Disparities and Variability in Hospital Management of Mild Traumatic Brain Injury

Insurance status significantly influences management decisions:

Uninsured patients are less likely to be admitted, even when clinical factors may justify observation.

Privately insured or Medicare/Medicaid-covered individuals often receive more resource-intensive care, including imaging, neurosurgical consults, and longer admissions.

Non-White, non-Black, non-Hispanic patients may experience:

Lower odds of discharge to home

Longer hospital stays but not necessarily associated with better outcomes

Potential underuse or delayed access to follow-up care (rehabilitation, neuropsychology)

Wide differences exist between hospitals in:

Admission rates for mTBI

Length of stay (LOS) for admitted patients

Discharge disposition (home vs. skilled nursing facility vs. rehab)

Level 1 trauma centers tend to have longer LOS, but paradoxically, their patients are less likely to be discharged home, possibly reflecting:

More cautious or protocol-driven care

Complex patient populations

System inefficiencies or defensive medicine practices

Rural vs. urban hospitals may differ in resource availability:

Rural centers might discharge more patients directly from the ED due to lack of neuroimaging or neurosurgical backup.

Urban or academic centers may admit more patients for observation and follow-up care coordination.

Variability is also driven by a lack of standardization:

Some centers use evidence-based decision rules (e.g., Canadian CT Head Rule), while others rely on individual clinician judgment.

Institutional differences in admission criteria for elderly patients, those on anticoagulants, or those with minor CT findings.

Disparities in mTBI care may lead to:

Under-treatment of vulnerable populations

Over-utilization in low-risk cases due to defensive medicine

Inefficient use of hospital resources

There's a growing need for:

Nationally standardized care pathways

Cultural competence training

Policy reform targeting access and equity

Quality benchmarking across institutions

A scoping review, guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, was used to explore three electronic databases- PubMed, Medline, and CINAHL. Searches identified peer-reviewed empirical literature addressing aspects of the Social determinants of health and HDs related to TBI. A total of 123 records were identified and reduced to 27 studies based on the inclusion criteria. Results revealed that race/ethnicity was the most commonly reported Social determinant of health impacting TBI, followed by an individual's insurance status. Health disparities were noted to occur across the continuum of TBI, including TBI risk, acute hospitalization, rehabilitation, and recovery. The most frequently reported HD was that Whites are more likely to be discharged to inpatient rehabilitation compared to racial/ethnic minorities. Health disparities associated with TBI are most commonly associated with the race/ethnicity SDoH, though insurance status and socioeconomic status commonly influence health inequities as well. The additional need for evidence related to the impact of other, lesser-researched SDoH is discussed, as well as clinical implications that can be used to target intervention for at-risk groups using an individual's known Social determinants of health ¹⁾

A total of 122,406 patients with mTBI were included.

Vattipally et al. performed hierarchical logistic regression to investigate associations of patient-level variables with inpatient admission. Among hospitalized patients, a hierarchical linear regression was constructed for associations with LOS, including hospitals as a random effects term. Based on random effects coefficients, hospitals were classified as high-LOS outliers or non-outliers.

Main measures: Univariable comparisons on facility characteristics were performed. Patients were propensity score matched across hospital outlier status, and a multivariable logistic regression for associations with discharge to home was performed.

Results: The median age was 63 years (interquartile range [IQR], 42-77 years), and 111 306 (91%) patients experienced inpatient admission. Uninsured status was associated with lower odds of inpatient admission (odds ratio [OR], 0.71; 95% confidence interval [CI], 0.65-0.76; P < .001). After excluding very low-volume hospitals, 80,258 admitted patients were treated across 469 hospitals, and 98 were designated as high-LOS outliers. These were more likely to be Level 1 trauma centers (76% vs. 26%; P < .001). After matching, patients treated at high-LOS outlier hospitals were less likely to experience home discharge (OR, 0.89; 95% CI, 0.85-0.93; P < .001). This effect was amplified for patients identifying as non-White, non-Black, non-Hispanic other races (P = .003).

Inpatient admission after mTBI varies by insurance status, with uninsured patients less likely to be admitted. There is significant interhospital variation in LOS, with Level 1 trauma centers more likely to be high-LOS outliers. Despite their longer LOS, patients treated at outlier hospitals experienced lower odds of home discharge ²⁾.

This study provides valuable evidence on disparities and variability in the hospital management of patients with mild traumatic brain injury (mTBI) in the United States. Using a large national dataset and robust statistical methods, the authors demonstrate that factors such as insurance status, hospital type, and patient race/ethnicity significantly influence decisions around hospital admission, length of stay (LOS), and likelihood of discharge to home.

However, the retrospective design and reliance on administrative data limit causal interpretation and prevent adjustment for key clinical variables. The classification of hospitals as LOS outliers should also be interpreted with caution, as longer stays may reflect more comprehensive care or greater patient complexity, rather than inefficiency.

Overall, the study highlights the urgent need for healthcare policies aimed at reducing inequities and standardizing care criteria for mTBI, while still respecting patient-level nuances and hospital contexts. Future research should integrate more detailed clinical data and explore targeted interventions to improve both equity and efficiency in mTBI care.

A secondary analysis of ED visits in the National Hospital Ambulatory Medical Care Survey for the years 1998 through 2000 was performed. Cases of mTBI were identified using ICD-9 codes 800.0, 800.5, 850.9, 801.5, 803.0, 803.5, 804.0, 804.5, 850.0, 850.1, 850.5, 850.9, 854.0, and 959.01. ED care variables related to imaging, procedures, treatments, and disposition were analyzed along racial, ethnic, and gender categories. The relationship between race, ethnicity, and selected ED care variables was analyzed using multivariate logistic regression with control for associated injuries, geographic region, and insurance type.

The incidence of mTBI was highest among men (590/100,000), Native Americans/Alaska Natives (1026.2/100,000), and non-Hispanics (391.1/100,000). After controlling for important confounders, Hispanics were more likely than non-Hispanics to receive a nasogastric tube (OR, 6.36; 95% CI = 1.2 to 33.6); nonwhites were more likely to receive ED care by a resident (OR, 3.09; 95% CI = 1.9 to 5.0) and less likely to be sent back to the referring physician after ED discharge (OR, 0.47; 95% CI = 0.3 to 0.9). Men and women received equivalent ED care.

There are significant racial and ethnic but not gender disparities, in ED care for mTBI. The causes of these disparities and the relationship between these disparities and post-mTBI outcome need to be examined ³⁾.