BACKGROUND

Although pediatric health care use declined during the coronavirus disease 2019 (COVID-19) pandemic, the impact on children with complex chronic conditions (CCCs) has not been well reported.

OBJECTIVE

To describe the impact of the pandemic on inpatient use and outcomes for children with CCCs.

METHODS

This multicenter cross-sectional study used data from the Pediatric Health Information System. We examined trends in admissions between January 2020 through March 2021, comparing them to the same timeframe in the previous 3 years (pre-COVID-19). We used generalized linear mixed models to examine the association of the COVID-19 period and outcomes for children with CCCs presenting between March 16, 2020 to March 15, 2021 (COVID-19 period) to the same timeframe in the previous 3 years (pre-COVID-19).

RESULTS

Children with CCCs experienced a 19.5% overall decline in admissions during the COVID-19 pandemic. Declines began in the second week of March of 2020, reaching a nadir in early April 2020. Changes in admissions varied over time and by admission indication. Children with CCCs hospitalized for pneumonia and bronchiolitis experienced overall declines in admissions of 49.7% to 57.7%, whereas children with CCCs hospitalized for diabetes experienced overall increases in admissions of 21.2%. Total and index length of stay, costs, and ICU use, although statistically higher during the COVID-19 period, were similar overall to the pre-COVID-19 period.

CONCLUSIONS

Total admissions for children with CCCs declined nearly 20% during the pandemic. Among prevalent conditions, the greatest declines were observed for children with CCCs hospitalized with respiratory illnesses. Despite declines in admissions, overall hospital-level outcomes remained similar.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, has impacted health care systems since its emergence. Changes in pandemic-related health care include reductions in emergency department (ED) visits, 35% reductions in admissions at children’s hospitals for generally healthy children, as well as delays in presentations for those with specific chronic diseases.16  There are few data, however, on the effect of the COVID-19 pandemic on children with complex chronic conditions (CCCs).79 

Children with CCCs are a growing pediatric subpopulation who require significant health care use. Children with CCCs are at higher risk for hospital admissions and readmissions, have longer lengths of stay, and higher health care costs compared to their noncomplex peers.10  Before the pandemic, children with CCCs experienced challenges accessing quality health care and frequently had unmet health care needs.1113  Although sparse, studies focused on children with CCCs during the COVID-19 pandemic have demonstrated disruptions in educational and medical services including reductions in ED visits during an 8-week period early in the pandemic compared to the same period in 2019.79,14 

Children with CCCs are at increased risk for significant health declines with disruption in access to health care services.7,15,16  Understanding how the pandemic affected health care use for these children may inform the future provision of health care and hospital plans for other large-scale disasters limiting health care access. Therefore, we sought to describe the impact of the COVID-19 pandemic on hospital admissions and clinical and financial outcomes for children with CCCs.

We performed a multicenter, cross-sectional study of inpatient and observation status stays among children with CCCs using the Pediatric Health Information System (PHIS) database. The PHIS database contains detailed patient-level data from 49 children’s hospitals affiliated with Children’s Hospital Association (Lenexa, KS). Eight hospitals were excluded for failure to report billing data throughout the study period (7 hospitals) and for length of stay (LOS) data not reported in hours (1 hospital).

We included children with 1 or more CCCs,17  who were 0 to 18 years of age with an index admission (medical or surgical) at a PHIS-participating hospital. We used Feudtner’s description to identify the number and types of CCCs among children in our study.17  We excluded birth admissions for healthy newborns (all patient refined diagnosis related groups [APR-DRGs], 626 and 640) and maternal obstetrical admissions, because children’s hospitals have variable admission practices for these indications and most admissions are not related to acute illness. We excluded transfers, those who left against medical advice, and hospitals and hospitalizations with incomplete data (eg, delinquent data submissions, incomplete billing data through the study period, and LOS not in hours).

We present overall trends in admissions for children with CCCs between January 1, 2020 and March 15, 2021 compared to the average number of admissions during this same period in the preceding 3 years. We used a 3-year average before 2020 to account for year-to-year differences in admissions. To understand relative changes in admissions for children with CCCs during the pandemic, we also included a contemporaneous control group of children without CCCs. In examinations of clinical and financial outcomes, we examined a 1-year COVID-19 period from March 16, 2020 to March 15, 2021 and a corresponding pre-COVID-19 period of March 16, 2017 to March 15, 2020. For these analyses we divided the data into 3 subgroups on the basis of trends during the COVID-19 period as follows: COVID-19 period 1 (March 16, 2020 to May 31, 2020; corresponding approximately to the US declaration of a national emergency to the end of the academic year for many school districts); COVID-19 period 2 (June 1, 2020 to August 31, 2020; corresponding approximately to when inpatient admissions and surgical procedures began to stabilize after a period of pronounced reduction18  and the start of summer vacation for many school districts); and COVID-19 period 3 (September 1, 2020 to March 15, 2021; corresponding approximately to when hospital admissions typically increase with the onset of respiratory season and the beginning of the academic year for many school districts). The end date of March 15, 2021 was used to allow a full 30-day readmission window into April for all encounters. To allow for direct comparisons over years, we normalized all dates using 7-day increments (ie, day of the week was not considered in describing weeks of the year).

