0001 
Pneumonia 0.93 (0.86–1.01) .0007 0.92 (0.85–1.01) .0002 0.73 (0.25–2.09) .22 0.59 (0.23–1.50) .02 0.94 (0.87–1.02) .005 0.76 (0.43–1.36) .06 
Asthma 0.92 (0.88–0.97) <.0001 0.93 (0.88–0.98) <.0001 1.20 (0.51–2.81) .39 1.00 (0.52–1.91) .99 0.92 (0.87–0.97) <.0001 0.75 (0.51–1.08) .002 
Nonbacterial gastroenteritis 1.00 (0.94–1.06) .91 1.02 (0.96–1.10) .18 1.44 (0.90–2.32) .002 1.42 (0.94–2.14) .0007 1.07 (1.01–1.14) <.0001 1.38 (0.56–3.39) .15 
Other GI diagnoses 0.93 (0.88–0.99) <.0001 0.93 (0.87–0.99) <.0001 0.73 (0.43–1.25) .02 0.86 (0.57–1.29) .14 1.03 (0.97–1.09) .06 1.52 (0.86–2.69) .003 
Cellulitis 0.98 (0.93–1.03) .16 0.98 (0.93–1.04) .24 1.07 (0.57–1.99) .69 1.05 (0.61–1.81) .73 1.00 (0.95–1.06) .79 1.73 (0.62–4.88) .03 
Diabetes 0.99 (0.95–1.03) .24 0.99 (0.95–1.03) .23 0.92 (0.33–2.61) .75 0.91 (0.43–1.94) .62 0.96 (0.93–1.00) .0004 1.09 (0.83–1.45) .20 
Malnutrition 0.95 (0.85–1.06) .04 0.94 (0.83–1.05) .02 0.91 (0.44–1.89) .60 0.83 (0.46–1.48) .19 0.92 (0.82–1.03) .004 1.32 (0.64–2.72) .13 
Hypovolemia 0.99 (0.92–1.07) .64 1.00 (0.92–1.08) .99 1.05 (0.53–2.09) .78 1.14 (0.64–2.03) .36 1.05 (0.97–1.13) .01 0.90 (0.24–3.38) .74 
Urinary tract infection 0.95 (0.90–1.01) .002 0.96 (0.90–1.02) .006 0.86 (0.41–1.84) .44 1.06 (0.62–1.80) .67 0.99 (0.94–1.05) .73 1.68 (0.81–3.51) .005 
Anemia 0.98 (0.89–1.08) .51 1.00 (0.90–1.11) .94 1.05 (0.50–2.18) .79 1.12 (0.60–2.09) .47 1.02 (0.92–1.13) .38 1.14 (0.58–2.26) .43 
Other health 0.95 (0.88–1.02) .006 0.94 (0.86–1.02) .002 0.79 (0.39–1.60) .18 0.81 (0.46–1.45) .15 0.94 (0.86–1.03) .008 0.88 (0.50–1.56) .37 
All other APR-DRG 0.97 (0.96–0.99) <.0001 0.97 (0.96–0.98) <.0001 0.89 (0.80–0.99) <.0001 0.90 (0.82–0.98) <.0001 0.99 (0.98–1.01) .02 1.07 (1.00–1.14) <.0001 
APR-DRGIndex LOSTotal LOSReadmission, 14 dReadmission, 30 dCostICU Use
Ratio (99.9% CI)PRatio (99.9% CI)PRatio (99.9% CI)PRatio (99.9% CI)PRatio (99.9% CI)PRatio (99.9% CI)P
Seizure 0.97 (0.94–1.01) .005 0.97 (0.93–1.01) .0006 0.83 (0.55–1.25) .07 0.89 (0.65–1.20) .12 0.96 (0.92–1.01) .002 0.96 (0.72–1.28) .54 
URTI 1.12 (1.04–1.20) <.0001 1.10 (1.02–1.19) <.0001 0.73 (0.33–1.60) .11 0.75 (0.40–1.42) .07 1.13 (1.05–1.22) <.0001 0.76 (0.39–1.48) .10 
