BACKGROUND AND OBJECTIVES:

International efforts have been focused on identifying children at low risk of clinically important traumatic brain injury in whom computed tomography (CT) neuroimaging can be avoided. We sought to determine if CT use for pediatric head trauma has decreased among US emergency departments (EDs).

METHODS:

This was a cross-sectional analysis of the National Hospital Ambulatory Care Medical Survey database of nationally representative ED visits from 2007 to 2015. We included children <18 years of age evaluated in the ED for head injury. Survey weighting procedures were used to estimate the annual proportion of children who underwent CT neuroimaging and to perform multivariable logistic regression.

RESULTS:

There were an estimated 14.3 million pediatric head trauma visits during the 9-year study period. Overall, 32% (95% confidence interval [CI]: 29%–35%) of children underwent CT neuroimaging with no significant annual linear trend (P trend = .50). Multivariate analysis similarly revealed no difference by year (adjusted odds ratio [aOR]: 1.02; 95% CI: 0.97–1.07) after adjustment for patient- and ED-level covariates. CT use was associated with age ≥2 years (aOR: 1.51; 95% CI: 1.13–2.01), white race (aOR: 1.43; 95% CI: 1.10–1.86), highest triage acuity (aOR: 8.24 [95% CI: 4.00–16.95]; P < .001), and presentation to a nonteaching (aOR: 1.47; 95% CI: 1.05–2.06) or nonpediatric (aOR: 1.53; 95% CI: 1.05–2.23) hospital.

CONCLUSIONS:

CT neuroimaging did not decrease from 2007 to 2015. Findings suggest an important need for quality improvement initiatives to decrease CT use among children with head injuries.

What’s Known on This Subject:

There have been multiple long-standing efforts to reduce computed tomography (CT) imaging rates for children presenting to the emergency department with head injuries. The impact of these interventions is largely unknown.

What This Study Adds:

CT neuroimaging did not decrease in the United States between 2007 and 2015, despite national educational campaigns and clinical-decision rules for identifying children for whom CT can safely be avoided. Quality improvement initiatives are necessary to translate evidence into practice.

Traumatic brain injury (TBI) remains among the leading causes of pediatric morbidity and mortality worldwide. Incidence of TBIs among children and adolescents in the United States increased by 25% from 2006 to 2010.1 Although the majority of head injuries in children do not result in clinically important TBI, children who are at risk for deterioration or need neurosurgical intervention must be identified rapidly in the emergency department (ED) setting. Computed tomography (CT) is the reference standard to provide a rapid and definitive diagnosis of intracranial pathology but must be balanced against the risks of radiation-induced malignancy.2,4 Moreover, CT use is resource-intensive and carries additional risks for children who require sedation for imaging.5,6 In the United States, CT neuroimaging for pediatric head trauma nearly doubled from 1995 to 2003,7 and there exists significant ongoing practice variation.8,10 Identifying children who are at low risk of clinically important TBI for whom CT can be safely avoided has become an international priority and has been the objective of several of the largest multicenter studies ever conducted in pediatric medicine.11,14 

For nearly 2 decades, there have been concerted efforts to limit pediatric CT exposure to “as low as reasonably achievable.”15 Beginning in 2007, the Image Gently Alliance has led an educational campaign to reduce diagnostic radiation exposure among children.16 Reducing inappropriate CT use specifically for pediatric head trauma was identified in 2013 as a Choosing Wisely focus of the American Academy of Pediatrics.17 Importantly, in 2009, the Pediatric Emergency Care Applied Research Network (PECARN) derived high-performing clinical prediction rules for the ED assessment of children with head injuries,13 which have since been externally validated in multiple settings.11,18,20 When implemented, the PECARN rules have been demonstrated to decrease the rate of CT imaging for pediatric head trauma without missing injuries that warrant neurosurgical intervention.21,23 

Using nationally representative data, we aimed to describe ED trends in the use of CT neuroimaging for children in the United States from 2007 to 2015. We hypothesized that there would be a significant decline in CT neuroimaging during the study period, reflecting both a growing national awareness of CT-associated risks and publication of the highly sensitive PECARN rules.

We conducted a repeated cross-sectional analysis of the National Hospital Ambulatory Medical Care Survey (NHAMCS) ED data sets from 2007 to 2015. The NHAMCS is conducted annually by the Centers for Disease Control and Prevention National Center for Health Statistics, and statistics from 2015 were published in the most recent release (release date: November 20, 2017). In the survey, a multistage probability sampling design is used to collect data on ∼30 000 annual visits to some 300 randomly selected US EDs. Each patient visit is the basic sampling unit and is assigned a weight to allow for the generation of nationally representative population-level estimates. Visit information is collected by trained staff members during a randomly assigned 4-week reporting period, monitored for accuracy by NHAMCS field representatives, and processed centrally with manual and computerized verification algorithms. NHAMCS sampling data are collected from within geographically defined areas, hospitals within those areas, EDs within those hospitals, and on patients who have visited those EDs. More information regarding the NHAMCS sampling methodology can be found on the Web site for the Centers for Disease Control and Prevention.24 NHAMCS data sets are publicly available and deidentified and as such, were deemed exempt from review by the Harvard University Institutional Review Board.