We describe overall trends in admissions for children with CCCs and for the 12 most prevalent APR-DRGs (version 36, 3M Corporation, St. Paul, MN) on the basis of admission trends before 2020. APR-DRGs are a patient classification scheme that group patients on the basis of the principal discharge diagnosis. This allows for assessment of changes on the basis of the indication for admission. For ease of interpretation, we collapsed other neonatal APR-DRG codes together and labeled them as “complex neonates” (Supplemental Table 3).

We also examined clinical and financial outcomes overall and by type of CCC. Clinical outcomes included LOS measured in hours, same-cause readmission rates at 3-, 7-, 14-, and 30-day intervals, ICU use, mortality, and use of 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. In examinations of readmissions, we counted only the first readmission (if 1 occurred) for each readmission window. We examined ICU use at any time during the index admission. Financial outcomes included standardized costs in US dollars for the index admission and the total episode of care. We used previously described methods for calculating annual standardized costs using billing data and inflated standardized costs from 2017 to 2019 to 2020 dollars using the medical component of the consumer price index.19,20 

We examined demographic characteristics including age, sex, primary payor, race and ethnicity, and median household income quartile by zip code. We included race and ethnicity as a covariate as multiple studies have reported the differential impacts of the COVID-19 pandemic on the basis of race and ethnicity.2124  We examined patient characteristics including planned procedures25  and mean hospitalization resource intensity scores for kids (H-RISK),26  H-RISK serves as a surrogate for severity of illness and is calculated by assigning relative weights to each APR-DRG and severity of illness level facilitating comparison across APR-DRG groups. We also examined hospital characteristics including hospital region and source of admission (through the 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 sum 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) examined the association of COVID-19 period and outcomes adjusting for age, sex, primary payor, race and ethnicity, number of CCCs, median household income, admission through the ED, hospital region, and H-RISK. 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 examined differences in outcomes for children with CCCs over time comparing the 3 COVID-19 periods to each other. All statistical analyses were performed using SAS 9.4 (SAS Institute, Cary, NC), and P values <.001 were considered statistically significant (unless otherwise indicated) because of the inclusion of large sample sizes and multiple comparisons. This study, using deidentified data, was deemed exempt from institutional board review.

Hospital admissions began to decline around the 11th week of 2020 (March 11- to March 17 2020), with the greatest declines in admissions observed during the 14th week (–47.6%, April 1 to April 7, 2020) (Fig 1). We observed a sharp decline in weekly admissions from week 11 to week 14 followed by a slower recovery toward pre-COVID-19 admission numbers. Beginning week 22, children with CCCs experienced a period of stabilization in admissions near to pre-COVID-19 levels (–12.6%, May 27 to June 2, 2020). Children with CCCs experienced less of a decline and a more rapid return to pre-COVID-19 admission numbers compared to children without CCCs (Supplemental Fig 4).

FIGURE 1

Trends in numbers of overall admissions for children with complex chronic conditions during the pre-COVID-19 versus COVID-19 period. The COVID-19 trend line represents admissions from January 1, 2020 to March 15, 2021, whereas the pre-COVID-19 trend line represents a 3-year average of admissions before 2020. COVID-19 period 1 is defined as March 16, 2020 to May 31, 2020. COVID-19 period 2 is defined as June 1, 2020 to August 31, 2020. COVID-19 period 3 is defined as September 1, 2020 to March 15, 2021. All dates were normalized using 7-day increments and reported as a continuous count by week.

FIGURE 1

Trends in numbers of overall admissions for children with complex chronic conditions during the pre-COVID-19 versus COVID-19 period. The COVID-19 trend line represents admissions from January 1, 2020 to March 15, 2021, whereas the pre-COVID-19 trend line represents a 3-year average of admissions before 2020. COVID-19 period 1 is defined as March 16, 2020 to May 31, 2020. COVID-19 period 2 is defined as June 1, 2020 to August 31, 2020. COVID-19 period 3 is defined as September 1, 2020 to March 15, 2021. All dates were normalized using 7-day increments and reported as a continuous count by week.

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The COVID-19 pandemic impacted admissions for children with CCCs based on their APR-DRG category (Fig 2, Supplemental Table 4, Supplemental Fig 5). Among the 12 most prevalent prepandemic APR-DRGs, we observed that children with CCCs hospitalized for acute respiratory infections (ie, bronchiolitis, pneumonia, and upper respiratory infections) experienced the greatest declines (−44.7% to –57.7%) in admissions during the COVID-19 period, whereas patients with diabetes experienced the greatest increases in admissions (+21.2%) during the COVID-19 pandemic. We also observed differences in admission trends over time for these APR-DRGs (Fig 2). Conditions such as “other GI diagnoses” and seizures demonstrated an early sharp decline in admissions with return toward pre-COVID-19 numbers by week 22. In comparison, children with CCCs hospitalized with acute respiratory infections experienced sharp early declines that were sustained throughout the study period, whereas admissions for “other hematologic and immunologic diagnoses” and “chemotherapy” overall remained steady throughout.