Pulmonary edema and respiratory failure 0.91 (0.84–0.98) <.0001 0.89 (0.82–0.97) <.0001 0.68 (0.23–2.03) .16 0.42 (0.16–1.10) .0003 0.90 (0.83–0.98) <.0001 1.03 (0.72–1.47) .73 
Bronchiolitis 0.84 (0.78–0.91) <.0001 0.82 (0.76–0.89) <.0001 0.65 (0.27–1.58) .05 0.50 (0.24–1.04) .0001 0.86 (0.80–0.94) <.0001 0.53 (0.32–0.85) <.0001 
Pneumonia 0.93 (0.86–1.01) .0007 0.92 (0.85–1.01) .0002 0.73 (0.25–2.09) .22 0.59 (0.23–1.50) .02 0.94 (0.87–1.02) .005 0.76 (0.43–1.36) .06 
Asthma 0.92 (0.88–0.97) <.0001 0.93 (0.88–0.98) <.0001 1.20 (0.51–2.81) .39 1.00 (0.52–1.91) .99 0.92 (0.87–0.97) <.0001 0.75 (0.51–1.08) .002 
Nonbacterial gastroenteritis 1.00 (0.94–1.06) .91 1.02 (0.96–1.10) .18 1.44 (0.90–2.32) .002 1.42 (0.94–2.14) .0007 1.07 (1.01–1.14) <.0001 1.38 (0.56–3.39) .15 
Other GI diagnoses 0.93 (0.88–0.99) <.0001 0.93 (0.87–0.99) <.0001 0.73 (0.43–1.25) .02 0.86 (0.57–1.29) .14 1.03 (0.97–1.09) .06 1.52 (0.86–2.69) .003 
Cellulitis 0.98 (0.93–1.03) .16 0.98 (0.93–1.04) .24 1.07 (0.57–1.99) .69 1.05 (0.61–1.81) .73 1.00 (0.95–1.06) .79 1.73 (0.62–4.88) .03 
Diabetes 0.99 (0.95–1.03) .24 0.99 (0.95–1.03) .23 0.92 (0.33–2.61) .75 0.91 (0.43–1.94) .62 0.96 (0.93–1.00) .0004 1.09 (0.83–1.45) .20 
Malnutrition 0.95 (0.85–1.06) .04 0.94 (0.83–1.05) .02 0.91 (0.44–1.89) .60 0.83 (0.46–1.48) .19 0.92 (0.82–1.03) .004 1.32 (0.64–2.72) .13 
Hypovolemia 0.99 (0.92–1.07) .64 1.00 (0.92–1.08) .99 1.05 (0.53–2.09) .78 1.14 (0.64–2.03) .36 1.05 (0.97–1.13) .01 0.90 (0.24–3.38) .74 
Urinary tract infection 0.95 (0.90–1.01) .002 0.96 (0.90–1.02) .006 0.86 (0.41–1.84) .44 1.06 (0.62–1.80) .67 0.99 (0.94–1.05) .73 1.68 (0.81–3.51) .005 
Anemia 0.98 (0.89–1.08) .51 1.00 (0.90–1.11) .94 1.05 (0.50–2.18) .79 1.12 (0.60–2.09) .47 1.02 (0.92–1.13) .38 1.14 (0.58–2.26) .43 
Other health 0.95 (0.88–1.02) .006 0.94 (0.86–1.02) .002 0.79 (0.39–1.60) .18 0.81 (0.46–1.45) .15 0.94 (0.86–1.03) .008 0.88 (0.50–1.56) .37 
All other APR-DRG 0.97 (0.96–0.99) <.0001 0.97 (0.96–0.98) <.0001 0.89 (0.80–0.99) <.0001 0.90 (0.82–0.98) <.0001 0.99 (0.98–1.01) .02 1.07 (1.00–1.14) <.0001 