The eligible study population included all pediatric patients <18 years of age presenting with a chief complaint or discharge diagnosis of head injury, which were identified by reason for visit and International Classification of Diseases, Ninth Revision, Clinical Modification codes, respectively. Patient visits were identified by reason for visit codes, including injury of head (55050); contusion, abrasion, or bruise of head (54050); and fracture or dislocation of head and face (50050), as well as by using the International Classification of Diseases, Ninth Revision, Clinical Modification codes for skull fracture (800.xx to 804.xx), concussion (850.xx), intracranial hemorrhage (851.xx to 853.xx), other brain injury (854.xx), and head injury, unspecified (959.01). Analysis was restricted to patients for whom an injury was indicated by using the question, “Is this visit related to an injury?” a variable available in the NHAMCS. Visits recorded with a disposition of “dead on arrival” or “left without been seen” were excluded.

The primary outcome was the annual proportion of children with acute head injuries who received a CT scan in the ED. To explore the latency of knowledge translation, secondary multivariable analyses were conducted to evaluate the association between CT use in the period before and after the publication of the PECARN prediction rules. For secondary analyses, binary variables were created to compare neuroimaging for visits from 2007 to 2009 (before the PECARN period [published October 2009]) with visits from 2010 to 2015 (after PECARN period) as well as for additional sensitivity analyses by sequentially omitting the first years after PECARN publication. Beginning in 2007 (for the outcome of interest), NHAMCS data include specific information that identifies whether CT imaging is neuroimaging or another body system. Additional data were collected on covariates that were shown previously to be associated with CT neuroimaging,7,25,26 including patient demographic information (age, sex, race, and insurance provider), visit characteristics (triage acuity level and requirement for admission), and ED characteristics (pediatric and teaching status). Missing data within the NHAMCS were coded as unknown or unavailable. Age was treated as a binary variable for children <2 years old and children 2 to 18 years old, consistent with the PECARN rule dichotomization.13 Race was classified as white, African American, or other as per the NHAMCS recoded race variable. Insurance provider was categorized as private, Medicaid or Medicare, self-pay, or other. Triage acuity was classified as immediate, emergent, urgent, semiurgent, nonurgent, and unknown or unavailable, as designated in the NHAMCS, and modeled as a categorical variable. Consistent with previous work, EDs were classified as pediatric hospitals if ≥85% of all visits were for patients <21 years and as teaching hospitals if ≥25% of all patients were evaluated by a resident physician.7 

All analyses were performed by using Stata v.14.1 (StataCorp, College Station, TX) with survey procedures for weights, stratum, and primary sampling units to account for the multistage sampling design of the NHAMCS and to generate population estimates. The annual population-level CT trend was analyzed by using a Pearson’s χ2 global test for differences among survey-weighted proportions. Multivariable logistic regression was used to test the strength of association of factors associated with CT neuroimaging and to compare CT use before and after the PECARN rules. Missing data were greatest for triage acuity (14.9% of observations), such that sensitivity analyses were performed by complete case analysis with these observations removed as well as with all unavailable triage values recoded as highest acuity (immediate) and recoded as lowest acuity (nonurgent). Population estimates are presented in millions unless otherwise noted, and percentages are expressed as survey-weighted proportions with 95% confidence intervals (CIs). A 2-tailed P value <.05 was considered statistically significant.

During the 9-year study period, there were 269 721 ED visits in the NHAMCS, of which 59 921 were for children <18 years old. There were 3089 observations that met inclusion criteria, of which 35 were excluded for a disposition of “dead on arrival” or “left without being seen.” The final analysis included 3054 unweighted observations, representing an estimated 14.3 million (95% CI: 13.0–15.7 million) pediatric ED visits for head trauma. Nationwide estimates for pediatric head trauma increased from 1.31 million in 2007 to 1.91 million in 2015. The median patient age was 6 years (interquartile range: 2–13 years old); 61.4% of patients were boys (95% CI: 59.0%–63.7%), 1.6% of patients were hospitalized (95% CI: 1.2%–2.2%), and a majority of patients were evaluated in nonteaching (88.2%; 95% CI: 85.2%–90.7%) and nonpediatric hospitals (88.7%; 95% CI: 84.2%–92.0%). Demographics and visit characteristics for the study population are shown in Table 1.