FIGURE 2

Trends in numbers of admissions for the top 12 most prevalent conditions by APR-DRG for children with complex chronic conditions during the pre-COVID-19 versus COVID-19 period. The COVID-19 trend line in each figure represents admissions from January 1, 2020 to March 15, 2021, whereas the pre-COVID-19 trend line represents a 3-year average of admissions before 2020. COVID-19 period 1 is defined as March 16, 2020 to May 31, 2020. COVID-19 period 2 is defined as June 1, 2020 to August 31, 2020. COVID-19 period 3 is defined as September 1, 2020 to March 15, 2021. All dates were normalized using 7-day increments and reported as a continuous count by week.

FIGURE 2

Trends in numbers of admissions for the top 12 most prevalent conditions by APR-DRG for children with complex chronic conditions during the pre-COVID-19 versus COVID-19 period. The COVID-19 trend line in each figure represents admissions from January 1, 2020 to March 15, 2021, whereas the pre-COVID-19 trend line represents a 3-year average of admissions before 2020. COVID-19 period 1 is defined as March 16, 2020 to May 31, 2020. COVID-19 period 2 is defined as June 1, 2020 to August 31, 2020. COVID-19 period 3 is defined as September 1, 2020 to March 15, 2021. All dates were normalized using 7-day increments and reported as a continuous count by week.

Close modal

We identified a total of 780 184 admissions for 431 883 children with CCCs, of which 165 033 admissions occurred in the COVID-19 period from March 16, 2020 to March 15, 2021 and 615 151 admissions (mean: 205 050 per year) occurred in the corresponding pre-COVID-19 period (Table 1, Fig 3, and Supplemental Table 5). Compared to the mean annual number of admissions in the pre-COVID-19 period, the total number of admissions for children with CCCs declined 19.5% across the entire COVID-19 period. We observed small differences in the distributions of admissions by age, payor, median household income, and numbers and types of CCCs between COVID-19 and pre-COVID-19 periods. The mean H-RISK score was 6.1% greater among children with CCCs presenting in the COVID-19 period relative to the pre-COVID-19 period. Of included children, 1910 received a diagnosis of COVID-19 during their hospitalization, with the greatest percentage of cases observed between November 2020 to January 2021. Compared to periods 2 and 3, children with CCCs presenting in period 1 had higher proportions of 3 or more CCCs and higher H-RISK scores (Supplemental Table 6).

FIGURE 3

Consort diagram. The consort diagram does not include the contemporaneous control of children without complex chronic conditions. Incomplete data was predominantly comprised of hospitalizations from hospitals with delinquent data submissions at the time of the analysis (N = 72 643).

FIGURE 3

Consort diagram. The consort diagram does not include the contemporaneous control of children without complex chronic conditions. Incomplete data was predominantly comprised of hospitalizations from hospitals with delinquent data submissions at the time of the analysis (N = 72 643).