Ratio refers to adjusted odds ratio or aRM. “All other” refers to all other APR-DRG categories combined. A Bonferroni correction for 16 comparisons was applied to determine statistical significance. GI, gastrointestinal.

Costs of care were lower during the COVID-19 period for 3 specific APR-DRGs, including bronchiolitis (aRM 0.86 [99.9% CI 0.80–0.94]), pulmonary edema and respiratory failure (aRM 0.90 [99.9% CI 0.83–0.98]), and asthma (aRM 0.92 [99.9% CI 0.87–0.97]). Costs were higher for infections of the upper respiratory tract (aRM 1.13 [99.9% CI 1.05–1.22]) and nonbacterial gastroenteritis (aRM 1.07 [99.9% CI 1.01–1.14]).

In this multicenter study of pediatric hospitalizations, we observed considerable reductions in use during the COVID-19 pandemic, as seen by overall inpatient admissions declining nearly 40%. Despite reductions in overall admissions, the overall clinical and financial outcomes were similar between COVID-19 and pre-COVID-19 periods. In assessments of use by APR-DRG, we observed considerable variation in inpatient admissions by diagnosis between the two time periods, with notable declines for the common pediatric conditions of asthma, bronchiolitis, and pneumonia. Many of the reductions to inpatient admissions were sustained through the end of the study period.

Similar to global reports of decreased health care use during the early pandemic, we observed substantial declines in pediatric inpatient admissions among generally healthy children compared with previous years, especially in the early pandemic period. These data align with a study of hospitalization and ICU admissions from 5 pediatric hospitals around the world, in which researchers noted a 32% to 49% decrease in hospitalization rates and a 12% to 38% decrease in ICU admission (with the exception of a hospital in Paris, at which admissions increased by 2%) during the first 6 weeks of the pandemic.12  In a study of ED resource use within the United States, Hartnett et al11  reported substantial declines in ED visits, with the greatest reductions observed for children ≤14 years of age in age-stratified analyses. Similarly, Wilder et al24  describe declines in overall hospitalizations per week at a single tertiary care pediatric hospital. The substantial reductions that we observed likely reflect a complex interplay of factors, including, among others, the influence of fear on health-seeking behavior, adherence to social distancing policies, knowledge about when to seek health care, and the impact of social distancing and school closures on transmission of respiratory infections.

The greatest declines in inpatient admissions we observed were for asthma, bronchiolitis, pneumonia, and URTIs. Although reductions in hospitalizations for some specific APR-DRGs, such as asthma, may be expected with the provision of high-quality ambulatory pediatric care (eg, ambulatory care sensitive conditions), we observed declines greater than expected across many APR-DRG categories, and the degree of impact was not consistently observed across other ambulatory care sensitive conditions (eg, diabetes stays were reduced only 8.5% during the COVID-19 period). Our observation of declines in inpatient care for many infections and infection-mediated diseases (eg, asthma) are consistent with other studies in which researchers examined ED and inpatient resource use during COVID-19, including asthma, croup, bronchiolitis, and pneumonia.2426  Notably, the specific conditions with the greatest declines in our study are all conditions that may be affected by changes in community viral and bacterial transmission. Thus, social distancing and policies including school closures may have had a cumulative impact on declines in admissions in addition to the factors described above.

With overall patient and caregiver avoidance of health care facilities during the pandemic, one might expect a delay in presentation, leading to patients who are potentially sicker being admitted and worse patient outcomes (eg, increased ICU use). Previous studies of the COVID-19 pandemic in children have reported delayed presentations of pediatric solid tumors, diagnosis of new onset diabetes leading to increased incidence of diabetic ketoacidosis, and increased complications related to appendicitis.1315  Although the mean H-RISK (used as a proxy for severity of illness) was higher during the COVID-19 period in our study, we did not observe many differences in overall clinical outcomes (eg, ICU use) among previously healthy children when looking across the entire COVID-19 period compared with the pre-COVID-19 period, with the exception of fewer readmissions. Notably, ICU use was higher during the early compared with extended COVID-19 period, although other outcomes including LOS, readmission rates, mortality, and mechanical ventilation use remained similar during this early period. Overall reductions in inpatient admissions may have contributed to more focused care and improved hospital flow and/or reduced readmissions for admitted children; however, other factors including staffing changes could have also contributed, and future studies exploring these factors may shed further light on our observations.

Although differences in overall outcomes were small, when we examine outcomes by APR-DRG some important differences did emerge. Whereas several infection and infection-related conditions experienced reductions in inpatient use (eg, declines in LOS and costs for respiratory syncytial virus bronchiolitis and asthma), children with URTIs experienced longer LOS. Focused investigations of factors that contributed to differential outcomes for these subsets of infection and infection-mediated diseases may identify opportunities to mobilize ambulatory resources in future pandemics.

Our findings should be interpreted within the context of several limitations. First, in this study we used administrative data and errors in billing and coding could contribute to misclassification bias. Because PHIS is rigorously monitored for any data quality issues, the impact of misclassification bias is expected to be small. Differences in the prevalence of COVID-19 within individual communities could have also impacted some of the variability we observed. Previous reports describe the impact of the COVID-19 pandemic on socioeconomic factors, including an increased proportion of publicly insured individuals. Finally, within our models, we adjusted for sociodemographic and clinical factors, including payer, which may have adjusted away some of the indirect effects of the pandemic by biasing our results toward the null.

