BACKGROUND AND OBJECTIVE

The reported impacts of the COVID-19 pandemic on child maltreatment in the United States have been mixed. Encounter trends for child physical abuse within pediatric emergency departments may provide insights. Thus, this study sought to determine the change in the rate of emergency department encounters related to child physical abuse.

METHODS

A retrospective study within the Pediatric Emergency Care Applied Research Network Registry. Encounters related to child physical abuse were identified by 3 methods: child physical abuse diagnoses among all ages, age-restricted high-risk injury, or age-restricted skeletal survey completion. The primary outcomes were encounter rates per day and clinical severity before (January 2018–March 2020) and during the COVID-19 pandemic (April 2020–March 2021). Multivariable Poisson regression models were fit to estimate rate ratios with marginal estimation methods.

RESULTS

Encounter rates decreased significantly during the pandemic for 2 of 3 identification methods. In fully adjusted models, encounter rates were reduced by 19% in the diagnosis-code cohort (adjusted rate ratio: 0.81 [99% confidence interval: 0.75–0.88], P <.001), with the greatest reduction among preschool and school-aged children. Encounter rates decreased 10% in the injury cohort (adjusted rate ratio: 0.90 [confidence interval: 0.82–0.98], P = .002). For all 3 methods, rates for lower-severity encounters were significantly reduced whereas higher-severity encounters were not.

CONCLUSIONS

Encounter rates for child physical abuse were reduced or unchanged. Reductions were greatest for lower-severity encounters and preschool and school-aged children. This pattern calls for critical assessment to clarify whether pandemic changes led to true reductions versus decreased recognition of child physical abuse.

WHAT’S KNOWN ON THIS SUBJECT:

The COVID-19 pandemic prompted safety concerns for children given multiple societal stressors with simultaneous disruption of normal routines; yet literature has been mixed with regard to changes in child maltreatment, including health care use related to physical child abuse.

WHAT THIS STUDY ADDS:

In this multicenter assessment of emergency health care related to child physical abuse, encounter rates decreased inconsistently, with focused declines in low-severity and older age group encounters. This pattern raises concern for unrecognized harm versus true reductions.

Child abuse and neglect occur within multiple layers of risk and protective factors. Family-level factors, such as mental health and substance use, impact the likelihood of maltreatment.1,2  Disruptive events at community and society levels, such as financial recession and natural disasters, also increase the risk for physical abuse.37  Thus, the early days of the coronavirus disease 2019 (COVID-19) pandemic prompted safety concerns for children given reports of increased mental health crises, intimate partner violence, and disruption of daily routines.817 

Available results have been mixed with regard to the COVID-19 pandemic’s impact on child maltreatment, which is likely related to data sources and definitions.1821  Single-center health care studies have suggested increases in sentinel injuries, sexual abuse, and neglect early in the pandemic.2226  Conversely, multicenter analyses have revealed reduced hospitalizations for physical abuse, including abusive head trauma, during a similar period.27,28  Relatedly, the Centers for Disease Control and Prevention documented an initial precipitous decline in emergency health care use related to maltreatment, including physical abuse, sexual abuse, and neglect, followed by a return to previous levels.29  Finally, child protective services (CPS) data revealed substantial declines in report numbers across multiple jurisdictions, a signal reflective of all types of child maltreatment and reporting sources.3033  Nuanced understanding of the experiences of children during the pandemic is critical for proximate and future public health planning.

Emergency health care encounters for physical abuse can provide broad yet nuanced insights as a composite indicator impacted by injury severity and abuse recognition per the clinical experience that children with high-severity injuries receive emergency health care related to acute medical needs, independent of recognition interactions, whereas children with low-severity injuries are more likely receive emergency health care related to risk recognized through recognition interactions. Thus, if decreased reports to CPS result from a true decline in child physical abuse incidence, we would expect consistent decreases in emergency department (ED) encounters related to abuse concerns across severity levels. Alternatively, if decreased recognition of abuse is a primary driver of the reduction in reports to CPS, we would expect reductions in low-severity ED encounters related to child physical abuse, whereas high-severity encounters would remain constant.

Overall, we hypothesized that the rate of ED encounters related to child physical abuse with high severity would not change during the pandemic whereas the rate of encounters with low severity would decrease. To expand on previous research, we assessed a full year of pandemic clinical data from the Pediatric Emergency Care Applied Research Network (PECARN) Registry, allowing for multicenter analysis, including clinical severity.34  Thus, our assessment of physical abuse encounter rates within emergency health care settings may provide additional clarity to the experiences of children.

We conducted a multicenter retrospective study using data from the PECARN Registry from January 1, 2018 through March 31, 2021.34  PECARN Registry participation was approved by the institutional review boards of all study sites and the Data Coordinating Center.

The PECARN Registry comprises electronic medical health record data from every ED patient encounter at participating institutions, harmonized into a deidentified, central repository.34  Variables include standardized demographics (race, ethnicity, age, sex, insurance type), clinical care orders, laboratory and radiology results, International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) coded diagnoses and dispositions. This study included 9 participating institutions.

Three methods were used to identify ED encounters related to child physical abuse: (1) diagnosis codes: child abuse diagnosis by at least 1 ICD-10-CM code indicative of suspected or confirmed abuse (Supplemental Table 4), (2) injury codes: an ICD-10-CM code for injury associated with a diagnosis of abuse in certain young age groups (Supplemental Table 5), (3) skeletal survey cohort: evaluation of potential child physical abuse by skeletal survey radiographic study in children <24 months of age.3538  Visits identified by the 3 methods were treated as separate subgroups in analyses; an encounter could be included in >1 subgroup.

For the injury code cohort, International Classification of Diseases, 9th Revision, Clinical Modification injury codes associated with high specificity for child physical abuse were identified from the literature and converted to ICD-10-CM codes by using general equivalence mapping.35  Using a consensus process, 3 authors (Drs Chaiyachati, Wood, and Lindberg) reviewed the ICD-10-CM codes to ensure they represented injuries associated with a high risk of abuse. To increase specificity, exclusionary ICD-10-CM codes representing motor vehicle crashes, birth injuries, metabolic bone diseases, bleeding disorders, or follow-up visits were applied (Supplemental Table 6).39 

Demographic characteristics included age at encounter, insurance type (private, Medicaid, self-pay), and composite race and ethnicity. Race and ethnicity were hierarchically categorized by ethnicity (Hispanic or non-Hispanic) and then by race within the non-Hispanic group. Due to limited sample sizes, non-Hispanic racial categories were analyzed as Black, White, and additional racial group (including American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, Multiple Races, and other). Race and ethnicity were included in analyses due to documented differential COVID-19 pandemic experiences by groups.40  In addition, the likelihood to seek emergency health care and for clinicians to consider abuse may differ by racial and ethnic group.4143  Exposure to pandemic-related changes was defined by date: before the pandemic (January 1, 2018–March 31, 2020) or during the pandemic (April 1, 2020–March 31, 2021).

Clinical severity was assessed by injury severity measures and clinical disposition. Injury severity measures included triage acuity defined by emergency severity index (ESI), injury severity scores, and disposition.44  Injury severity scores were tabulated from ICD-10-CM codes with 2 methods: maximum abbreviated injury score (MAIS; 0: none, 1: minor, 2: moderate, 3: serious, 4: severe, 5: critical, 6: maximum; categories analyzed as 0–2, 3–6) and injury severity scale (ISS; range 0–75, the sum of squares of highest AIS scores for 3 most severely injured body regions; categories analyzed as 0–8, 9–15, >16).4548  Clinical disposition included ED visit disposition of discharged, admitted, transferred, or died and ED or hospital disposition vital status of alive or deceased.

Average daily rates of child abuse encounters and all PECARN Registry encounters were calculated for each calendar month and pandemic time period and plotted over time to visualize absolute and relative temporal patterns.

We described the number and rate per day of child abuse encounters overall as well as for each demographic and clinical characteristic of interest. For each characteristic, a “partially adjusted” multivariable Poisson regression model including an interaction between pandemic time period and the characteristic was fit to estimate rate ratios comparing pandemic rates to prepandemic rates while controlling for calendar month and clinical site for each of the 3 cohorts. The fully adjusted daily encounter rate models were generated with age, sex, race/ethnicity, primary payer, calendar month, site, ISS as severity measure, and an interaction term between ISS and pandemic time period, as well as interaction terms between pandemic time period and demographic covariates if the test for the interaction in the partially adjusted model had P <.10. Fully adjusted rate ratios and 99% confidence intervals (CI) were estimated for overall encounters and each severity level by using marginal estimation methods to average over other model covariates.34 

Because of strong correlations between clinical severity measures, separate, fully adjusted models were fit for each measure of clinical severity (MAIS, triage ESI level, ED disposition, and vital status) with covariates as listed above.

Because of the large sample size, we used a significance level of 0.10 for tests of interactions and 0.01 for all other tests of statistical significance. No adjustments were made for multiple comparisons. Encounters with missing data were excluded. We performed all analyses using SAS/STAT software version 9.4 (SAS Institute Inc., Cary, NC, USA).