TABLE 1

Demographic Characteristics of the Study Population and Overall CT Use

CharacteristicsChildren (n = 3054 Observations That Meet Inclusion Criteria)
Population Estimate, millionsPercentage of Visits, % (95% CI)
Age group, y   
 <2 2.96 20.6 (18.5–22.8) 
 ≥2–18 11.38 79.4 (77.2–81.5) 
Sex   
 Male 8.80 61.4 (59.1–63.7) 
Race   
 White 10.68 74.6 (71.8–77.2) 
 African American 2.96 20.6 (18.1–23.4) 
 Other 0.69 4.8 (3.7–6.2) 
Type of institution: teaching hospital   
 Teaching 1.69 11.8 (9.4–14.8) 
 Nonteaching 12.63 88.2 (85.2–90.7) 
Type of institution: pediatric hospital   
 Pediatric 1.62 23.4 (16.5–32.2) 
 Nonpediatric 12.71 88.7 (84.2–92.0) 
Patient disposition   
 Admitted 0.23 1.6 (1.2–2.2) 
 Discharged from ED 14.10 98.4 (97.8–98.9) 
Triage acuity level   
 Immediate 0.25 1.7 (1.2–2.4) 
 Emergent 1.09 7.6 (6.3–9.1) 
 Urgent 4.19 29.2 (26.5–32.1) 
 Semiurgent 5.34 37.3 (34.6–39.9) 
 Nonurgent 0.95 6.7 (5.4–8.3) 
 Unknown or unavailable 2.51 17.5 (14.3–21.3) 
Insurance provider   
 Self-pay 0.81 5.7 (4.5–7.1) 
 Private 6.19 43.2 (40.3–46.2) 
 Medicare or Medicaid 6.01 42.0 (38.9–45.1) 
 Other or unknown 1.32 9.2 (7.4–11.5) 
Overall CT use   
 CT head and any nonhead CT 4.58 32.0 (29.4–34.7) 
 CT head only 3.87 29.5 (26.8–32.4) 
CharacteristicsChildren (n = 3054 Observations That Meet Inclusion Criteria)
Population Estimate, millionsPercentage of Visits, % (95% CI)
Age group, y   
 <2 2.96 20.6 (18.5–22.8) 
 ≥2–18 11.38 79.4 (77.2–81.5) 
Sex   
 Male 8.80 61.4 (59.1–63.7) 
Race   
 White 10.68 74.6 (71.8–77.2) 
 African American 2.96 20.6 (18.1–23.4) 
 Other 0.69 4.8 (3.7–6.2) 
Type of institution: teaching hospital   
 Teaching 1.69 11.8 (9.4–14.8) 
 Nonteaching 12.63 88.2 (85.2–90.7) 
Type of institution: pediatric hospital   
 Pediatric 1.62 23.4 (16.5–32.2) 
 Nonpediatric 12.71 88.7 (84.2–92.0) 
Patient disposition   
 Admitted 0.23 1.6 (1.2–2.2) 
 Discharged from ED 14.10 98.4 (97.8–98.9) 
Triage acuity level   
 Immediate 0.25 1.7 (1.2–2.4) 
 Emergent 1.09 7.6 (6.3–9.1) 
 Urgent 4.19 29.2 (26.5–32.1) 
 Semiurgent 5.34 37.3 (34.6–39.9) 
 Nonurgent 0.95 6.7 (5.4–8.3) 
 Unknown or unavailable 2.51 17.5 (14.3–21.3) 
Insurance provider   
 Self-pay 0.81 5.7 (4.5–7.1) 
 Private 6.19 43.2 (40.3–46.2) 
 Medicare or Medicaid 6.01 42.0 (38.9–45.1) 
 Other or unknown 1.32 9.2 (7.4–11.5) 
Overall CT use   
 CT head and any nonhead CT 4.58 32.0 (29.4–34.7) 
 CT head only 3.87 29.5 (26.8–32.4) 

Overall, 32.0% (95% CI: 29.0%–34.6%) of children with head injuries underwent CT neuroimaging. Figure 1 reveals the population-weighted annual trend of CT neuroimaging in the study population by year, which ranged from 26.4% to 36.0%. Over the course of the 9-year study period, there was no significant linear trend in the annual estimates for CT neuroimaging among children with head injuries (P trend = .50). Restricting this analysis to only the lowest acuity categories (semiurgent or nonurgent), CT use was 16.0% in 2007 and 26.1% in 2015 (P trend = .69). Approximately 84.6% of children with head injuries who received CT imaging underwent isolated neuroimaging without CT of any other body region. Excluding children who received both head and any nonhead CT imaging, overall CT use was 29.5% with no linear trend between 2007 (27.6%; 95% CI: 19.8%–37.1%) and 2015 (30.2%; 95% CI: 26.8%–32.4%) (P trend = .39).

FIGURE 1

CT neuroimaging trend over time with weighted proportion (±95% CI) of children who underwent CT neuroimaging for head injury by year and annual weighted population estimates for all pediatric head injuries that were evaluated in EDs nationwide (table below). The Image Gently Alliance campaign (June 2007), the publication of the PECARN rules (October 2009), and the Choosing Wisely campaign (February 2013) are indicated by solid black vertical lines.