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TABLE 1

Clinical and Demographic Characteristics

OverallPre-COVID-19COVID-19
Index admissions 780 184 615 151 165 033 
 Medical 592 367 (75.9) 469 593 (76.3) 122 774 (74.4) 
 Surgical 187 817 (24.1) 145 558 (23.7) 42 259 (25.6) 
Age, y    
 <1 181 663 (23.3) 142 216 (23.1) 39 447 (23.9) 
 14 195 709 (25.1) 158 037 (25.7) 37 672 (22.8) 
 5–9 139 271 (17.9) 111 736 (18.2) 27 535 (16.7) 
 1014 151 936 (19.5) 117 996 (19.2) 33 940 (20.6) 
 1518 111 605 (14.3) 85  166 (13.8) 26 439 (16.0) 
Sex    
 Female 356 991 (45.8) 280 785 (45.6) 76 206 (46.2) 
 Male 422 834 (54.2) 334 077 (54.3) 88 757 (53.8) 
 Missing 359 (0.0) 289 (0.0) 70 (0.0) 
Payor    
 Government 445 629 (57.1) 350 741 (57.0) 94 888 (57.5) 
 Private 301 540 (38.6) 237 257 (38.6) 64 283 (39.0) 
 Self-Pay 8104 (1.0) 6039 (1.0) 2065 (1.3) 
 Other 24 911 (3.2) 21 114 (3.4) 3797 (2.3) 
Race and ethnicity    
 Non-Hispanic White 386 016 (49.5) 303 856 (49.4) 82 160 (49.8) 
 Non-Hispanic Black 150 833 (19.3) 119 533 (19.4) 31 300 (19.0) 
 Hispanic 156 739 (20.1) 122 736 (20.0) 34 003 (20.6) 
 Other 86 596 (11.1) 69 026 (11.2) 17 570 (10.6) 
Median household income (US dollars)    
 Quartile 1 (0–33 311) 179 415 (23.0) 141 833 (23.1) 37 582 (22.8) 
 Quartile 2 (33 312–41 386) 186 138 (23.9) 147 288 (23.9) 38 850 (23.5) 
 Quartile 3 (41 387–54 013) 196 213 (25.1) 154 404 (25.1) 41 809 (25.3) 
 Quartile 4 (54 014–203 326) 197 927 (25.4) 155 208 (25.2) 42 719 (25.9) 
 Missing 20 491 (2.6) 16 418 (2.7) 4073 (2.5) 
Number of complex chronic conditions    
 1 403 902 (51.8) 319 040 (51.9) 84 862 (51.4) 
 2 162 466 (20.8) 127 151 (20.7) 35 315 (21.4) 
 3 109 537 (14.0) 86 896 (14.1) 22 641 (13.7) 
 ≥4 104 279 (13.4) 82 064 (13.3) 22 215 (13.5) 
Types of complex chronic conditions    
 Neuromuscular 195 989 (25.1) 154 423 (25.1) 41 566 (25.2) 
 Cardiovascular 168 361 (21.6) 131 901 (21.4) 36 460 (22.1) 
 Respiratory 84 701 (10.9) 68 493 (11.1) 16 208 (9.8) 
 GI 220 994 (28.3) 175 492 (28.5) 45 502 (27.6) 
 Hematologic and immune 108 287 (13.9) 85 217 (13.9) 23 070 (14.0) 
 Metabolic 117 077 (15.0) 89 241 (14.5) 27 836 (16.9) 
 Congenital and genetic 109 856 (14.1) 88 059 (14.3) 21 797 (13.2) 
 Malignancy 110 535 (14.2) 85 717 (13.9) 24 818 (15.0) 
 Neonatal 68 466 (8.8) 53 898 (8.8) 14 568 (8.8) 
 Tech dependent 247 839 (31.8) 197 272 (32.1) 50 567 (30.6) 
H-RISK 2.217 (0.004) 2.187 (0.005) 2.328 (0.009) 
Hospital regiona    
 Midwest 191 324 (24.5) 150 537 (24.5) 40 787 (24.7) 
 Northeast 123 112 (15.8) 97 614 (15.9) 25 498 (15.5) 
 South 293 476 (37.6) 232 033 (37.7) 61 443 (37.2) 
 West 172 272 (22.1) 134 967 (21.9) 37 305 (22.6) 
Admission source    
 Emergency department 377 788 (48.4) 302 746 (49.2) 75 042 (45.5) 
 Direct 402 396 (51.6) 312 405 (50.8) 89 991 (54.5) 
Admission type    
 Medical 592 367 (75.9) 469 593 (76.3) 122 774 (74.4) 
 Surgical 187 817 (24.1) 145 558 (23.7) 42 259 (25.6) 
Planned procedure    
 No 619 138 (79.4) 489 322 (79.5) 129 816 (78.7) 