After the application of exclusion criteria, a total of 1 579 014 ED encounters were identified in the PECARN Registry, including 10 270 (0.7%) as possible child physical abuse (Fig 1). Because of missing data, 315 (3.1%) of the abuse encounters were excluded.

FIGURE 1

Consort diagram.

FIGURE 1

Consort diagram.

Close modal

Diagnosis Code Cohort

Encounter rates as identified by child abuse diagnosis codes (diagnosis code cohort) decreased from 4.6 encounters per day prepandemic to 3.8 encounters per day during the pandemic, with the month and site-adjusted (“partially adjusted”) rate ratio (RR) of 0.82 (99% CI: 0.73–0.92; P <.001, Table 1). Differences were noted by age in partially adjusted analysis with decreased encounter rates for children aged 2 to <6 years (RR: 0.70 [CI: 0.58–0.85], P <.001) and 6 to <13 years (RR: 0.79 [CI: 0.64–0.98], P = .004), but no significant change for children <2 or >13 years of age. There was also a decrease for children reported as Black non-Hispanic (RR: 0.78 [CI: 0.64–0.96], P = .002) and White non-Hispanic (RR: 0.80 [CI: 0.65–0.99], P = .006) with no change for children recorded as Hispanic. Encounters with public insurance decreased significantly (RR: 0.81 [CI: 0.70–0.93], P <.001) without changes in rates for self-pay or private insurance encounters. Encounter trends were also variable by site with 2 of 9 institutions having significantly reduced daily diagnosis rates. After full adjustment with marginal estimation to average over model covariates, including ISS, the overall reduction in encounter rate during the pandemic in the diagnosis-code cohort was 19% (adjusted rate ratio [ARR]: 0.81 [CI: 0.75–0.88], P <.001).

TABLE 1

Rates of Child Abuse Encounters by Pandemic Time Period (Diagnosis-Code Cohort)

Before Pandemic: Encounters per Day (N)During Pandemic: Encounters per Day (N)Unadjusted Rate RatioPartially Adjusted Rate Ratio (99% CI)aPFully Adjusted Rate Ratio (99% CI)bP
Overall 4.57 (3755) 3.76 (1372) 0.82 0.82 (0.73–0.92) <.001 0.81 (0.75–0.88) <.001 
Age        
 0 to <6 mo 0.80 (656) 0.74 (269) 0.93 0.92 (0.74–1.15) .33 — — 
 6 to <12 mo 0.44 (365) 0.41 (149) 0.93 0.92 (0.68–1.23) .44 — — 
 12 to <24 mo 0.53 (439) 0.44 (160) 0.83 0.82 (0.62–1.08) .06 — — 
 2 to <6 y 1.24 (1015) 0.87 (317) 0.70 0.70 (0.58–0.85) <.001 — — 
 6 to <13 y 0.98 (806) 0.78 (284) 0.80 0.79 (0.64–0.98) .004 — — 
 13 to <18 y 0.58 (474) 0.53 (193) 0.91 0.91 (0.70–1.18) .37 — — 
Sex        
 Female 2.09 (1716) 1.75 (638) 0.84 0.83 (0.72–0.96) .001 — — 
 Male 2.48 (2039) 2.01 (734) 0.81 0.81 (0.71–0.92) <.001 — — 
Race/ethnicity        
 Hispanic 0.51 (421) 0.45 (164) 0.88 0.87 (0.60–1.28) .36 — — 
 Non-Hispanic additional racial groups 0.42 (342) 0.41 (151) 0.98 0.99 (0.66–1.48) .95 — — 
 Non-Hispanic Black 1.84 (1507) 1.44 (526) 0.78 0.78 (0.64–0.96) .002 — — 
 Non-Hispanic White 1.81 (1485) 1.45 (531) 0.80 0.80 (0.65–0.99) .006 — — 
Primary payer        
 Private 0.87 (711) 0.82 (300) 0.94 0.95 (0.72–1.24) .60 — — 
 Public 3.39 (2787) 2.75 (1002) 0.81 0.81 (0.70–0.93) <.001 — — 
 Self-pay 0.31 (257) 0.19 (70) 0.61 0.61 (0.36–1.04) .02 — — 
Site        
 A 1.00 (825) 0.71 (259) 0.71 0.70 (0.55–0.90) <.001 — — 
 B 0.91 (750) 0.65 (239) 0.71 0.71 (0.55–0.93) <.001 — — 
 C 0.74 (607) 0.56 (205) 0.76 0.76 (0.57–1.01) .012 — — 
 D 0.56 (456) 0.46 (169) 0.82 0.83 (0.61–1.14) .13 — — 
 E 0.50 (407) 0.48 (175) 0.96 0.96 (0.70–1.33) .77 — — 
 F 0.38 (316) 0.38 (137) 1.00 0.97 (0.68–1.39) .84 — — 
 G 0.19 (159) 0.22 (82) 1.16 1.16 (0.72–1.86) .43 — — 
 H 0.21 (175) 0.19 (71) 0.90 0.91 (0.56–1.49) .62 — — 
 I 0.07 (60) 0.10 (35) 1.43 1.31 (0.62–2.76) .35 — — 
ISS        
 0–8 3.94 (3234) 3.17 (1158) 0.80 0.80 (0.72–0.90) <.001 0.80 (0.73–0.87) <.001 
 9–15 0.55 (452) 0.50 (184) 0.91 0.91 (0.69–1.22) .42 0.91 (0.72–1.14) .27 
 16+ 0.08 (69) 0.08 (30) 1.00 0.98 (0.48–2.00) .93 0.97 (0.55–1.70) .89 
MAIS        
 0–2 3.97 (3257) 3.21 (1172) 0.81 0.81 (0.72–0.91) <.001 0.80 (0.73–0.88) <.001 
 3–6 0.61 (498) 0.55 (200) 0.90 0.90 (0.68–1.20) .35 0.90 (0.72–1.11) .19 
Triage category        
 ESI1 0.18 (144) 0.16 (58) 0.89 0.90 (0.47–1.74) .69 0.90 (0.60–1.34) .49 
 ESI2 1.73 (1419) 1.43 (522) 0.83 0.83 (0.67–1.02) .02 0.82 (0.72–0.94) <.001 
 ESI3 1.94 (1596) 1.67 (611) 0.86 0.86 (0.70–1.05) .05 0.85 (0.76–0.97) <.001 
 ESI4 0.64 (524) 0.41 (150) 0.64 0.64 (0.44–0.95) .003 0.64 (0.50–0.81) <.001 
 ESI5 0.04 (29) 0.05 (18) 1.25 1.39 (0.40–4.91) .50 1.38 (0.64–3.00) .28 
ED dispositionc        
 Admitted/transferred/died 1.32 (1082) 1.14 (417) 0.86 0.86 (0.71–1.06) .06 0.86 (0.74–1.00) .009 
 Discharged 2.83 (2327) 2.23 (813) 0.79 0.78 (0.68–0.90) <.001 0.78 (0.70–0.87) <.001 
Deathc        
 No 4.16 (3412) 3.37 (1231) 0.81 0.81 (0.72–0.91) <.001 0.80 (0.74–0.88) <.001 
 Yes 0.03 (27) 0.01 (4) 0.33 0.33 (0.05–2.08) .12 0.33 (0.08–1.31) .04 
Before Pandemic: Encounters per Day (N)During Pandemic: Encounters per Day (N)Unadjusted Rate RatioPartially Adjusted Rate Ratio (99% CI)aPFully Adjusted Rate Ratio (99% CI)bP
Overall 4.57 (3755) 3.76 (1372) 0.82 0.82 (0.73–0.92) <.001 0.81 (0.75–0.88) <.001 
Age        
 0 to <6 mo 0.80 (656) 0.74 (269) 0.93 0.92 (0.74–1.15) .33 — — 
 6 to <12 mo 0.44 (365) 0.41 (149) 0.93 0.92 (0.68–1.23) .44 — — 
 12 to <24 mo 0.53 (439) 0.44 (160) 0.83 0.82 (0.62–1.08) .06 — — 
 2 to <6 y 1.24 (1015) 0.87 (317) 0.70 0.70 (0.58–0.85) <.001 — — 
 6 to <13 y 0.98 (806) 0.78 (284) 0.80 0.79 (0.64–0.98) .004 — — 
 13 to <18 y 0.58 (474) 0.53 (193) 0.91 0.91 (0.70–1.18) .37 — — 
Sex        
 Female 2.09 (1716) 1.75 (638) 0.84 0.83 (0.72–0.96) .001 — — 
 Male 2.48 (2039) 2.01 (734) 0.81 0.81 (0.71–0.92) <.001 — — 
Race/ethnicity        
 Hispanic 0.51 (421) 0.45 (164) 0.88 0.87 (0.60–1.28) .36 — — 
 Non-Hispanic additional racial groups 0.42 (342) 0.41 (151) 0.98 0.99 (0.66–1.48) .95 — — 
 Non-Hispanic Black 1.84 (1507) 1.44 (526) 0.78 0.78 (0.64–0.96) .002 — — 
 Non-Hispanic White 1.81 (1485) 1.45 (531) 0.80 0.80 (0.65–0.99) .006 — — 
Primary payer        
 Private 0.87 (711) 0.82 (300) 0.94 0.95 (0.72–1.24) .60 — — 
 Public 3.39 (2787) 2.75 (1002) 0.81 0.81 (0.70–0.93) <.001 — — 
 Self-pay 0.31 (257) 0.19 (70) 0.61 0.61 (0.36–1.04) .02 — — 
Site        
 A 1.00 (825) 0.71 (259) 0.71 0.70 (0.55–0.90) <.001 — — 
 B 0.91 (750) 0.65 (239) 0.71 0.71 (0.55–0.93) <.001 — — 
 C 0.74 (607) 0.56 (205) 0.76 0.76 (0.57–1.01) .012 — — 
 D 0.56 (456) 0.46 (169) 0.82 0.83 (0.61–1.14) .13 — — 
 E 0.50 (407) 0.48 (175) 0.96 0.96 (0.70–1.33) .77 — — 
 F 0.38 (316) 0.38 (137) 1.00 0.97 (0.68–1.39) .84 — — 
 G 0.19 (159) 0.22 (82) 1.16 1.16 (0.72–1.86) .43 — — 
 H 0.21 (175) 0.19 (71) 0.90 0.91 (0.56–1.49) .62 — — 
 I 0.07 (60) 0.10 (35) 1.43 1.31 (0.62–2.76) .35 — — 
ISS        
 0–8 3.94 (3234) 3.17 (1158) 0.80 0.80 (0.72–0.90) <.001 0.80 (0.73–0.87) <.001 
 9–15 0.55 (452) 0.50 (184) 0.91 0.91 (0.69–1.22) .42 0.91 (0.72–1.14) .27 
 16+ 0.08 (69) 0.08 (30) 1.00 0.98 (0.48–2.00) .93 0.97 (0.55–1.70) .89 
MAIS        
 0–2 3.97 (3257) 3.21 (1172) 0.81 0.81 (0.72–0.91) <.001 0.80 (0.73–0.88) <.001 
 3–6 0.61 (498) 0.55 (200) 0.90 0.90 (0.68–1.20) .35 0.90 (0.72–1.11) .19 
Triage category        
 ESI1 0.18 (144) 0.16 (58) 0.89 0.90 (0.47–1.74) .69 0.90 (0.60–1.34) .49 
 ESI2 1.73 (1419) 1.43 (522) 0.83 0.83 (0.67–1.02) .02 0.82 (0.72–0.94) <.001 
 ESI3 1.94 (1596) 1.67 (611) 0.86 0.86 (0.70–1.05) .05 0.85 (0.76–0.97) <.001 
 ESI4 0.64 (524) 0.41 (150) 0.64 0.64 (0.44–0.95) .003 0.64 (0.50–0.81) <.001 
 ESI5 0.04 (29) 0.05 (18) 1.25 1.39 (0.40–4.91) .50 1.38 (0.64–3.00) .28 
ED dispositionc        
 Admitted/transferred/died 1.32 (1082) 1.14 (417) 0.86 0.86 (0.71–1.06) .06 0.86 (0.74–1.00) .009 
 Discharged 2.83 (2327) 2.23 (813) 0.79 0.78 (0.68–0.90) <.001 0.78 (0.70–0.87) <.001 
Deathc        
 No 4.16 (3412) 3.37 (1231) 0.81 0.81 (0.72–0.91) <.001 0.80 (0.74–0.88) <.001 
 Yes 0.03 (27) 0.01 (4) 0.33 0.33 (0.05–2.08) .12 0.33 (0.08–1.31) .04 
a