FIGURE 1

CT neuroimaging trend over time with weighted proportion (±95% CI) of children who underwent CT neuroimaging for head injury by year and annual weighted population estimates for all pediatric head injuries that were evaluated in EDs nationwide (table below). The Image Gently Alliance campaign (June 2007), the publication of the PECARN rules (October 2009), and the Choosing Wisely campaign (February 2013) are indicated by solid black vertical lines.

Multivariable analysis results are presented in Table 2. Similar to the linear trend analysis of weighted annual CT use, a multivariate analysis revealed no significant association between CT neuroimaging and year (adjusted odds ratio [aOR]: 1.02; 95% CI: 0.97–1.07; P = .50) after adjustment for patient age, sex, race, insurance provider, pediatric or teaching hospital, and triage acuity. Sensitivity analyses similarly revealed no significant association with year when observations missing acuity data (coded as unknown or unavailable in NHAMCS) were excluded (aOR: 1.02; 95% CI: 0.96–1.08; P = .53), or when all these missing values were recoded as the highest (immediate) acuity level (aOR: 1.01; 95% CI: 0.96–1.06; P = .78) or as the lowest (nonurgent) acuity level (aOR: 1.02; 95% CI: 0.97–1.08; P = .40).

TABLE 2

Predictors of CT Use

VariableaOR (95% CI)P
Year 1.02 (0.97–1.07) .50 
Age group, y   
 ≥2–18 vs <2 1.51 (1.13–2.01) .005 
Sex   
 Male versus female 1.04 (0.85–1.28) .71 
Race   
 White versus African American 1.43 (1.10–1.86) .008 
 Other versus African American 1.06 (0.60–1.87) .83 
Type of institution   
 Nonteaching versus teaching 1.47 (1.05–2.06) .02 
 Nonpediatric versus pediatric 1.53 (1.05–2.23) .03 
Triage acuity level   
 Immediate versus nonurgent 8.24 (4.00–16.95) <.001 
 Emergent versus nonurgent 6.97 (3.67–13.24) <.001 
 Urgent versus nonurgent 2.99 (1.71–5.25) <.001 
 Semiurgent versus nonurgent 1.39 (0.82–2.34) .22 
 Unknown or unavailable versus nonurgent 1.70 (0.94–3.07) .08 
Insurance provider   
 Private insurance versus self-pay 0.90 (0.48–1.70) .74 
 Medicaid or Medicare versus self-pay 0.84 (0.47–1.50) .55 
 Other or unknown versus self-pay 0.97 (0.49–1.92) .94 
VariableaOR (95% CI)P
Year 1.02 (0.97–1.07) .50 
Age group, y   
 ≥2–18 vs <2 1.51 (1.13–2.01) .005 
Sex   
 Male versus female 1.04 (0.85–1.28) .71 
Race   
 White versus African American 1.43 (1.10–1.86) .008 
 Other versus African American 1.06 (0.60–1.87) .83 
Type of institution   
 Nonteaching versus teaching 1.47 (1.05–2.06) .02 
 Nonpediatric versus pediatric 1.53 (1.05–2.23) .03 
Triage acuity level   
 Immediate versus nonurgent 8.24 (4.00–16.95) <.001 
 Emergent versus nonurgent 6.97 (3.67–13.24) <.001 
 Urgent versus nonurgent 2.99 (1.71–5.25) <.001 
 Semiurgent versus nonurgent 1.39 (0.82–2.34) .22 
 Unknown or unavailable versus nonurgent 1.70 (0.94–3.07) .08 
Insurance provider   
 Private insurance versus self-pay 0.90 (0.48–1.70) .74 
 Medicaid or Medicare versus self-pay 0.84 (0.47–1.50) .55 
 Other or unknown versus self-pay 0.97 (0.49–1.92) .94 

Several factors were found to be significantly associated with increased CT neuroimaging (Table 2), including age ≥2 years, white race, acuity categories urgent or higher, and presentation to a nonteaching or nonpediatric hospital.

The unadjusted proportion of children with head injuries who underwent CT neuroimaging did not differ when comparing the periods before (2007–2009; 33.2%) and after the PECARN rules (2010–2015; 31.4%; P = .49). Similarly, there was no difference when adjusted for potential confounding in a multivariate analysis (aOR: 1.07 after PECARN versus before; 95% CI: 0.84–1.38; P = .59). To allow for a possible transitional wash-in period, sensitivity analyses were performed by sequentially omitting the first years after the PECARN publication, and each also revealed no change in CT neuroimaging in the 6-year period after the PECARN rules (Table 3).