This study of US children’s hospitals revealed overall reductions in pediatric inpatient admissions, with substantial reductions observed for many infections and infectious-mediated processes (eg, asthma). Although we observed small reductions in overall LOSs, ICU use, and readmission rates during the early COVID-19 pandemic compared with the same time frame in previous years, the impact by diagnosis was variable.

Dr Markham directed the study design, analysis, and interpretation of the data and wrote the first draft of the manuscript, providing critical intellectual content throughout the study; Dr Richardson performed all statistical analyses, participated in the study design and interpretation of the data, and provided critical intellectual content in the revision of the manuscript; Drs DePorre, Teufel, Hersh, Fleegler, Antiel, Williams, and Goldin participated in the study design, analysis, and interpretation of the data and provided critical intellectual content in the revision of the manuscript; Dr Shah supervised the study design, analysis, and interpretation of the data and provided critical intellectual content in the revision of the manuscript; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: No external funding.

     
  • APR-DRG

    All Patient Refined Diagnosis Related Group

  •  
  • aRM

    adjusted ratio of means

  •  
  • CI

    confidence interval

  •  
  • COVID-19

    coronavirus disease 2019

  •  
  • ED

    emergency department

  •  
  • GLMM

    generalized linear mixed model

  •  
  • H-RISK

    Hospitalization Resource Intensity Score for Kids

  •  
  • LOS

    length of stay

  •  
  • PHIS

    Pediatric Health Information System

  •  
  • URTI

    upper respiratory tract infection

1
Metzler
B
,
Siostrzonek
P
,
Binder
RK
,
Bauer
A
,
Reinstadler
SJ
.
Decline of acute coronary syndrome admissions in Austria since the outbreak of COVID-19: the pandemic response causes cardiac collateral damage
.
Eur Heart J
.
2020
;
41
(
19
):
1852
1853
2
Tam
CF
,
Cheung
KS
,
Lam
S
, et al
.
Impact of coronavirus disease 2019 (COVID-19) outbreak on ST-segment-elevation myocardial infarction care in Hong Kong, China
.
Circ Cardiovasc Qual Outcomes
.
2020
;
13
(
4
):
e006631
3
Lazzerini
M
,
Barbi
E
,
Apicella
A
,
Marchetti
F
,
Cardinale
F
,
Trobia
G
.
Delayed access or provision of care in Italy resulting from fear of COVID-19
.
Lancet Child Adolesc Health
.
2020
;
4
(
5
):
e10
e11
4
Wong
LE
,
Hawkins
JE
,
Langness
S
,
Murrell
KL
,
Iris
P
,
Sammann
A
.
Where are all the patients? Addressing covid-19 fear to encourage sick patients to seek emergency care
.
NEJM Catal Innov Care Deliv
.
2020
.
Available at: https://catalyst.nejm.org/doi/full/10.1056/CAT.20.0193. Accessed August 11, 2020
5
Molina Gutiérrez
,
Ruiz Domínguez
JA
,
Bueno Barriocanal
M
, et al
.
Impacto de la pandemia COVID-19 en urgencias: primeros hallazgos en un hospital de Madrid [Impact of the COVID-19 pandemic on emergency department: early findings from a hospital in Madrid]
.
An Pediatr (Barc)
.
2020
;
93
(
5
):
313
322
6
Kim
HS
,
Cruz
DS
,
Conrardy
MJ
, et al
.
Emergency department visits for serious diagnoses during the COVID-19 pandemic
.
Acad Emerg Med
.
2020
;
27
(
9
):
910
913
7
Tam
C-CF
,
Cheung
K-S
,
Lam
S
, et al
.
Impact of coronavirus disease 2019 (COVID-19) outbreak on outcome of myocardial infarction in Hong Kong, China
.
Catheter Cardiovasc Interv
.
2021
;
97
(
2
):
E194
E197
8
Hamilton
JJ
.
Surgical, economic, and psychological impacts of SARS-COV-2 on a Kansas community hospital system
.
Am Surg
.
2020
;
86
(
6
):
599
601
9
Boserup