Partially adjusted estimates come from separate multivariable Poisson regression models for each characteristic, each with the following covariates: pandemic time period, site, calendar month, and an interaction between pandemic time period and the characteristic. Estimates and confidence intervals represent the contrast within each characteristic (eg, Hispanic ethnicity) of rates during the pandemic period compared with the prepandemic period.

b

Fully adjusted estimates come from separate multivariable Poisson regression models for each severity indicator, each with the following covariates: pandemic time period, age, sex, race/ethnicity, primary payer, site, calendar month and pandemic time period interactions with site and severity. The overall estimate is reported from the multivariable ISS model.

c

All visits from Site F were excluded from ED disposition and death models due to incomplete disposition data.

—, fully adjusted rate ratios were not estimated for demographic variables; these variables were not interacted with pandemic time period in the fully adjusted model due to the interaction terms being insignificant in the partially adjusted model.

Injury Code Cohort

Encounter rates for high-risk injuries (injury code cohort) also had a statistically significant reduction by partial adjustment (3.28 to 2.95 encounters per day, RR: 0.90 [CI: 0.81–0.99], P = .007, Table 2). There were no significant differences by specific demographic characteristic categories between the prepandemic and pandemic periods. After full adjustment, the reduction in encounter rate was 10% (ARR: 0.90 [CI: 0.82–0.98], P = .002).

TABLE 2

Rates of Child Abuse Encounters by Pandemic Time Period (Injury-Code Cohort)