TABLE 3

CT Use Before and After PECARN Rules, With Years Sequentially Omitted to Analyze for Possible Wash-In Effect

Comparison YearaORa (95% CI)P
After PECARN (2010–2015) versus before PECARN (2007–2009) 1.07 (0.84–1.38) .59 
After PECARN (2011–2015) versus before PECARN (2007–2009) 1.09 (0.83–1.42) .54 
After PECARN (2012–2015) versus before PECARN (2007–2009) 1.03 (0.76–1.39) .87 
After PECARN (2013–2015) versus before PECARN (2007–2009) 1.04 (0.73–1.41) .91 
Comparison YearaORa (95% CI)P
After PECARN (2010–2015) versus before PECARN (2007–2009) 1.07 (0.84–1.38) .59 
After PECARN (2011–2015) versus before PECARN (2007–2009) 1.09 (0.83–1.42) .54 
After PECARN (2012–2015) versus before PECARN (2007–2009) 1.03 (0.76–1.39) .87 
After PECARN (2013–2015) versus before PECARN (2007–2009) 1.04 (0.73–1.41) .91 
a

Adjusted for patient age, sex, race, insurance provider, presentation at a pediatric or teaching hospital, and triage acuity.

Using a large, nationally representative database of US ED visits, we found no change in CT neuroimaging among children with head injuries from 2007 to 2015. CT use remained high (32% overall) throughout the study period, and there was no decrease in linear trend over time or in multivariable analyses after adjustment for potential confounders. Moreover, CT use did not decrease among children who were receiving only isolated neuroimaging nor among low acuity triage categories of those least likely to meet the PECARN high-risk criteria. The finding of no decrease in CT neuroimaging during the 9-year study period, and particularly after the publication of the PECARN rules in 2009, was counter to the a priori hypothesis of this study.

Rates of CT neuroimaging presented here are similar to other investigations. A study of 25 US tertiary pediatric EDs from 2004 to 2006 and another of 40 US tertiary pediatric EDs from 2005 to 2009 both revealed mean rates of 35% for children with head injuries who underwent CT neuroimaging.8,27 Both studies were limited to children’s hospitals rather than nationally representative data. In an analysis of the NHAMCS from 1995 to 2003, researchers reported a peak rate of 29% of children with head injuries who underwent CT in 2000.7 A more recent NHAMCS study from 2002 to 2006 revealed 39% CT use among pediatric visits for head injury in the pooled 5-year sample.26 Of note, previous studies in which the NHAMCS database was queried predated 2007 data capture changes that specify the CT type into head versus nonhead scans and precluded any definitive knowledge of the body region that underwent CT imaging. In a study of 324 435 pediatric head trauma visits to 848 general EDs, researchers used the Nationwide ED Sample to find that CT neuroimaging ranged from 53.7% to 55.2% between 2006 and 2010.9 The elevated use of CT found in that study may be because the authors did not apply sampling weights and excluded pediatric EDs in the analysis. Importantly, the majority of estimates for CT use in children with head injuries have been from children’s hospitals, and no national estimates have been reported beyond 2010.

Excess CT use contributes to rising health care costs, exposes many children to the harmful effects of ionizing radiation and for some, the additional risks of sedation required for imaging. With a long-standing recognition of the lifetime fatal malignancy risk that is associated with CT imaging, considerable efforts have been made, championing the “as low as reasonably achievable” principle and a reduction of unnecessary CT scans.15 Beginning in 2007, the Image Gently Alliance national educational campaign has been raising awareness among health care providers and the public regarding the radiation-associated risks of diagnostic imaging.28,30 Lodwick et al31 found that the overall use of CT imaging decreased from 2009 to 2013 at 30 tertiary pediatric hospitals. Use of CT neuroimaging declined an average of 6.7% per year; however, this was for all CT head indications, and even among these tertiary pediatric centers, there was an approximate fourfold range in scanning between the hospitals with the lowest and highest rates.31 So, although there is some evidence of more conservative use of CT imaging, the current study suggests that this may be predominantly among pediatric centers and may not be for children with head injuries per se. Reducing unnecessary CT neuroimaging specifically among children with head injuries has been a Choosing Wisely priority of the American Academy of Pediatrics since 2013.17 

The PECARN decision rules identify children for whom CT can be avoided with a high sensitivity and negative predictive value.11,13 No broad assessment of CT use has been undertaken since the derivation of these rules in 2009, and we found that the use of CT neuroimaging did not decrease in the 6-year period after the publication of the PECARN rules. This steady elevated use of CT neuroimaging reveals the well-established challenge of translating high quality evidence into practice.32 Knowledge translation of health research has been reported to take an estimated average of 17 years to enter day-to-day clinical practice,33,34 although there is no consensus on how to precisely measure these translational delays nor how they can be reduced.33 A 2017 survey of ED physicians revealed that despite familiarity of Choosing Wisely recommendations, over half of respondents reported that they sometimes, often, or always perform CT for patients with head injuries who are at low risk per decision rules.35 Barriers to reducing CT use for minor head injury in the ED have been qualitatively explored. Melnick et al36 described factors that promote or hinder appropriate use of CT within 5 core domains: the need to establish trust, patient and provider anxiety, ED-related practice constraints, the influence of others, and patient expectations. The authors concluded that systems to establish trust and manage uncertainty could optimize CT use in the ED.36 