 Yes 161 046 (20.6) 125 829 (20.5) 35 217 (21.3) 
OverallPre-COVID-19COVID-19
Index admissions 780 184 615 151 165 033 
 Medical 592 367 (75.9) 469 593 (76.3) 122 774 (74.4) 
 Surgical 187 817 (24.1) 145 558 (23.7) 42 259 (25.6) 
Age, y    
 <1 181 663 (23.3) 142 216 (23.1) 39 447 (23.9) 
 14 195 709 (25.1) 158 037 (25.7) 37 672 (22.8) 
 5–9 139 271 (17.9) 111 736 (18.2) 27 535 (16.7) 
 1014 151 936 (19.5) 117 996 (19.2) 33 940 (20.6) 
 1518 111 605 (14.3) 85  166 (13.8) 26 439 (16.0) 
Sex    
 Female 356 991 (45.8) 280 785 (45.6) 76 206 (46.2) 
 Male 422 834 (54.2) 334 077 (54.3) 88 757 (53.8) 
 Missing 359 (0.0) 289 (0.0) 70 (0.0) 
Payor    
 Government 445 629 (57.1) 350 741 (57.0) 94 888 (57.5) 
 Private 301 540 (38.6) 237 257 (38.6) 64 283 (39.0) 
 Self-Pay 8104 (1.0) 6039 (1.0) 2065 (1.3) 
 Other 24 911 (3.2) 21 114 (3.4) 3797 (2.3) 
Race and ethnicity    
 Non-Hispanic White 386 016 (49.5) 303 856 (49.4) 82 160 (49.8) 
 Non-Hispanic Black 150 833 (19.3) 119 533 (19.4) 31 300 (19.0) 
 Hispanic 156 739 (20.1) 122 736 (20.0) 34 003 (20.6) 
 Other 86 596 (11.1) 69 026 (11.2) 17 570 (10.6) 
Median household income (US dollars)    
 Quartile 1 (0–33 311) 179 415 (23.0) 141 833 (23.1) 37 582 (22.8) 
 Quartile 2 (33 312–41 386) 186 138 (23.9) 147 288 (23.9) 38 850 (23.5) 
 Quartile 3 (41 387–54 013) 196 213 (25.1) 154 404 (25.1) 41 809 (25.3) 
 Quartile 4 (54 014–203 326) 197 927 (25.4) 155 208 (25.2) 42 719 (25.9) 
 Missing 20 491 (2.6) 16 418 (2.7) 4073 (2.5) 
Number of complex chronic conditions    
 1 403 902 (51.8) 319 040 (51.9) 84 862 (51.4) 
 2 162 466 (20.8) 127 151 (20.7) 35 315 (21.4) 
 3 109 537 (14.0) 86 896 (14.1) 22 641 (13.7) 
 ≥4 104 279 (13.4) 82 064 (13.3) 22 215 (13.5) 
Types of complex chronic conditions    
 Neuromuscular 195 989 (25.1) 154 423 (25.1) 41 566 (25.2) 
 Cardiovascular 168 361 (21.6) 131 901 (21.4) 36 460 (22.1) 
 Respiratory 84 701 (10.9) 68 493 (11.1) 16 208 (9.8) 
 GI 220 994 (28.3) 175 492 (28.5) 45 502 (27.6) 
 Hematologic and immune 108 287 (13.9) 85 217 (13.9) 23 070 (14.0) 
 Metabolic 117 077 (15.0) 89 241 (14.5) 27 836 (16.9) 
 Congenital and genetic 109 856 (14.1) 88 059 (14.3) 21 797 (13.2) 
 Malignancy 110 535 (14.2) 85 717 (13.9) 24 818 (15.0) 
 Neonatal 68 466 (8.8) 53 898 (8.8) 14 568 (8.8) 
 Tech dependent 247 839 (31.8) 197 272 (32.1) 50 567 (30.6) 
H-RISK 2.217 (0.004) 2.187 (0.005) 2.328 (0.009) 
Hospital regiona    
 Midwest 191 324 (24.5) 150 537 (24.5) 40 787 (24.7) 
 Northeast 123 112 (15.8) 97 614 (15.9) 25 498 (15.5) 
 South 293 476 (37.6) 232 033 (37.7) 61 443 (37.2) 
 West 172 272 (22.1) 134 967 (21.9) 37 305 (22.6) 
Admission source    
 Emergency department 377 788 (48.4) 302 746 (49.2) 75 042 (45.5) 
 Direct 402 396 (51.6) 312 405 (50.8) 89 991 (54.5) 
Admission type    
 Medical 592 367 (75.9) 469 593 (76.3) 122 774 (74.4) 
 Surgical 187 817 (24.1) 145 558 (23.7) 42 259 (25.6) 
Planned procedure    
 No 619 138 (79.4) 489 322 (79.5) 129 816 (78.7) 
 Yes 161 046 (20.6) 125 829 (20.5) 35 217 (21.3) 