Before Pandemic: Encounters per day (N)During Pandemic: Encounters per day (N)Unadjusted Rate RatioPartially Adjusted Rate Ratio (99% CI)aPFully Adjusted Rate Ratio (99% CI)bP
Overall 3.28 (2693) 2.95 (1078) 0.90 0.90 (0.81–0.99) .007 0.90 (0.82–0.98) .002 
Age        
 0 to <6 mo 2.09 (1713) 1.88 (685) 0.90 0.90 (0.79–1.01) .02 — — 
 6 to <12 mo 0.99 (809) 0.92 (335) 0.93 0.93 (0.78–1.11) .28 — — 
 12 to <24 mo 0.21 (171) 0.16 (58) 0.76 0.76 (0.50–1.15) .09 — — 
Sex        
 Female 1.54 (1261) 1.35 (494) 0.88 0.88 (0.76–1.01) .02 — — 
 Male 1.74 (1432) 1.60 (584) 0.92 0.91 (0.80–1.04) .08 — — 
Race/ethnicity        
 Hispanic 0.50 (411) 0.48 (175) 0.96 0.95 (0.71–1.28) .68 — — 
 Non-Hispanic additional racial groups 0.35 (290) 0.37 (134) 1.06 1.04 (0.74–1.45) .79 — — 
 Non-Hispanic Black 0.91 (745) 0.73 (268) 0.80 0.81 (0.64–1.02) .02 — — 
 Non-Hispanic White 1.52 (1247) 1.37 (501) 0.90 0.90 (0.76–1.07) .11 — — 
Primary payer        
 Private 1.17 (963) 1.13 (412) 0.97 0.96 (0.80–1.15) .55 — — 
 Public 2.00 (1638) 1.75 (638) 0.88 0.87 (0.76–1.01) .014 — — 
 Self-pay 0.11 (92) 0.08 (28) 0.73 0.68 (0.35–1.32) .13 — — 
Site        
 A 0.53 (435) 0.42 (154) 0.79 0.79 (0.61–1.04) .03 — — 
 B 0.47 (382) 0.39 (142) 0.83 0.83 (0.63–1.10) .09 — — 
 C 0.40 (328) 0.36 (131) 0.90 0.89 (0.67–1.20) .33 — — 
 D 0.58 (473) 0.51 (185) 0.88 0.88 (0.68–1.12) .17 — — 
 E 0.35 (291) 0.33 (120) 0.94 0.92 (0.68–1.26) .51 — — 
 F 0.34 (283) 0.36 (130) 1.06 1.03 (0.76–1.39) .81 — — 
 G 0.33 (272) 0.35 (127) 1.06 1.05 (0.77–1.42) .71 — — 
 H 0.14 (116) 0.12 (43) 0.86 0.83 (0.50–1.39) .35 — — 
 I 0.14 (113) 0.13 (46) 0.93 0.91 (0.55–1.51) .64 — — 
ISS        
 0–8 2.01 (1650) 1.71 (624) 0.85 0.85 (0.75–0.96) <.001 0.85 (0.75–0.96) <.001 
 9–15 1.16 (951) 1.15 (418) 0.99 0.98 (0.84–1.15) .81 0.98 (0.85–1.15) .80 
 16+ 0.11 (92) 0.10 (36) 0.91 0.88 (0.51–1.49) .53 0.88 (0.53–1.45) .50 
MAIS        
 0–2 2.03 (1666) 1.73 (633) 0.85 0.85 (0.75–0.97) .001 0.85 (0.75–0.96) <.001 
 3–6 1.25 (1027) 1.22 (445) 0.98 0.97 (0.83–1.14) .63 0.97 (0.84–1.12) .60 
Triage category        
 ESI1 0.24 (194) 0.21 (76) 0.88 0.88 (0.58–1.34) .43 0.88 (0.62–1.24) .34 
 ESI2 1.05 (863) 0.98 (358) 0.93 0.93 (0.76–1.13) .34 0.93 (0.79–1.09) .25 
 ESI3 1.17 (960) 1.12 (410) 0.96 0.96 (0.80–1.15) .54 0.96 (0.82–1.11) .46 
 ESI4 0.65 (537) 0.55 (199) 0.85 0.83 (0.64–1.08) .07 0.83 (0.67–1.03) .03 
 ESI5 0.08 (67) 0.05 (17) 0.63 0.57 (0.24–1.33) .09 0.57 (0.28–1.15) .04 
ED dispositionc        
 Admitted/transferred/died 1.32 (1081) 1.21 (441) 0.92 0.92 (0.79–1.07) .14 0.92 (0.79–1.06) .12 
 Discharged 1.60 (1317) 1.39 (506) 0.87 0.86 (0.75–0.99) .007 0.86 (0.75–0.99) .005 
Deathc     —   
 No 2.91 (2388) 2.59 (945) 0.89 0.89 (0.80–0.99) .006 0.89 (0.80–0.98) .002 
 Yes 0.03 (22) 0.01 (3) 0.33 0.31 (0.05–1.78) .08 0.31 (0.06–1.49) .05 
Before Pandemic: Encounters per day (N)During Pandemic: Encounters per day (N)Unadjusted Rate RatioPartially Adjusted Rate Ratio (99% CI)aPFully Adjusted Rate Ratio (99% CI)bP
Overall 3.28 (2693) 2.95 (1078) 0.90 0.90 (0.81–0.99) .007 0.90 (0.82–0.98) .002 
Age        
 0 to <6 mo 2.09 (1713) 1.88 (685) 0.90 0.90 (0.79–1.01) .02 — — 
 6 to <12 mo 0.99 (809) 0.92 (335) 0.93 0.93 (0.78–1.11) .28 — — 
 12 to <24 mo 0.21 (171) 0.16 (58) 0.76 0.76 (0.50–1.15) .09 — — 
Sex        
 Female 1.54 (1261) 1.35 (494) 0.88 0.88 (0.76–1.01) .02 — — 
 Male 1.74 (1432) 1.60 (584) 0.92 0.91 (0.80–1.04) .08 — — 
Race/ethnicity        
 Hispanic 0.50 (411) 0.48 (175) 0.96 0.95 (0.71–1.28) .68 — — 
 Non-Hispanic additional racial groups 0.35 (290) 0.37 (134) 1.06 1.04 (0.74–1.45) .79 — — 
 Non-Hispanic Black 0.91 (745) 0.73 (268) 0.80 0.81 (0.64–1.02) .02 — — 
 Non-Hispanic White 1.52 (1247) 1.37 (501) 0.90 0.90 (0.76–1.07) .11 — — 
Primary payer        
 Private 1.17 (963) 1.13 (412) 0.97 0.96 (0.80–1.15) .55 — — 
 Public 2.00 (1638) 1.75 (638) 0.88 0.87 (0.76–1.01) .014 — — 
 Self-pay 0.11 (92) 0.08 (28) 0.73 0.68 (0.35–1.32) .13 — — 
Site        
 A 0.53 (435) 0.42 (154) 0.79 0.79 (0.61–1.04) .03 — — 
 B 0.47 (382) 0.39 (142) 0.83 0.83 (0.63–1.10) .09 — — 
 C 0.40 (328) 0.36 (131) 0.90 0.89 (0.67–1.20) .33 — — 
 D 0.58 (473) 0.51 (185) 0.88 0.88 (0.68–1.12) .17 — — 
 E 0.35 (291) 0.33 (120) 0.94 0.92 (0.68–1.26) .51 — — 
 F 0.34 (283) 0.36 (130) 1.06 1.03 (0.76–1.39) .81 — — 
 G 0.33 (272) 0.35 (127) 1.06 1.05 (0.77–1.42) .71 — — 
 H 0.14 (116) 0.12 (43) 0.86 0.83 (0.50–1.39) .35 — — 
 I 0.14 (113) 0.13 (46) 0.93 0.91 (0.55–1.51) .64 — — 
ISS        
 0–8 2.01 (1650) 1.71 (624) 0.85 0.85 (0.75–0.96) <.001 0.85 (0.75–0.96) <.001 
 9–15 1.16 (951) 1.15 (418) 0.99 0.98 (0.84–1.15) .81 0.98 (0.85–1.15) .80 
 16+ 0.11 (92) 0.10 (36) 0.91 0.88 (0.51–1.49) .53 0.88 (0.53–1.45) .50 
MAIS        
 0–2 2.03 (1666) 1.73 (633) 0.85 0.85 (0.75–0.97) .001 0.85 (0.75–0.96) <.001 
 3–6 1.25 (1027) 1.22 (445) 0.98 0.97 (0.83–1.14) .63 0.97 (0.84–1.12) .60 
Triage category        
 ESI1 0.24 (194) 0.21 (76) 0.88 0.88 (0.58–1.34) .43 0.88 (0.62–1.24) .34 
 ESI2 1.05 (863) 0.98 (358) 0.93 0.93 (0.76–1.13) .34 0.93 (0.79–1.09) .25 
 ESI3 1.17 (960) 1.12 (410) 0.96 0.96 (0.80–1.15) .54 0.96 (0.82–1.11) .46 
 ESI4 0.65 (537) 0.55 (199) 0.85 0.83 (0.64–1.08) .07 0.83 (0.67–1.03) .03 
 ESI5 0.08 (67) 0.05 (17) 0.63 0.57 (0.24–1.33) .09 0.57 (0.28–1.15) .04 
ED dispositionc        
 Admitted/transferred/died 1.32 (1081) 1.21 (441) 0.92 0.92 (0.79–1.07) .14 0.92 (0.79–1.06) .12 
 Discharged 1.60 (1317) 1.39 (506) 0.87 0.86 (0.75–0.99) .007 0.86 (0.75–0.99) .005 
Deathc     —   
 No 2.91 (2388) 2.59 (945) 0.89 0.89 (0.80–0.99) .006 0.89 (0.80–0.98) .002 
 Yes 0.03 (22) 0.01 (3) 0.33 0.31 (0.05–1.78) .08 0.31 (0.06–1.49) .05 
a

Partially adjusted estimates come from separate multivariable Poisson regression models for each characteristic, each with the following covariates: pandemic time period, site, calendar month, and an interaction between pandemic time period and the characteristic. Estimates and confidence intervals represent the contrast within each characteristic (eg, Hispanic ethnicity) of rates during the pandemic period compared with the prepandemic period.

b

Fully adjusted estimates come from separate multivariable Poisson regression models for each severity indicator, each with the following covariates: pandemic time period, age, sex, race/ethnicity, primary payer, site, and calendar month and interactions between pandemic time period and severity. The overall estimate is reported from the multivariable ISS model.

c

All visits from Site F were excluded from ED disposition and death models due to incomplete disposition data.

—, fully adjusted rate ratios were not estimated for demographic variables; these variables were not interacted with pandemic time period in the fully adjusted model due to the interaction terms being insignificant in the partially adjusted model.

Skeletal Survey Cohort

Encounter rates for child physical abuse evaluation by skeletal survey completion (skeletal survey cohort) did not have a statistically significant reduction by partial adjustment (3.8 to 3.5 encounters per day, RR: 0.92 [CI: 0.84–1.01], P = .03, Table 3). There were no significant differences in demographic factors between the prepandemic and pandemic periods. After full adjustment, there was not a significant reduction in encounter rate for the skeletal survey cohort (ARR: 0.92 [CI: 0.84–1.00], P = .013).

TABLE 3

Rates of Child Abuse Encounters by Pandemic Time Period (Skeletal-Survey Cohort)