Several reports have revealed successful implementation of the PECARN rules, resulting in lower rates of CT imaging for pediatric head trauma without missing neurosurgical TBIs.21,23 The implementation of the PECARN rules at an urban tertiary pediatric ED reduced CT scanning from 21% to 15%, with an additional reduction to 9% from individual practitioner performance feedback. There were no increases in ED length of stay, 72-hour return visits, or missed significant TBIs.21 Similarly, a hospital-sponsored quality improvement project incorporated the maintenance of certification credits and participant coaching to reduce the CT rate from 29% to 17% in a community ED.22 A multifaceted intervention of 5 pediatric EDs and 8 general EDs that was centered on real-time, computerized PECARN clinical-decision support was associated with decreased CT use among all children with minor blunt head trauma without increasing the rate of missed injuries.23 Findings from the latter study suggest achievable benchmarks of <15% CT use for all children with minor head trauma and <5% for children who are at low risk per the PECARN rules.23 An important remaining challenge will be scaling these successes to a national level, particularly given the epidemic of pediatric head injuries.1 

In our study, we identify several factors that are associated with an increased use of CT neuroimaging, including age, higher triage acuity, and presentation to nonteaching or nonpediatric hospitals. Each of these variables have been previously shown to be associated with increased CT use.7,9,26 Moreover, white race was significantly associated with increased odds of CT neuroimaging, adding to a growing body of literature that suggests racial disparities in the care of children with acute head injuries.26,37 Identifying patient and provider groups that are most likely to benefit from targeted quality initiatives to reduce CT overuse remains an important area of future research.

There are several potential limitations to the current study. The NHAMCS provides high-level, nationally representative data but does not contain important clinical information, such as the severity of the head injury or the Glasgow coma score. Therefore, the true appropriateness of CT use cannot be assessed. We have attempted to control for injury severity using triage acuity in all models. In the NHAMCS, the unit of analysis was the ED visit; we are unable to account for repeat visits by individual patients. Similarly, no patient or provider identifiers are released in the NHAMCS data set, which precludes longitudinal analysis of individual patients or institutions. As such, we are unable to identify hospital-level variation or performance at specific centers. Also, our study is dependent on coding accuracy within the NHAMCS, and we cannot exclude the possibility of misclassification. However, NHAMCS data are processed at a central facility and reviewed manually for accuracy, and the diagnostic codes that are used are those endorsed by the Centers of Disease Control and Prevention for head trauma case inclusion.38 Misclassification is also possible in the ascertainment of hospital pediatric and teaching status, although we have used definitions consistent with those that have been described previously.7 

The use of CT neuroimaging for children with acute head injuries did not decrease over the 9-year study period, which also spanned the publication of the PECARN clinical-decision rules. Results from this large nationally representative study suggest a need for targeted quality improvement initiatives to ensure appropriate CT use in this patient population. There remains an important need for interventions to translate clinical-decision rules into practice.

     
  • aOR

    adjusted odds ratio

  •  
  • CI

    confidence interval

  •  
  • CT

    computed tomography

  •  
  • ED

    emergency department

  •  
  • NHAMCS

    National Hospital Ambulatory Medical Care Survey

  •  
  • PECARN

    Pediatric Emergency Care Applied Research Network

  •  
  • TBI

    traumatic brain injury

Dr Burstein conceptualized and designed the study, contributed to all data collection and analyses, drafted the initial manuscript, and reviewed and revised the manuscript; Drs Upton and Terra contributed to all data collection and analyses and reviewed and revised the manuscript; Dr Neuman contributed to data analyses and reviewed and revised the manuscript; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: No external funding.

COMPANION PAPER: A companion to this article can be found online at www.pediatrics.org/cgi/doi/10.1542/peds.2018-2137.

We thank Geetha Iyer (Harvard T.H. Chan School of Public Health) and Raphael Freitas (McGill University Health Centre) for technical assistance.