Data are presented as n (%) with the exception of H-RISK, which is presented as mean (SD). All comparisons were significant at P <.001 except for neuromuscular, hematologic/immune, and neonatal complex chronic conditions. H-RISK, hospitalization resource intensity scores for kids.

a

This study included hospitalizations from 25 states, representing all 4 regions of the United States.

In adjusted analyses, the differences in overall LOS and costs of index admissions and the total episode of care, although statistically significant, were overall similar during the COVID-19 period compared to the pre-COVID-19 period (Table 2). Readmission rates were lower during the COVID-19 period compared to the pre-COVID-19 period. ICU use and mortality remained similar between pre-COVID-19 and COVID-19 periods; however, the use of mechanical ventilation for children with CCCs was lower in the COVID-19 period. Unadjusted outcomes are presented in Supplemental Table 7. In a subanalysis of the 3 COVID-19 periods, children with CCCs presenting in period 1 of the COVID-19 pandemic experienced longer LOS, had higher readmission rates, ICU use, and rates of mechanical ventilation though mortality rates were similar compared to the other 2 COVID-19 periods (Supplemental Table 8).

TABLE 2

Overall Adjusted Clinical and Financial Outcomes for Children With Complex Chronic Conditions.

Pre-COVID-19COVID-19Ratio of Means or Odds Ratio for COVID-19 vs Pre-COVID
Length of stay, h, geometric mean (99.9% CI)    
 Index admissiona 86.4 (80.5–92.7) 85.1 (79.2–91.3) 0.98 (0.98–0.99) 
 Total episode of carea 105.6 (97.9–113.8) 102.5 (95.0–110.6) 0.97 (0.96–0.98) 
 Days between index admit and readmit 11.1 (10.8–11.5) 11.2 (10.8–11.5) 1.01 (0.99–1.02) 
Cost (US dollars), geometric mean (99.9% CI)    
 Index admissiona 13 317 (11 319–15 668) 13 734 (11 671–16 162) 1.03 (1.02–1.04) 
 Total episode of carea 16 674 (14 154–19 641) 17 009 (14 436–20 041) 1.02 (1.01–1.03) 
Readmission rates, % (99.9% CI)    
 3 da 3.1 (2.7–3.6) 2.7 (2.4–3.2) 0.88 (0.83, –0.93) 
 7 da 7.5 (6.9–8.3) 6.9 (6.3–7.6) 0.91 (0.88–0.95) 
 14 da 13.0 (11.9–14.1) 12.2 (11.2–13.3) 0.94 (0.91–0.96) 
 30 da 20.9 (19.4–22.6) 20.0 (18.4–21.6) 0.94 (0.92–0.96) 
ICU use, % (99.9% CI) 21.0 (18.0–24.4) 20.7 (17.8–24.1) 0.98 (0.96–1.01) 
Mechanical ventilation, % (99.9% CI)a 9.9 (8.2–11.8) 8.8 (7.3–10.6) 0.88 (0.85–0.91) 
Mortality, % (99.9% CI)    
 Index admission 1.6 (1.3–1.9) 1.6 (1.3–2.0) 1.01 (0.93–1.09) 
 Total episode of care 1.9 (1.6–2.3) 1.9 (1.6–2.3) 0.97 (0.91–1.05) 
Pre-COVID-19COVID-19Ratio of Means or Odds Ratio for COVID-19 vs Pre-COVID
Length of stay, h, geometric mean (99.9% CI)    
 Index admissiona 86.4 (80.5–92.7) 85.1 (79.2–91.3) 0.98 (0.98–0.99) 
 Total episode of carea 105.6 (97.9–113.8) 102.5 (95.0–110.6) 0.97 (0.96–0.98) 
 Days between index admit and readmit 11.1 (10.8–11.5) 11.2 (10.8–11.5) 1.01 (0.99–1.02) 
Cost (US dollars), geometric mean (99.9% CI)    
 Index admissiona 13 317 (11 319–15 668) 13 734 (11 671–16 162) 1.03 (1.02–1.04) 
 Total episode of carea 16 674 (14 154–19 641) 17 009 (14 436–20 041) 1.02 (1.01–1.03) 
Readmission rates, % (99.9% CI)    
 3 da 3.1 (2.7–3.6) 2.7 (2.4–3.2) 0.88 (0.83, –0.93) 
 7 da 7.5 (6.9–8.3) 6.9 (6.3–7.6) 0.91 (0.88–0.95) 
 14 da 13.0 (11.9–14.1) 12.2 (11.2–13.3) 0.94 (0.91–0.96) 
 30 da 20.9 (19.4–22.6) 20.0 (18.4–21.6) 0.94 (0.92–0.96) 
ICU use, % (99.9% CI) 21.0 (18.0–24.4) 20.7 (17.8–24.1) 0.98 (0.96–1.01) 
Mechanical ventilation, % (99.9% CI)a 9.9 (8.2–11.8) 8.8 (7.3–10.6) 0.88 (0.85–0.91) 
Mortality, % (99.9% CI)    
 Index admission 1.6 (1.3–1.9) 1.6 (1.3–2.0) 1.01 (0.93–1.09) 
 Total episode of care 1.9 (1.6–2.3) 1.9 (1.6–2.3) 0.97 (0.91–1.05) 

Comparisons were adjusted for age, sex, primary payor, race and ethnicity, number of complex chronic conditions, median household income, admission through the ED, hospital region, and H-RISK. ICU utilization includes any time spent in the ICU during the episode of care, whereas mechanical ventilation includes any time spent on a ventilator. Total episode of care includes the index admission and readmission. CI, confidence interval.

a

Indicates a significant comparison with P < .001.

Outcomes remained similar in adjusted analyses for children with CCCs regardless of the type of underlying medical complexity with some small differences (Supplemental Table 9). For example, children with underlying respiratory complexity had shorter lengths of stay, decreased 30-day readmission rates, costs, and ICU use during the COVID-19 period, whereas children with underlying metabolic complexity had longer lengths of stay, higher costs, and ICU use during the COVID-19 period. Children with tech dependency or increased numbers of CCCs experienced overall shorter LOS and had reduced ICU use in the COVID-19 period.

During the COVID-19 pandemic, admissions for children with CCCs declined nearly 20% compared to the pre-COVID-19 period. Children with CCCs experienced the most substantial declines in early April 2020 with return toward, but not full return, to pre-COVID-19 admission numbers by late May of 2020. The pandemic affected the number of admissions and the timing of admissions for children with CCCs differently on the basis of admission indication. Overall adjusted outcomes including LOS, costs, ICU use, and mortality were similar during the COVID-19 period compared to the pre-COVID-19 period; although children with CCCs admitted during the early pandemic experienced increased resource use compared to those presenting later during the pandemic. These findings suggest that social distancing policies and fears regarding COVID-19 exposures may have affected access to care and and/or health-seeking behaviors for children with CCCs, especially within the early pandemic, although future research exploring health-seeking behaviors for this population is needed.

Among children with CCCs presenting during the COVID-19 pandemic there was a significant decline in admissions compared to previous years, especially in the early months of the pandemic. The overall 19.5% reduction in admissions that we observed for children with CCCs was less severe and not as prolonged as the reductions observed among generally healthy children presenting during the pandemic (overall 35.1% reductions;5  Supplemental Fig 1). Nearly half of participants with chronic diseases in a previous study reported that the pandemic impacted their health, with 53% of participants reporting missed routine health care visits.27  Our observations likely represent a combination of the overall medical complexity of individual patients, caregivers’ ability to identify acute worsening and to escalate care at home, potential disruption of services related to school closures, and the impact that social distancing policies and stay at home orders had on health-seeking behaviors for this fragile population. Developing mitigation strategies, such as robust telemedicine programs, may help to further address disruptions of in-person health care delivery for children with CCCs within future large-scale disasters limiting health care access.28,29 