Before Pandemic: Encounters per day (N)During Pandemic: Encounters per day (N)Unadjusted Rate RatioPartially Adjusted Rate Ratio (99% CI)aPFully Adjusted Rate Ratio (99% CI)bP
Overall 3.78 (3106) 3.48 (1270) 0.92 0.92 (0.84–1.01) .03 0.92 (0.84–1.00) .013 
Age        
 0 to <6 mo 1.74 (1425) 1.65 (604) 0.95 0.95 (0.83–1.09) .38 — — 
 6 to <12 mo 1.11 (914) 1.01 (370) 0.91 0.91 (0.77–1.08) .17 — — 
 12 to <24 mo 0.93 (767) 0.81 (296) 0.87 0.87 (0.72–1.05) .06 — — 
Sex        
 Female 1.68 (1377) 1.49 (544) 0.89 0.89 (0.78–1.02) .03 — — 
 Male 2.11 (1729) 1.99 (726) 0.94 0.95 (0.84–1.07) .22 — — 
Race/ethnicity        
 Hispanic 0.48 (392) 0.49 (180) 1.02 1.03 (0.75–1.43) .79 — — 
 Non-Hispanic additional racial groups 0.42 (348) 0.41 (148) 0.98 0.96 (0.67–1.36) .75 — — 
 Non-Hispanic Black 1.21 (992) 1.06 (388) 0.88 0.88 (0.71–1.09) .13 — — 
 Non-Hispanic White 1.67 (1374) 1.52 (554) 0.91 0.91 (0.76–1.09) .17 — — 
Primary payer        
 Private 0.95 (777) 0.92 (334) 0.97 0.97 (0.78–1.20) .70 — — 
 Public 2.69 (2212) 2.46 (897) 0.91 0.91 (0.80–1.04) .07 — — 
 Self-pay 0.14 (117) 0.11 (39) 0.79 0.75 (0.41–1.39) .23 — — 
Site        
 A 1.08 (883) 0.94 (342) 0.87 0.87 (0.73–1.05) .05 — — 
 B 0.56 (459) 0.51 (187) 0.91 0.92 (0.72–1.18) .37 — — 
 C 0.46 (378) 0.36 (130) 0.78 0.77 (0.58–1.04) .02 — — 
 D 0.53 (435) 0.48 (174) 0.91 0.90 (0.70–1.16) .29 — — 
 E 0.39 (318) 0.37 (134) 0.95 0.95 (0.71–1.27) .65 — — 
 F 0.31 (251) 0.30 (111) 0.97 1.00 (0.72–1.38) .97 — — 
 G 0.23 (189) 0.27 (97) 1.17 1.16 (0.81–1.65) .30 — — 
 H 0.16 (133) 0.15 (55) 0.94 0.93 (0.59–1.47) .69 — — 
 I 0.07 (60) 0.11 (40) 1.57 1.50 (0.84–2.69) .07 — — 
ISS        
 0–8 2.85 (2336) 2.55 (932) 0.89 0.90 (0.81–1.00) .0103 0.90 (0.81–0.99) .006 
 9–15 0.88 (720) 0.87 (317) 0.99 0.99 (0.82–1.20) .90 0.99 (0.83–1.18) .90 
 16+ 0.06 (50) 0.06 (21) 1.00 0.95 (0.46–1.94) .84 0.95 (0.48–1.85) .83 
MAIS        
 0–2 2.86 (2352) 2.58 (940) 0.90 0.90 (0.81–1.00) .012 0.90 (0.81–0.99) .006 
 3–6 0.92 (754) 0.90 (330) 0.98 0.99 (0.82–1.19) .84 0.99 (0.83–1.17) .82 
Triage category        
 ESI1 0.22 (182) 0.16 (60) 0.73 0.74 (0.44–1.25) .14 0.74 (0.51–1.09) .05 
 ESI2 1.26 (1034) 1.19 (436) 0.94 0.95 (0.78–1.16) .50 0.95 (0.82–1.10) .36 
 ESI3 1.89 (1553) 1.77 (647) 0.94 0.94 (0.80–1.10) .31 0.94 (0.83–1.06) .17 
 ESI4 0.36 (292) 0.30 (109) 0.83 0.84 (0.57–1.24) .25 0.84 (0.63–1.12) .12 
 ESI5 0.04 (30) 0.01 (5) 0.25 0.38 (0.07–2.01) .13 0.38 (0.11–1.30) .04 
ED dispositionc        
 Admitted/transferred/died 1.43 (1177) 1.30 (476) 0.91 0.91 (0.78–1.07) .14 0.91 (0.79–1.05) .09 
 Discharged 2.03 (1667) 1.86 (679) 0.92 0.92 (0.80–1.05) .11 0.92 (0.82–1.03) .06 
Deathc        
 No 3.42 (2810) 3.10 (1132) 0.91 0.91 (0.83–1.00) .009 0.91 (0.83–1.00) .007 
 Yes 0.05 (45) 0.07 (27) 1.40 1.35 (0.71–2.59) .23 1.35 (0.72–2.53) .21 
Before Pandemic: Encounters per day (N)During Pandemic: Encounters per day (N)Unadjusted Rate RatioPartially Adjusted Rate Ratio (99% CI)aPFully Adjusted Rate Ratio (99% CI)bP
Overall 3.78 (3106) 3.48 (1270) 0.92 0.92 (0.84–1.01) .03 0.92 (0.84–1.00) .013 
Age        
 0 to <6 mo 1.74 (1425) 1.65 (604) 0.95 0.95 (0.83–1.09) .38 — — 
 6 to <12 mo 1.11 (914) 1.01 (370) 0.91 0.91 (0.77–1.08) .17 — — 
 12 to <24 mo 0.93 (767) 0.81 (296) 0.87 0.87 (0.72–1.05) .06 — — 
Sex        
 Female 1.68 (1377) 1.49 (544) 0.89 0.89 (0.78–1.02) .03 — — 
 Male 2.11 (1729) 1.99 (726) 0.94 0.95 (0.84–1.07) .22 — — 
Race/ethnicity        
 Hispanic 0.48 (392) 0.49 (180) 1.02 1.03 (0.75–1.43) .79 — — 
 Non-Hispanic additional racial groups 0.42 (348) 0.41 (148) 0.98 0.96 (0.67–1.36) .75 — — 
 Non-Hispanic Black 1.21 (992) 1.06 (388) 0.88 0.88 (0.71–1.09) .13 — — 
 Non-Hispanic White 1.67 (1374) 1.52 (554) 0.91 0.91 (0.76–1.09) .17 — — 
Primary payer        
 Private 0.95 (777) 0.92 (334) 0.97 0.97 (0.78–1.20) .70 — — 
 Public 2.69 (2212) 2.46 (897) 0.91 0.91 (0.80–1.04) .07 — — 
 Self-pay 0.14 (117) 0.11 (39) 0.79 0.75 (0.41–1.39) .23 — — 
Site        
 A 1.08 (883) 0.94 (342) 0.87 0.87 (0.73–1.05) .05 — — 
 B 0.56 (459) 0.51 (187) 0.91 0.92 (0.72–1.18) .37 — — 
 C 0.46 (378) 0.36 (130) 0.78 0.77 (0.58–1.04) .02 — — 
 D 0.53 (435) 0.48 (174) 0.91 0.90 (0.70–1.16) .29 — — 
 E 0.39 (318) 0.37 (134) 0.95 0.95 (0.71–1.27) .65 — — 
 F 0.31 (251) 0.30 (111) 0.97 1.00 (0.72–1.38) .97 — — 
 G 0.23 (189) 0.27 (97) 1.17 1.16 (0.81–1.65) .30 — — 
 H 0.16 (133) 0.15 (55) 0.94 0.93 (0.59–1.47) .69 — — 
 I 0.07 (60) 0.11 (40) 1.57 1.50 (0.84–2.69) .07 — — 
ISS        
 0–8 2.85 (2336) 2.55 (932) 0.89 0.90 (0.81–1.00) .0103 0.90 (0.81–0.99) .006 
 9–15 0.88 (720) 0.87 (317) 0.99 0.99 (0.82–1.20) .90 0.99 (0.83–1.18) .90 
 16+ 0.06 (50) 0.06 (21) 1.00 0.95 (0.46–1.94) .84 0.95 (0.48–1.85) .83 
MAIS        
 0–2 2.86 (2352) 2.58 (940) 0.90 0.90 (0.81–1.00) .012 0.90 (0.81–0.99) .006 
 3–6 0.92 (754) 0.90 (330) 0.98 0.99 (0.82–1.19) .84 0.99 (0.83–1.17) .82 
Triage category        
 ESI1 0.22 (182) 0.16 (60) 0.73 0.74 (0.44–1.25) .14 0.74 (0.51–1.09) .05 
 ESI2 1.26 (1034) 1.19 (436) 0.94 0.95 (0.78–1.16) .50 0.95 (0.82–1.10) .36 
 ESI3 1.89 (1553) 1.77 (647) 0.94 0.94 (0.80–1.10) .31 0.94 (0.83–1.06) .17 
 ESI4 0.36 (292) 0.30 (109) 0.83 0.84 (0.57–1.24) .25 0.84 (0.63–1.12) .12 
 ESI5 0.04 (30) 0.01 (5) 0.25 0.38 (0.07–2.01) .13 0.38 (0.11–1.30) .04 
ED dispositionc        
 Admitted/transferred/died 1.43 (1177) 1.30 (476) 0.91 0.91 (0.78–1.07) .14 0.91 (0.79–1.05) .09 
 Discharged 2.03 (1667) 1.86 (679) 0.92 0.92 (0.80–1.05) .11 0.92 (0.82–1.03) .06 
Deathc        
 No 3.42 (2810) 3.10 (1132) 0.91 0.91 (0.83–1.00) .009 0.91 (0.83–1.00) .007 
 Yes 0.05 (45) 0.07 (27) 1.40 1.35 (0.71–2.59) .23 1.35 (0.72–2.53) .21 
a

Partially adjusted estimates come from separate multivariable Poisson regression models for each characteristic, each with the following covariates: pandemic time period, site, calendar month, and an interaction between pandemic time period and the characteristic. Estimates and confidence intervals represent the contrast within each characteristic (eg, Hispanic ethnicity) of rates during the pandemic period compared with the prepandemic period.

b

Fully adjusted estimates come from separate multivariable Poisson regression models for each severity indicator, each with the following covariates: pandemic time period, age, sex, race/ethnicity, primary payer, site, calendar month and interactions between pandemic time period and severity. The overall estimate is reported from the multivariable ISS model.

c

All visits from Site F were excluded from ED disposition and death models due to incomplete disposition data.