1
Marin
JR
,
Weaver
MD
,
Yealy
DM
,
Mannix
RC
.
Trends in visits for traumatic brain injury to emergency departments in the United States.
JAMA
.
2014
;
311
(
18
):
1917
1919
[PubMed]
2
Brenner
DJ
,
Hall
EJ
.
Computed tomography–an increasing source of radiation exposure.
N Engl J Med
.
2007
;
357
(
22
):
2277
2284
[PubMed]
3
Pearce
MS
,
Salotti
JA
,
Little
MP
, et al
.
Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study.
Lancet
.
2012
;
380
(
9840
):
499
505
[PubMed]
4
Miglioretti
DL
,
Johnson
E
,
Williams
A
, et al
.
The use of computed tomography in pediatrics and the associated radiation exposure and estimated cancer risk.
JAMA Pediatr
.
2013
;
167
(
8
):
700
707
[PubMed]
5
Goldwasser
T
,
Bressan
S
,
Oakley
E
,
Arpone
M
,
Babl
FE
.
Use of sedation in children receiving computed tomography after head injuries.
Eur J Emerg Med
.
2015
;
22
(
6
):
413
418
[PubMed]
6
Hoyle
JD
 Jr
,
Callahan
JM
,
Badawy
M
, et al;
Traumatic Brain Injury Study Group for the Pediatric Emergency Care Applied Research Network
.
Pharmacological sedation for cranial computed tomography in children after minor blunt head trauma.
Pediatr Emerg Care
.
2014
;
30
(
1
):
1
7
[PubMed]
7
Blackwell
CD
,
Gorelick
M
,
Holmes
JF
,
Bandyopadhyay
S
,
Kuppermann
N
.
Pediatric head trauma: changes in use of computed tomography in emergency departments in the United States over time.
Ann Emerg Med
.
2007
;
49
(
3
):
320
324
[PubMed]
8
Stanley
RM
,
Hoyle
JD
 Jr
,
Dayan
PS
, et al;
Pediatric Emergency Care Applied Research Network
.
Emergency department practice variation in computed tomography use for children with minor blunt head trauma.
J Pediatr
.
2014
;
165
(
6
):
1201
1206.e2
9
Marin
JR
,
Weaver
MD
,
Barnato
AE
,
Yabes
JG
,
Yealy
DM
,
Roberts
MS
.
Variation in emergency department head computed tomography use for pediatric head trauma.
Acad Emerg Med
.
2014
;
21
(
9
):
987
995
[PubMed]
10
Miescier
MJ
,
Dudley
NC
,
Kadish
HA
,
Mundorff
MB
,
Corneli
HM
.
Variation in computed tomography use for evaluation of head injury in a pediatric emergency department.
Pediatr Emerg Care
.
2017
;
33
(
3
):
156
160
[PubMed]
11
Babl
FE
,
Borland
ML
,
Phillips
N
, et al;
Paediatric Research in Emergency Departments International Collaborative
.
Accuracy of PECARN, CATCH, and CHALICE head injury decision rules in children: a prospective cohort study.
Lancet
.
2017
;
389
(
10087
):
2393
2402
[PubMed]
12
Dunning
J
,
Daly
JP
,
Lomas
JP
,
Lecky
F
,
Batchelor
J
,
Mackway-Jones
K
;
Children’s Head Injury Algorithm for the Prediction of Important Clinical Events Study Group
.
Derivation of the children’s head injury algorithm for the prediction of important clinical events decision rule for head injury in children.
Arch Dis Child
.
2006
;
91
(
11
):
885
891
[PubMed]
13
Kuppermann
N
,
Holmes
JF
,
Dayan
PS
, et al;
Pediatric Emergency Care Applied Research Network
.
Identification of children at very low risk of clinically-important brain injuries after head trauma: a prospective cohort study.
Lancet
.
2009
;
374
(
9696
):
1160
1170
[PubMed]
14
Osmond
MH
,
Klassen
TP
,
Wells
GA
, et al;
Pediatric Emergency Research Canada Head Injury Study Group
.
CATCH: a clinical decision rule for the use of computed tomography in children with minor head injury.
CMAJ
.
2010
;
182
(
4
):
341
348
[PubMed]
15
The ALARA (as low as reasonably achievable) concept in pediatric CT intelligent dose reduction. Multidisciplinary conference organized by the Society of Pediatric Radiology. August 18-19, 2001.
Pediatr Radiol
.
2002
;
32
(
4
):
217
313
[PubMed]
16
Image Gently Alliance
. Campaign overview. Available at: www.imagegently.org/About-Us/Campaign-Overview. Accessed February 15, 2018
17
Bender
JM
,
Taylor
CS
,
Cumpio
J
, et al
.
Infants 1-90 days old hospitalized with human rhinovirus infection.
J Clin Lab Anal
.
2014
;
28
(
5
):
349
352
[PubMed]
18
Schonfeld
D
,
Bressan
S
,
Da Dalt
L
,
Henien
MN
,
Winnett
JA
,
Nigrovic
LE
.
Pediatric Emergency Care Applied Research Network head injury clinical prediction rules are reliable in practice.
Arch Dis Child
.
2014
;
99
(
5
):
427
431
[PubMed]
19
Lorton
F
,
Poullaouec
C
,
Legallais
E
, et al
.
Validation of the PECARN clinical decision rule for children with minor head trauma: a French multicenter prospective study.
Scand J Trauma Resusc Emerg Med
.
2016
;
24
:
98
[PubMed]
20
Ide
K
,
Uematsu
S
,
Tetsuhara
K
,
Yoshimura
S
,
Kato
T