B
,
McKenney
M
,
Elkbuli
A
.
The financial strain placed on America’s hospitals in the wake of the COVID-19 pandemic [published online ahead of print July 9, 2020]
.
Am J Emerg Med
.
doi:10.1016/j.ajem.2020.07.007
10
Khullar
D
,
Bond
AM
,
Schpero
WL
.
COVID-19 and the financial health of US hospitals
.
JAMA
.
2020
;
323
(
21
):
2127
2128
11
Hartnett
KP
,
Kite-Powell
A
,
DeVies
J
, et al;
National Syndromic Surveillance Program Community of Practice
.
Impact of the COVID-19 pandemic on emergency department visits - United States, January 1, 2019-May 30, 2020
.
MMWR Morb Mortal Wkly Rep
.
2020
;
69
(
23
):
699
704
12
Lee
L
,
Mannix
R
,
Guedi
R
, et al
.
Pediatric ED utilisation in the early phase of the COVID-19 pandemic
.
Emerg Med J
.
2021
;
38
:
100
102
13
Offenbacher
R
,
Knoll
MA
,
Loeb
DM
.
Delayed presentations of pediatric solid tumors at a tertiary care hospital in the Bronx due to COVID-19
.
Pediatr Blood Cancer
.
2021
;
68
(
2
):
e28615
14
Cherubini
V
,
Gohil
A
,
Addala
A
, et al
.
Unintended consequences of coronavirus disease-2019: remember general pediatrics
.
J Pediatr
.
2020
;
223
:
197
198
15
Snapiri
O
,
Rosenberg Danziger
C
,
Krause
I
, et al
.
Delayed diagnosis of paediatric appendicitis during the COVID-19 pandemic
.
Acta Paediatr
.
2020
;
109
(
8
):
1672
1676
16
Feudtner
C
,
Feinstein
JA
,
Zhong
W
,
Hall
M
,
Dai
D
.
Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation
.
BMC Pediatr
.
2014
;
14
:
199
17
Keren
R
,
Luan
X
,
Localio
R
, et al;
Pediatric Research in Inpatient Settings (PRIS) Network
.
Prioritization of comparative effectiveness research topics in hospital pediatrics
.
Arch Pediatr Adolesc Med
.
2012
;
166
(
12
):
1155
1164
18
Stokes
EK
,
Zambrano
LD
,
Anderson
KN
, et al
.
Coronavirus disease 2019 case surveillance — United States, January 22–May 30, 2020
.
MMWR Morb Mortal Wkly Rep
.
2020
;
69
(
24
):
759
765
19
Rentsch
CT
,
Kidwai-Khan
F
,
Tate
JP
, et al
.
Covid-19 by race and ethnicity: a national cohort study of 6 million United States veterans [published online ahead of print May 18, 2020]
.
medRxiv
.
doi:10.1101/2020.05.12.20099135
20
Rentsch
CT
,
Kidwai-Khan
F
,
Tate
JP
, et al
.
Patterns of COVID-19 testing and mortality by race and ethnicity among United States veterans: A nationwide cohort study
.
PLoS Med
.
2020
;
17
(
9
):
e1003379
21
Killerby
ME
,
Link-Gelles
R
,
Haight
SC
, et al;
CDC COVID-19 Response Clinical Team
.
Characteristics associated with hospitalization among patients with COVID-19 - metropolitan Atlanta, Georgia, March–April 2020
.
MMWR Morb Mortal Wkly Rep
.
2020
;
69
(
25
):
790
794
22
Richardson
T
,
Rodean
J
,
Harris
M
,
Berry
J
,
Gay
JC
,
Hall
M
.
Development of hospitalization resource intensity scores for Kids (H-RISK) and comparison across pediatric populations
.
J Hosp Med
.
2018
;
13
(
9
):
602
608
23
Agency for Healthcare Research and Quality
.
Chronic condition indicator (CCI) for ICD-9-CM
.
24
Wilder
JL
,
Parsons
CR
,
Growdon
AS
,
Toomey
SL
,
Mansbach
JM
.
Pediatric hospitalizations during the COVID-19 pandemic
.
Pediatrics
.
2020
;
146
(
6
):
e2020005983
25
Taquechel
K
,
Diwadkar
AR
,
Sayed
S
, et al
.
Pediatric asthma health care utilization, viral testing, and air pollution changes during the COVID-19 pandemic
.
J Allergy Clin Immunol Pract
.
2020
;
8
(
10
):
3378
3387.e11
26
Kadambari
S
,
Abo
YN
,
Phuong
LK
,
Osowicki
J
,
Bryant
PA
.
Decrease in infection-related hospital admissions during COVID-19: why are parents avoiding the doctor?
Pediatr Infect Dis J
.
2020
;
39
(
11
):
e385
e386

Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

Supplementary data