Acute respiratory infections were among conditions with the greatest reductions in admissions for children with CCCs, whereas conditions such as diabetes were among a very few conditions that experienced increases in admissions during COVID-19. Studies examining ED and inpatient resource use for children during COVID-19 similarly observed significant reductions in admissions for respiratory illnesses.3032  Among children with CCCs presenting to a pediatric ED in Italy, Brisca et al observed that those with respiratory medical complexity experienced declines in ED visits from 15.6% in 2019% to 4.8% in 2020.7  The sustained reductions in hospitalizations for acute respiratory infections among children with CCCs in our study likely reflect the impact that social distancing practices, masking, and school closures had on community transmission of infections. These findings highlight how public health measures may mitigate some medical illnesses among children with CCCs and underscore a need to reevaluate infection control practices for this population. However, any practice change would need to be counterbalanced against the potential negative psychological and social impacts that these measures may have for some individuals. Previous studies highlighted delays in diagnosis of new onset diabetes and increased incidence of diabetic ketoacidosis during the pandemic.33  Although we observed increased admissions for diabetes among children with CCCs, we are unable to determine if these hospitalizations represent new a diagnosis versus complications of chronic disease. Future studies focused on understanding the increased admissions for diabetes among children with CCCs may provide further context for these admissions and identify potential unmet needs specific to this population.

Studies of the COVID-19 pandemic in children have reported delayed presentations leading to worsening health outcomes.13  In our study, children with CCCs presenting during the COVID-19 pandemic, especially during the early COVID-19 period, had higher H-RISK scores and increased number of CCCs. With some exceptions (eg, reduced LOS, 30-day readmissions, costs, and ICU use among those with respiratory medical complexity), outcomes were overall similar between pre-COVID-19 and COVID-19 periods regardless of the type of underlying medical complexity. However, in a subanalysis of children with CCCs by period of presentation, we observed increased resource use (eg, increased LOS, higher readmission rates) among children with CCCs presenting in the early pandemic. Our observations of potentially worsened health outcomes early in the pandemic may represent changes in health-seeking behavior secondary to COVID-19 policies and pandemic fears, whereas our observations later in the pandemic, including a return toward baseline outcomes for children with CCCs, may be secondary to the easing of restrictions and/or a natural progression back to previous health-seeking behavior. Alternative explanations for these findings may include changes in hospital case mix early in the pandemic secondary to admission deferral of less severe cases and/or prolonged lengths of stay related to difficulties coordinating and arranging outpatient services in the setting of lockdowns and school closures. Regardless, ensuring hospitals are perceived as a safe environment to caregivers and access to care is not limited during a national event such as a pandemic is especially important for children with CCCs.

There are several important limitations to our study. First, we used administrative data, and any data quality issues (eg, incomplete or missing data) could impact or bias our results. The PHIS database and contributing hospitals rigorously monitor data quality, so data quality concerns are expected to be small. Second, our analysis focused on admissions to children’s hospitals, which frequently provide care to children with CCCs because of the concentration of subspecialty services in these settings; however, inpatient admissions represent only 1 metric of health care access, and with lockdowns and social distancing measures, it is possible that children with CCCs may have accessed telehealth or sought care in alternative settings (eg, smaller community hospitals, ambulatory settings). Third, individual communities were impacted differently by the COVID-19 pandemic over time, which we are unable to account for, and differences in local prevalence of infections and local and regional closures and lockdowns could have contributed to some of our observations. Finally, previous reports describe variability in the impact of the COVID-19 pandemic on the basis of socioeconomic factors, and our adjustments for sociodemographic and clinical factors, including payor and race and ethnicity, may have adjusted away some of the indirect effects of the pandemic by biasing our results toward the null.

Children with CCCs experienced overall declines of nearly 20% in admissions to US children’s hospitals during the COVID-19 pandemic compared to the same timeframe in the previous 3 years. The COVID-19 pandemic differentially impacted children with CCCs on the basis of the indication for admission. Although statistically different, the overall adjusted outcomes including LOS, costs, and ICU use were similar to the pre-COVID-19 period. Future studies focused on understanding health-seeking behavior and the impact on outcomes for this vulnerable population may shed further light on our observations.

FUNDING: No external funding.

CONFLICT OF INTEREST DISCLOSURES: The authors have no financial relationships relevant to this article to disclose.

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 has provided critical intellectual content in the revision of the manuscript as an author; Drs Teufel, Hersh, DePorre, Fleegler, Antiel, Williams, Hotz, and Wilder participated in the study design, analysis, and interpretation of the data and have provided critical intellectual content in the revision of the manuscript as authors; Dr Shah supervised the study design, analysis, and interpretation of the data and has provided critical intellectual content in the revision of the manuscript as an author; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

COMPANION PAPER: A companion to this article can be found online at www.hosppeds.org/cgi/doi/10.1542/hpeds.2022-006542.

