Pediatric Trauma Care Disparities: Association of Race and Sex With High Acuity Trauma Hospital Admissions

INTRODUCTION

For adult trauma patients, the likelihood of receiving treatment at a hospital properly equipped for trauma care can vary by race and sex. This study examines whether a pediatric patient's race/ethnicity and sex are associated with treatment at a high acuity trauma hospital (HATH).

MATERIALS AND METHODS

Using the 2017 National Inpatient Sample, we identified pediatric trauma patients ( ≤16 y) using International Classification of Diseases-10 codes. Because trauma centers are not defined in National Inpatient Sample, we defined HATHs as hospitals which transferred 0% of pediatric neurotrauma. We used logistic regression to examine associations between race/ethnicity, sex, age, and treatment at a HATH, adjusted for factors including Injury Severity Score, mechanism of injury, and region.

RESULTS

Of 18,085 injured children (median Injury Severity Score 3 [IQR 1-8]), 67% were admitted to a HATH. Compared to White patients, Hispanic (odds ratio [OR] 0.85 [95% confidence interval [CI] 0.79-0.93]) and other race/ethnicity patients (OR 0.85 [95% CI 0.78-0.93]) had a significantly lower odds of treatment at a HATH. Children aged 2-11 (OR 1.36 [95% CI 1.27-1.46]) were more likely to be treated at a HATH compared to adolescents (age 12-16). After adjustment for other factors, sex was not associated with treatment at a HATH.

CONCLUSIONS

Our study demonstrated racial and ethnic disparities in access to HATHs for pediatric trauma patients. Hispanic and other race/ethnicity pediatric trauma patients have lower odds of treatment at HATHs. Further research is needed to study the root causes of these disparities to ensure that all children with injuries receive equitable and high-quality care.

Diagnostic Adjunct Techniques in the Assessment of Hypovolemia: A Prospective Pilot Project

INTRODUCTION

Measuring the hypovolemic resuscitation end point remains a critical care challenge. Our project compared clinical hypovolemia (CH) with three diagnostic adjuncts: 1) noninvasive cardiac output monitoring (NICOM), 2) ultrasound (US) static IVC collapsibility (US-IVC), and 3) US dynamic carotid upstroke velocity (US-C). We hypothesized US measures would correlate more closely to CH than NICOM.

METHODS

Adult trauma/surgical intensive care unit patients were prospectively screened for suspected hypovolemia after acute resuscitation, excluding patients with burns, known heart failure, or severe liver/kidney disease. Adjunct measurements were assessed up to twice a day until clinical improvement. Hypovolemia was defined as: 1) NICOM: ≥10% stroke volume variation with passive leg raise, 2) US-IVC: <2.1 cm and >50% collapsibility (nonventilated) or >18% collapsibility (ventilated), 3) US-C: peak systolic velocity increase 15 cm/s with passive leg raise. Previously unknown cardiac dysfunction seen on US was noted. Observation-level data were analyzed with a Cohen's kappa (κ).

RESULTS

44 patients (62% male, median age 60) yielded 65 measures. Positive agreement with CH was 47% for NICOM, 37% for US-IVC and 10% for US-C. None of the three adjuncts correlated with CH (κ -0.045 to 0.029). After adjusting for previously unknown cardiac dysfunction present in 10 patients, no adjuncts correlated with CH (κ -0.036 to 0.031). No technique correlated with any other (κ -0.118 to 0.083).

CONCLUSIONS

None of the adjunct measurements correlated with CH or each other, highlighting that fluid status assessment remains challenging in critical care. US should assess for right ventricular dysfunction prior to resuscitation.

Provision of Defect-Free Care: Implementation Science in Surgical Patient Safety

Implementation science is the study of the translation of evidence-based practices to real-world clinical environments. Implementation is measured with specific outcomes including acceptability, adoption, appropriateness, feasibility, fidelity, penetration, sustainability, and implementation cost. There are defined frameworks and models that outline implementation strategies and assist researchers in identifying barriers and facilitators to achieve implementation and conduct implementation research using methods such as qualitative analysis, parallel group, pre-/postintervention, interrupted time series, and cluster or stepped-wedge randomized trials. Deimplementation is the study of how to remove ineffective or unnecessary practices from the clinical setting and is an equally important component of implementation science.