—, fully adjusted rate ratios were not estimated for demographic variables; these variables were not interacted with pandemic time period in the fully adjusted model due to the interaction terms being insignificant in the partially adjusted model.

For all methods of identifying suspected child abuse, the magnitude of reduction for abuse encounter rates was smaller than the decrease in total encounters with the most marked reduction in abuse encounter rates during the first months of the pandemic (Fig 2).

FIGURE 2

Average daily encounters per month in prepandemic (Jan 2018–March 2020) and pandemic (April 2020–March 2021) periods. Averages represent unadjusted total counts across institutions.

FIGURE 2

Average daily encounters per month in prepandemic (Jan 2018–March 2020) and pandemic (April 2020–March 2021) periods. Averages represent unadjusted total counts across institutions.

Close modal

In the diagnosis-code cohort, low-severity presentations by ISS (0–8) were reduced in partially adjusted analysis (RR: 0.80 [CI: 0.72–0.90], P <.001), whereas higher ISS category presentations did not change significantly (ISS 9–15: P = .42, ISS 16+: P = .93, Table 1). After full adjustment, including interaction with ISS, reduction in low-severity ISS presentation was 20% (ISS: 0–8; ARR: 0.80 [CI: 0.73–0.87], P <.001). Other independently modeled clinical severity measures revealed similar reductions in low-severity encounters in the diagnosis code cohort, including MAIS (0–2, ARR: 0.80 [CI: 0.73–0.88], P <.001), ED discharges (ARR: 0.78 [CI: 0.70–0.87], P <.001), and hospital survival (ARR: 0.80 [CI: 0.74–0.88], P <.001). As with ISS, there were no significant changes in the rate for encounters with higher severity for each measure (Table 1).

Patterns for clinical severity were consistent in diagnosis code, injury code, and skeletal survey cohorts. After full adjustment, reductions in low-severity presentations by ISS were significant for both the injury code cohort (ARR: 0.85 [CI: 0.75–0.96], P <.001; Table 2) and the skeletal survey cohort (ARR: 0.90 [CI: 0.81–0.99], P = .006; Table 3); however, there were no detected changes in daily encounter rates with higher ISS scores. A similar reduction in low-severity encounters was observed when modeling low MAIS (injury code cohort: ARR: 0.85 [CI: 0.75–0.96], P <.001; skeletal survey cohort: ARR: 0.90 [CI: 0.81–0.99], P = .006) and hospital survival (injury code cohort: ARR: 0.89 [CI: 0.80–0.98], P = .002; skeletal survey cohort: ARR: 0.91 [CI: 0.83–1.0], P = .007) without changes in higher-severity encounter rates. ED discharges also decreased during the pandemic period in the injury code cohort (ARR: 0.86 [CI: 0.75–0.99], P = .005); there was no detected change in ED discharges when identified by skeletal survey. There were no changes in encounters with severe disposition (ie, admitted/transferred/died) for either the injury code or skeletal survey code cohort.

Our results reveal that pediatric ED encounters concerning child physical abuse by ICD-10-CM codes decreased by 19% during the pandemic when assessed across all ages within a multicenter pediatric ED data registry. Rates of encounters among children <2 years old with high-risk injuries were reduced by 10%, whereas children with a potential concern for abuse as indicated by skeletal survey completion did not have a significant reduction. The decrease in high-risk injury identification, but not in rates of skeletal survey, implies that decreases were not due to decreased likelihood of clinicians to evaluate or identify abuse. Additionally, our data support our hypothesis regarding clinical severity and presentation to medical care: encounter rates with lower clinical severity decreased during the pandemic whereas encounter rates with higher clinical severity were unchanged. This was largely consistent across identification methods and measures of severity.

Although reduced or stable emergency health care encounters related to child physical abuse may be reassuring, critical assessment is required to further understand and contextualize these results. With regard to reduced low-severity clinical encounters without change in high-severity clinical encounters, these results can be interpreted in at least 2 ways. First, if a reduction in low-severity clinical encounters is driven by decreased recognition whereas high-severity encounters continue to present for care due to medical need, our results would suggest that the actual population rate of abuse may not have decreased during the pandemic. Moreover, if any proportion of severe cases were undetected within medical care related to pandemic shifts, these results may suggest that overall abuse increased. A second interpretation is that the reduction in encounter rates represents a true decrease in the population rate of child physical abuse. A true decrease could result from novel protective factors within the pandemic, such as having more caregivers at home, for instance, older children engaged in virtual schooling or parents who became unemployed or remained home related to social distancing.28  To explain the specific reduction within the lower-severity cases of abuse, the presence of additional caregivers would have to reduce children’s risk of less-severe physical abuse while failing to impact higher-severity occurrences. Our results are unable to distinguish between these interpretations, and additional delineation will require additional, multimodal data. These findings add information to previous studies which did not reveal differences in severity of child abuse by several markers in the medical record.27,28  Our results may be related to using more sensitive assessments of clinical severity.

Second, these results suggest that children experienced different risks during the COVID-19 pandemic-related to their age. Children <2 years of age had a smaller reduction in the rate of emergency care for concerns for physical abuse. Specifically, the significant reductions in the diagnosis code cohort were concentrated among preschool (2 to <6 years; 30% reduction) and school-aged (6 to <13 years; 20% reduction) children, whereas the reduction among youngest children (<6 months) was only 5% to 10% across identification methods. This pattern supports the importance of school encounters for the recognition of child physical abuse and may be consistent with the importance of mandatory reporter or alternative caregiver exposures for detection in preschool-aged children as well.49  Several assessments support that a driving force for decreased reports to CPS was decreased attendance at in-person school.11,30,33  Similarly, decreased in-person health care use may contribute to the reduced diagnosis of physical abuse.41,5054  We included race and ethnicity in our models, recognizing that these social constructs may associate with the differential impact of the pandemic and evaluation patterns for child abuse.4043  Our findings indicate that there was a differential reduction by race and ethnicity within the diagnosis code cohort, but not for other cohorts.

Third, our results reveal institutional variability. Specifically, in the diagnosis code cohort, 2 of 9 sites had significant reductions whereas 2 other sites revealed nonsignificant trends toward increases. Variability by site is consistent with previous literature that includes multiple single-site reports revealing increases in child maltreatment and emphasizes the need for contextualization of results by granularity of inquiry.2226  Local policy and practice such as virtual versus in-person school may influence variability by site.11,30,33  Thus, aggregate assessment across institutions is valuable for trends, yet may obscure significant variation evident at higher granularity, providing 1 potential unifying theory for the existing variability in the literature.

Two assumptions are worth reviewing to contextualize our results. First, the identification of child physical abuse-related encounters within EDs assumes this is a relevant way to understand harm experienced by children in retrospective study designs. Diagnosis codes do not represent a reference standard for diagnosis of abuse in isolation yet are frequently used to measure population trends, and, although skeletal surveys are predominantly performed in EDs related to physical abuse evaluation, other medical indications are possible.55,56  Thus, differences across 3 encounter identification methods may be reflective of variable sensitivity and specificity. For example, using ICD-10-CM child abuse codes seems the most restrictive by the number of encounters identified. This is consistent with previous studies that have suggested low sensitivity for health care-assigned child abuse diagnosis codes and reiterates the importance of complementary encounter identification schema.38,57  Second, the comparison of prepandemic to pandemic periods relies on the assumption that hospital catchment with regard to child physical abuse evaluation and diagnosis was not specifically impacted by the COVID-19 pandemic. For example, this includes the assumption that transfer patterns to participating institutions were not impacted by pandemic-related behavior changes.

Our findings are also subject to at least 2 limitations. First, this analysis focused on physical abuse and does not provide insight into neglect, sexual abuse, or other forms of child maltreatment, although it is likely that some cases of sexual abuse were included in general abuse diagnosis codes (eg, “child maltreatment” [T76.92XA]). Second, the collection of patients and hospitals within the PECARN Registry may not be representative of the community or other care settings. Results require replication and expansion in other datasets to clarify generalizability.