,
Kobayashi
T
.
External validation of the PECARN head trauma prediction rules in Japan.
Acad Emerg Med
.
2017
;
24
(
3
):
308
314
[PubMed]
21
Nigrovic
LE
,
Stack
AM
,
Mannix
RC
, et al
.
Quality improvement effort to reduce cranial CTs for children with minor blunt head trauma.
Pediatrics
.
2015
;
136
(
1
). Available at: www.pediatrics.org/cgi/content/full/136/1/e227
[PubMed]
22
Jennings
RM
,
Burtner
JJ
,
Pellicer
JF
, et al
.
Reducing head CT use for children with head injuries in a community emergency department.
Pediatrics
.
2017
;
139
(
4
):
e20161349
[PubMed]
23
Dayan
PS
,
Ballard
DW
,
Tham
E
, et al;
Pediatric Emergency Care Applied Research Network
;
Clinical Research on Emergency Services and Treatment Network
;
Partners Healthcare
;
Traumatic Brain Injury-Knowledge Translation Study Group
.
Use of traumatic brain injury prediction rules with clinical decision support.
Pediatrics
.
2017
;
139
(
4
):
e20162709
[PubMed]
24
Larson
DB
,
Johnson
LW
,
Schnell
BM
,
Goske
MJ
,
Salisbury
SR
,
Forman
HP
.
Rising use of CT in child visits to the emergency department in the United States, 1995-2008.
Radiology
.
2011
;
259
(
3
):
793
801
[PubMed]
25
Fortin
EM
,
Fisher
J
,
Qiu
S
,
Babcock
CI
.
Privately insured medical patients are more likely to have a head CT.
Emerg Radiol
.
2016
;
23
(
6
):
597
601
[PubMed]
26
Mannix
R
,
Bourgeois
FT
,
Schutzman
SA
,
Bernstein
A
,
Lee
LK
.
Neuroimaging for pediatric head trauma: do patient and hospital characteristics influence who gets imaged?
Acad Emerg Med
.
2010
;
17
(
7
):
694
700
[PubMed]
27
Mannix
R
,
Meehan
WP
,
Monuteaux
MC
,
Bachur
RG
.
Computed tomography for minor head injury: variation and trends in major United States pediatric emergency departments.
J Pediatr
.
2012
;
160
(
1
):
136
139.e1
28
Goske
MJ
,
Applegate
KE
,
Boylan
J
, et al;
Alliance for Radiation Safety in Pediatric Imaging
.
Image Gently(SM): a national education and communication campaign in radiology using the science of social marketing.
J Am Coll Radiol
.
2008
;
5
(
12
):
1200
1205
[PubMed]
29
Goske
MJ
,
Applegate
KE
,
Boylan
J
, et al
.
The Image Gently campaign: working together to change practice.
AJR Am J Roentgenol
.
2008
;
190
(
2
):
273
274
[PubMed]
30
Bulas
D
,
Goske
M
,
Applegate
K
,
Wood
B
.
Image Gently: improving health literacy for parents about CT scans for children.
Pediatr Radiol
.
2009
;
39
(
2
):
112
116
[PubMed]
31
Lodwick
DL
,
Cooper
JN
,
Kelleher
KJ
,
Brilli
R
,
Minneci
PC
,
Deans
KJ
.
Variation in utilization of computed tomography imaging at tertiary pediatric hospitals.
Pediatrics
.
2015
;
136
(
5
). Available at: www.pediatrics.org/cgi/content/full/136/5/e1212
[PubMed]
32
Green
LW
,
Ottoson
JM
,
García
C
,
Hiatt
RA
,
Roditis
ML
.
Diffusion theory and knowledge dissemination, utilization and integration.
Front Public Health Serv Syst Res
.
2014
;
3
(
1
):
3
[PubMed]
33
Morris
ZS
,
Wooding
S
,
Grant
J
.
The answer is 17 years, what is the question: understanding time lags in translational research.
J R Soc Med
.
2011
;
104
(
12
):
510
520
[PubMed]
34
Westfall
JM
,
Mold
J
,
Fagnan
L
.
Practice-based research–“Blue Highways” on the NIH roadmap.
JAMA
.
2007
;
297
(
4
):
403
406
[PubMed]
35
Lin
MP
,
Nguyen
T
,
Probst
MA
,
Richardson
LD
,
Schuur
JD
.
Emergency physician knowledge, attitudes, and behavior regarding ACEP’s choosing wisely recommendations: a survey study.
Acad Emerg Med
.
2017
;
24
(
6
):
668
675
[PubMed]
36
Melnick
ER
,
Shafer
K
,
Rodulfo
N
, et al
.
Understanding overuse of computed tomography for minor head injury in the emergency department: a triangulated qualitative study.
Acad Emerg Med
.
2015
;
22
(
12
):
1474
1483
[PubMed]
37
Natale
JE
,
Joseph
JG
,
Rogers
AJ
, et al;
Pediatric Emergency Care Applied Research Network
.
Cranial computed tomography use among children with minor blunt head trauma: association with race/ethnicity.
Arch Pediatr Adolesc Med
.
2012
;
166
(
8
):
732
737
[PubMed]
38
Marr
AL
,
Coronado
VG
.
Central Nervous System Injury Surveillance Data Submission Standards—2002
.
Atlanta, GA
:
Centers for Disease Control and Prevention, National Center for Injury Prevention and Control
;
2004
. Available at: http://www.dshs.state.tx.us/injury/registry/coronadoandmarrcnsdefinitions.doc. Accessed July 20, 2018

Competing Interests

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

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