1.
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
.
68
(
2
):
e28615
2.
Cherubini
V
,
Gohil
A
,
Addala
A
et al
.
Unintended consequences of coronavirus disease-2019: remember general pediatrics
.
J Pediatr
.
2020
;
223
:
197
198
3.
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
4.
Lee
L
,
Mannix
R
,
Guedj
R
et al
.
Paediatric ED utilisation in the early phase of the COVID-19 pandemic
.
Emerg Med J
.
2021
;
38
(
2
):
100
102
5.
Markham
JL
,
Richardson
T
,
DePorre
A
et al
.
Inpatient use and outcomes at children’s hospitals during the early COVID-19 pandemic
.
Pediatrics
.
2021
;
147
(
6
):
e2020044735
6.
Gavish
R
,
Levinsky
Y
,
Dizitzer
Y
,
Bilavsky
E
,
Livni
G
,
Pirogovsky
A
,
Scheuerman
O
,
Krause
I
.
The COVID-19 pandemic dramatically reduced admissions of children with and without chronic conditions to general paediatric wards
.
Acta Paediatr
.
110
(
7
):
2212
2217
7.
Brisca
G
,
Vagelli
G
,
Tagliarini
G
et al
.
The impact of COVID-19 lockdown on children with medical complexity in pediatric emergency department
.
Am J Emerg Med
.
2021
;
42
:
225
227
8.
Jeste
S
,
Hyde
C
,
Distefano
C
et al
.
Changes in access to educational and healthcare services for individuals with intellectual and developmental disabilities during COVID-19 restrictions
.
J Intellect Disabil Res
.
2020
;
64
(
11
):
825
833
9.
Cacioppo
M
,
Bouvier
S
,
Bailly
R
et al
;
ECHO Group
.
Emerging health challenges for children with physical disabilities and their parents during the COVID-19 pandemic: The ECHO French survey
.
Ann Phys Rehabil Med
.
2021
;
64
(
3
):
101429
10.
Cohen
E
,
Berry
JG
,
Sanders
L
,
Schor
EL
,
Wise
PH
.
Status complexicus? The emergence of pediatric complex care
.
Pediatrics
.
2018
;
141
(
Suppl 3
):
S202
S211
11.
Houtrow
A
,
Harris
D
,
Molinero
A
,
Levin-Decanini
T
,
Robichaud
C
.
Children with disabilities in the United States and the COVID-19 pandemic
.
J Pediatr Rehabil Med
.
2020
;
13
(
3
):
415
424
12.
Houtrow
AJ
,
Okumura
MJ
,
Hilton
JF
,
Rehm
RS
.
Profiling health and health-related services for children with special health care needs with and without disabilities
.
Acad Pediatr
.
2011
;
11
(
6
):
508
516
13.
Kuo
DZ
,
Goudie
A
,
Cohen
E
et al
.
Inequities in health care needs for children with medical complexity
.
Health Aff (Millwood)
.
2014
;
33
(
12
):
2190
2198
14.
Children with special health care needs during COVID-19: findings from the family strengths research study
.
15.
Wong
CA
,
Ming
D
,
Maslow
G
,
Gifford
EJ
.
Mitigating the impacts of the COVID-19 pandemic response on at-risk children
.
Pediatrics
.
2020
;
146
(
1
):
e20200973
16.
Berry
JG
.
What children with medical complexity, their families, and healthcare providers deserve from an ideal healthcare system
.
17.
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
18.
Synhorst
DC
,
Bettenhausen
JL
,
Hall
M
et al
.
Healthcare encounter and financial impact of COVID-19 on children’s hospitals
.
J Hosp Med
.
2021
;
16
(
4
):
223
226
19.
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
20.
Mahant
S
,
Richardson
T
,
Keren
R
,
Srivastava
R
,
Meier
J
,
Pediatric Research in Inpatient Setting (PRIS) Network
.
Variation in tonsillectomy cost and revisit rates: analysis of administrative and billing data from US children’s hospitals
.
BMJ Qual Saf
.
2020
:
bmjqs-2019-010730
21.
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
.
medRxiv
.
2020
22.
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
23.
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
24.
Stokes
EK
.
Coronavirus disease 2019 case surveillance—United States, January 22–May 30, 2020
.
MMWR Morb Mortal Wkly Rep
.
2020
;
69
(
24
):
759
765
25.
Berry
JG
,
Toomey
SL
,
Zaslavsky
AM
et al
.
Pediatric readmission prevalence and variability across hospitals
.
JAMA
.
2013
;
309
(
4
):
372
380
26.
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
27.
Saqib
MAN
,
Siddiqui
S
,
Qasim
M
et al
.
Effect of COVID-19 lockdown on patients with chronic diseases
.
Diabetes Metab Syndr
.
2020
;
14
(
6
):
1621
1623
28.
Mosquera
RA
,
Avritscher
EBC
,
Pedroza
C
et al
.
Telemedicine for children with medical complexity: a randomized clinical trial
.
Pediatrics
.
2021
;
148
(
3
):
e2021050400
29.
First
L
.
Children with medical complexity and telemedicine: A good combination
.
30.
Wilder
JL
,
Parsons
CR
,
Growdon
AS
,
Toomey
SL
,
Mansbach
JM
.
Pediatric hospitalizations during the COVID-19 pandemic
.
Pediatrics
.
2020
;
146
(
6
):
e2020005983
31.
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
32.
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
.
2020
;
39
(
11
):
e385
e386
33.
Tieder
JS
,
McLeod
L
,
Keren
R
et al
;
Pediatric Research in Inpatient Settings Network
.
Variation in resource use and readmission for diabetic ketoacidosis in children’s hospitals
.
Pediatrics
.
2013
;
132
(
2
):
229
236

Supplementary data