In conclusion, our results suggest pediatric emergency medical encounters related to physical abuse were reduced during the COVID-19 pandemic compared with previous years. In addition, these reductions were driven by decreases in lower-severity encounters and among preschool and school-aged children. Although a reduction could be reassuring, there was no evidence of a reduction in the rates of higher-severity injuries. This pattern calls for additional critical assessment to clarify the role of decreased recognition and the associated potential for unrecognized harm experienced by children during the COVID-19 pandemic versus true reduction related to novel protective factors.21 

Members of the PECARN Registry Study Group and PECARN Child Abuse Special Interest Group include: Kathleen M. Adelgais, MD MPH, Section of Pediatric Emergency Medicine, Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado; Lynn Babcock, MD, MS, Department of Pediatrics, University of Cincinnati, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio; James M. Chamberlain, MD, Children's National Hospital, George Washington University School of Medicine and Health Sciences, Washington, District of Columbia; Susan Duffy, MD, MPH, Division of Pediatric Emergency Medicine, Departments of Emergency Medicine and Pediatrics, Hasbro Children's Hospital, Warren Alpert Medical School of Medicine at Brown University, Providence, Rhode Island; Robert W. Grundmeier, MD, Division of General Pediatrics, Department of Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine, and the Center for Center for Pediatric Clinical Effectiveness, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Sadiqa Kendi, MD, Division of Pediatric Emergency Medicine, Boston Medical Center, Boston University School of Medicine, Boston, Massachusetts; E. Brooke Lerner, PhD, Department of Emergency Medicine, University at Buffalo, Buffalo, New York; Julia N. Magana, MD, Department of Emergency Medicine, University of California Davis Health, University of California Davis School of Medicine, Sacramento, California; Prashant Mahajan, MD, MPH, MBA, Department of Emergency Medicine, University of Michigan, Ann Arbor, Michigan; Stephanie M. Ruest, MD, MPH, Division of Pediatric Emergency Medicine, Departments of Emergency Medicine and Pediatrics, Hasbro Children's Hospital, Warren Alpert Medical School of Medicine at Brown University, Providence, Rhode Island; Bashar S. Shihabuddin, MD, MS, Section of Emergency Medicine, Division of Pediatrics, Nationwide Children's Hospital, The Ohio State University College of Medicine, Columbus, Ohio; Norma-Jean E Simon, MPH, MPA, Division of Emergency Medicine, Department of Pediatrics, Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, Illinois; Asha Tharayil, MD, Division of Pediatrics, Emergency Medicine, UT Southwestern Medical Center, Dallas, Texas; Danny G. Thomas, MD, MPH, Section of Pediatric Emergency Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin; and Joseph J. Zorc, MD, MSCE, Division of Emergency Medicine, Department of Pediatrics, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.

Additionally, we wish to acknowledge Cara Elsholz, BS, and Cody Olsen, MS, for their contributions to project planning and organization.

A complete list of study group authors appears in the Acknowledgments.

Dr Chaiyachati conceptualized and designed the study, drafted the initial manuscript, and reviewed and revised the manuscript; Drs Wood, Lindberg, Chun, and Alpern conceptualized and designed the study, and reviewed and revised the manuscript; Ms Carter and Dr Cook had full access to data and completed data analysis, including creating the tables and figures; and all authors, including group authors, approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

This information or content and conclusions are those of the author and should not be construed as the official position or policy of, nor should any endorsements be inferred by the Health Resources and Services Administration, US Department of Health and Human Services, or the US Government.

This multicenter assessment of emergency health care related to child physical abuse assesses changes in encounter rate and severity during the coronavirus disease 2019 pandemic.

FUNDING: This project work was supported by the Agency for Healthcare Research and Quality, grant number R01HS020270. Salary support for Dr Chaiyachati was provided by the National Institutes of Health/National Institute of Mental Health institutional training grant number T32 MH019112. PECARN is supported by the Health Resources and Services Administration (U03 MC33155) of the US Department of Health and Human Services, in the Maternal and Child Health Bureau, under the Emergency Medical Services for Children program through the following cooperative agreements: DCC-University of Utah, GLEMSCRN-Nationwide Children’s Hospital, HOMERUN-Cincinnati Children’s Hospital Medical Center, PEMNEWS-Columbia University Medical Center, PRIME-University of California at Davis Medical Center, CHaMP node-State University of New York at Buffalo, WPEMR-Seattle Children's Hospital, and SPARC-Rhode Island Hospital/Hasbro Children's Hospital. Funded by the National Institutes of Health (NIH).

CONFLICT OF INTEREST DISCLOSURES: The Children's Hospital of Philadelphia has received payment for the expert testimony of Drs Chaiyachati and Wood when subpoenaed for cases of suspected abuse. The remaining authors have no conflicts of interest to disclose.

     
  • ARR

    adjusted rate ratio

  •  
  • CI

    99% confidence interval

  •  
  • COVID-19

    coronavirus disease 2019

  •  
  • CPS

    child protective services

  •  
  • ED

    emergency department

  •  
  • ESI

    emergency severity index

  •  
  • ICD-10-CM

    International Classification of Diseases, 10th Revision, Clinical Modification

  •  
  • ISS

    injury severity scale

  •  
  • MAIS

    maximum abbreviated injury score

  •  
  • PECARN

    Pediatric Emergency Care Applied Research Network

  •  
  • RR

    rate ratio

1
Sidebotham
P
,
Golding
J
;
ALSPAC Study Team. Avon Longitudinal Study of Parents and Children
.
Child maltreatment in the “children of the nineties” a longitudinal study of parental risk factors
.
Child Abuse Negl
.
2001
;
25
(
9
):
1177
1200
2
Dubowitz
H
,
Kim
J
,
Black
MM
,
Weisbart
C
,
Semiatin
J
,
Magder
LS
.
Identifying children at high risk for a child maltreatment report
.
Child Abuse Negl
.
2011
;
35
(
2
):
96
104
3
Berger
RP
,
Fromkin
JB
,
Stutz
H
, et al
.
Abusive head trauma during a time of increased unemployment: a multicenter analysis
.
Pediatrics
.
2011
;
128
(
4
):
637
643
4
Schneider
W
,
Waldfogel
J
,
Brooks-Gunn
J
.
The Great Recession and risk for child abuse and neglect
.
Child Youth Serv Rev
.
2017
;
72
:
71
81
5
Huang
MI
,
O’Riordan
MA
,
Fitzenrider
E
,
McDavid
L
,
Cohen
AR
,
Robinson
S
.
Increased incidence of nonaccidental head trauma in infants associated with the economic recession
.
J Neurosurg Pediatr
.
2011
;
8
(
2
):
171
176
6
Wood
JN
,
French
B
,
Fromkin
J
, et al
.
Association of pediatric abusive head trauma rates with macroeconomic indicators
.
Acad Pediatr
.
2016
;
16
(
3
):
224
232
7
Keenan
HT
,
Marshall
SW
,
Nocera
MA
,
Runyan
DK
.
Increased incidence of inflicted traumatic brain injury in children after a natural disaster
.
Am J Prev Med
.
2004
;
26
(
3
):
189
193
8
Ettman
CK
,
Abdalla
SM
,
Cohen
GH
,
Sampson
L
,
Vivier
PM
,
Galea
S
.
Prevalence of depression symptoms in US adults before and during the COVID-19 pandemic
.
JAMA Netw Open
.
2020
;
3
(
9
):
e2019686
9
Twenge
JM
,
Joiner
TEUS
.
U.S. Census Bureau-assessed prevalence of anxiety and depressive symptoms in 2019 and during the 2020 COVID-19 pandemic
.
Depress Anxiety
.
2020
;
37
(
10
):
954
956
10
Silliman Cohen
RI
,
Bosk
EA
.
Vulnerable youth and the COVID-19 pandemic
.
Pediatrics
.
2020
;
146
(
1
):
e20201306
11
Baron
EJ
,
Goldstein
EG
,
Wallace
CT
.
Suffering in silence: how COVID-19 school closures inhibit the reporting of child maltreatment
.
J Public Econ
.
2020
;
190
:
104258
12
Humphreys
KL
,
Myint
MT
,
Zeanah
CH
.
Increased risk for family violence during the COVID-19 pandemic
.
Pediatrics
.
2020
;
146
(
1
):
e20200982
13
Patrick
SW
,
Henkhaus
LE
,
Zickafoose
JS
, et al
.
Well-being of parents and children during the COVID-19 pandemic: a national survey
.
Pediatrics
.
2020
;
146
(
4
):
e2020016824
14
Lawson
M
,
Piel
MH
,
Simon
M
.
Child maltreatment during the COVID-19 pandemic: consequences of parental job loss on psychological and physical abuse towards children
.
Child Abuse Negl
.
2020
;
110
(
Pt 2
):
104709
15
Griffith
AK
.
Parental burnout and child maltreatment during the COVID-19 pandemic
.
J Fam Violence
.
2022
;
37
:
725
731
16
Thomas
EY
,
Anurudran
A
,
Robb
K
,
Burke
TF
.
Spotlight on child abuse and neglect response in the time of COVID-19
.
Lancet Public Health
.
2020
;
5
(
7
):
e371
17
Fry-Bowers
EK
.
Children are at risk from COVID-19
.
J Pediatr Nurs
.
2020
;
53
:
A10
A12
18
Cappa
C
,
Jijon
I
.
COVID-19 and violence against children: a review of early studies
.
Child Abuse Negl
.
2021
;
116
(
Pt 2
):
105053
19
Marmor
A
,
Cohen
N
,
Katz
C
.
Child maltreatment during COVID-19: key conclusions and future directions based on a systematic literature review [published online ahead of print September 7, 2021]
.
Trauma Violence Abuse
.
doi: 10.1177/15248380211043818
20
Rapp
A
,
Fall
G
,
Radomsky
AC
,
Santarossa
S
.
Child maltreatment during the COVID-19 pandemic: a systematic rapid review
.
Pediatr Clin North Am
.
2021
;
68
(
5
):
991
1009
21
Sege
R
,
Stephens
A
.
Child physical abuse did not increase during the pandemic
.
JAMA Pediatr
.
2022
;
176
(
4
):
338
340
22
Sidpra
J
,
Abomeli
D
,
Hameed
B
,
Baker
J
,
Mankad
K
.
Rise in the incidence of abusive head trauma during the COVID-19 pandemic
.
Arch Dis Child
.
2021
;
106
(
3
):
e14
23
Kovler
ML
,
Ziegfeld
S
,
Ryan
LM
, et al
.
Increased proportion of physical child abuse injuries at a level I pediatric trauma center during the COVID-19 pandemic
.
Child Abuse Negl
.
2021
;
116
(
Pt 2
):
104756
24
Sharma
S
,
Wong
D
,
Schomberg
J
, et al
.
COVID-19: differences in sentinel injury and child abuse reporting during a pandemic
.
Child Abuse Negl
.
2021
;
116
(
Pt 2
):
104990
25
Salt
E
,
Wiggins
AT
,
Cooper
GL
, et al
.
A comparison of child abuse and neglect encounters before and after school closings due to SARS-Cov-2
.
Child Abuse Negl
.
2021
;
118
:
105132
26
Bullinger
LR
,
Boy
A
,
Messner
S
,
Self-Brown
S
.
Pediatric emergency department visits due to child abuse and neglect following COVID-19 public health emergency declaration in the Southeastern United States
.
BMC Pediatr
.
2021
;
21
(
1
):
401
27
Kaiser
SV
,
Kornblith
AE
,
Richardson
T
, et al
.
Emergency visits and hospitalizations for child abuse during the COVID-19 pandemic
.
Pediatrics
.
2021
;
147
(
4
):
e2020038489
28
Maassel
NL
,
Asnes
AG
,
Leventhal
JM
,
Solomon
DG
.
Hospital admissions for abusive head trauma at children’s hospitals during COVID-19
.
Pediatrics
.
2021
;
148
(
1
):
e2021050361
29
Swedo
E
,
Idaikkadar
N
,
Leemis
R
, et al
.
Trends in U.S. emergency department visits related to suspected or confirmed child abuse and neglect among children and adolescents aged <18 years before and during the COVID-19 pandemic - United States, January 2019-September 2020
.
MMWR Morb Mortal Wkly Rep
.
2020
;
69
(
49
):
1841
1847
30
Rapoport
E
,
Reisert
H
,
Schoeman
E
,
Adesman
A
.
Reporting of child maltreatment during the SARS-CoV-2 pandemic in New York City from March to May 2020
.
Child Abuse Negl
.
2021
;
116
(
Pt 2
):
104719
31
Barboza
GE
,
Schiamberg
LB
,
Pachl
L
.
A spatiotemporal analysis of the impact of COVID-19 on child abuse and neglect in the city of Los Angeles, California
.
Child Abuse Negl
.
2021
;
116
(
Pt 2
):
104740
32
Nguyen
LH
.
Calculating the impact of COVID-19 pandemic on child abuse and neglect in the U.S
.
Child Abuse Negl
.
2021
;
118
:
105136
33
Brown
SM
,
Orsi
R
,
Chen
PCB
,
Everson
CL
,
Fluke
J
.
The impact of the COVID-19 pandemic on child protection system referrals and responses in Colorado, USA
.
Child Maltreat
.
2021
;
27
(
1
):
3
11
34
Deakyne Davies
SJ
,
Grundmeier
RW
,
Campos
DA
, et al;
Pediatric Emergency Care Applied Research Network
.
The pediatric emergency care applied research network registry: a multicenter electronic health record registry of pediatric emergency care
.
Appl Clin Inform
.
2018
;
9
(
2
):
366
376
35
Lindberg
DM
,
Beaty
B
,
Juarez-Colunga
E
,
Wood
JN
,
Runyan
DK
.
Testing for abuse in children with sentinel injuries
.
Pediatrics
.
2015
;
136
(
5
):
831
838
36
Christian
CW
;
Committee on Child Abuse and Neglect, American Academy of Pediatrics
.
The evaluation of suspected child physical abuse
.
Pediatrics
.
2015
;
135
(
5
):
e1337
e1354
37
Puls
HT
,
Anderst
JD
,
Davidson
A
,
Hall
M
.
Trends in the use of administrative codes for physical abuse hospitalizations
.
JAMA Pediatr
.
2020
;
174
(
1
):
91
93
38
Hooft
AM
,
Asnes
AG
,
Livingston
N
, et al
.
The accuracy of ICD codes: identifying physical abuse in 4 children’s hospitals
.
Acad Pediatr
.
2015
;
15
(
4
):
444
450
39
Stavas
N
,
Paine
C
,
Song
L
,
Shults
J
,
Wood
J
.
Impact of child abuse clinical pathways on skeletal survey performance in high-risk infants
.
Acad Pediatr
.
2020
;
20
(
1
):
39
45
40
Rossen
LM
,
Branum
AM
,
Ahmad
FB
,
Sutton
P
,
Anderson
RN
.
Excess deaths associated with COVID-19, by age and race and ethnicity—United States, January 26–October 3, 2020
.
MMWR Morb Mortal Wkly Rep
.
2020
;
69
(
42
):
1522
1527
41
Chaiyachati
BH
,
Agawu
A
,
Zorc
JJ
,
Balamuth
F
.
Trends in pediatric emergency department utilization after institution of coronavirus disease-19 mandatory social distancing
.
J Pediatr
.
2020
;
226
:
274
277.e1
42
Lane
WG
,
Rubin
DM
,
Monteith
R
,
Christian
CW
.
Racial differences in the evaluation of pediatric fractures for physical abuse
.
JAMA
.
2002
;
288
(
13
):
1603
1609
43
Jenny
C
,
Hymel
KP
,
Ritzen
A
,
Reinert
SE
,
Hay
TC
.
Analysis of missed cases of abusive head trauma
.
JAMA
.
1999
;
281
(
7
):
621
626
44
Gilboy
N
,
Tanabe
P
,
Travers
D
,
Rosenau
AM
.
Emergency Severity Index (ESI): A Triage Tool for Emergency Department Care, Version 4. Implementation Handbook 2012 Edition
.
Rockville, MD
:
Agency for Healthcare Research and Quality
.
2011
45
Baker
SP
,
O’Neill
B
,
Haddon
W
Jr
,
Long
WB
.
The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care
.
J Trauma
.
1974
;
14
(
3
):
187
196
46
Glerum
KM
,
Zonfrillo
MR
.
Validation of an ICD-9-CM and ICD-10-CM map to AIS 2005 Update 2008
.
Inj Prev
.
2019
;
25
(
2
):
90
92
47
Association for the Advancement of Automotive Medicine (AAAM)
.
The Abbreviated Injury Scale (AIS) 2005 - Update 2008
.
Barrington, IL
:
AAAM
;
2008
48
Zonfrillo
MR
,
Macy
ML
,
Cook
LJ
, et al;
Pediatric Emergency Care Applied Research Network (PECARN)
.
Anticipated resource utilization for injury versus non-injury pediatric visits to emergency departments
.
Inj Epidemiol
.
2016
;
3
(
1
):
12
49
Puls
HT
,
Hall
M
,
Frazier
T
,
Schultz
K
,
Anderst
JD
.
Association of routine school closures with child maltreatment reporting and substantiation in the United States; 2010-2017
.
Child Abuse Negl
.
2021
;
120
:
105257
50
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
51
Santoli
JM
,
Lindley
MC
,
DeSilva
MB
, et al
.
Effects of the COVID-19 pandemic on routine pediatric vaccine ordering and administration—United States, 2020
.
MMWR Morb Mortal Wkly Rep
.
2020
;
69
(
19
):
591
593
52
Dean
P
,
Zhang
Y
,
Frey
M
, et al
.
The impact of public health interventions on critical illness in the pediatric emergency department during the SARS-CoV-2 pandemic
.
J Am Coll Emerg Physicians Open
.
2020
;
1
(
6
):
1542
1551
53
DeLaroche
AM
,
Rodean
J
,
Aronson
PL
, et al
.
Pediatric emergency department visits at US children’s hospitals during the COVID-19 pandemic
.
Pediatrics
.
2021
;
147
(
4
):
e2020039628
54
Even
L
,
Lipshaw
MJ
,
Wilson
PM
,
Dean
P
,
Kerrey
BT
,
Vukovic
AA
.
Pediatric emergency department volumes and throughput during the COVID-19 pandemic
.
Am J Emerg Med
.
2021
;
46
:
739
741
55
Helton
JJ
,
Carbone
JT
,
Vaughn
MG
,
Cross
TP
.
Emergency department admissions for child sexual abuse in the United States from 2010 to 2016
.
JAMA Pediatr
.
2020
;
174
(
1
):
89
91
56
King
AJ
,
Farst
KJ
,
Jaeger
MW
,
Onukwube
JI
,
Robbins
JM
.
Maltreatment-related emergency department visits among children 0 to 3 years old in the United States
.
Child Maltreat
.
2015
;
20
(
3
):
151
161
57
Rovi
S
,
Johnson
M
.
Physician use of diagnostic codes for child and adult abuse
.
J Am Med Womens Assoc (1972)
.
1999
;
54
(
4
):
211
214

Supplementary data