Multisite medical record review of emergency department visits for unspecified injury of head following the ICD-10-CM coding transition.

INTRODUCTION: In 2016, a proposed International Classification of Diseases, Tenth Edition, Clinical Modification surveillance definition for traumatic brain injury (TBI) morbidity was introduced that excluded the unspecified injury of head (S09.90) diagnosis code. This study assessed emergency department (ED) medical records containing S09.90 for evidence of TBI based on medical documentation. METHODS: State health department representatives in Maryland, Kentucky, Colorado and Massachusetts reviewed a target of 385 randomly sampled ED records uniquely assigned the S09.90 diagnosis code (without proposed TBI codes), which were initial medical encounters among state residents discharged home during October 2015-December 2018. Using standardised abstraction procedures, reviewers recorded signs and symptoms of TBI, and head imaging results. A tiered case confirmation strategy was applied that assigned a level of certainty (high, medium, low, none) to each record based on the number and type of symptoms and imaging results present in the record. Positive predictive value (PPV) of S09.90 by level of TBI certainty was calculated by state. RESULTS: Wide variation in PPV of sampled ED records assigned S09.90: 36%-52% had medium or high evidence of TBI, while 48%-64% contained low or no evidence of a TBI. Loss of consciousness was mentioned in 8%-24% of sampled medical records. DISCUSSION: Exclusion of the S09.90 code in surveillance estimates may result in many missed TBI cases; inclusion may result in counting many false positives. Further, missed TBI cases influenced by incidence estimates, based on the TBI surveillance definition, may lead to inadequate allocation of public health resources.

Associations between adverse childhood experiences and acquired brain injury, including traumatic brain injuries, among adults: 2014 BRFSS North Carolina.

Adverse childhood experiences (ACEs) can negatively affect lifelong health and opportunity. Acquired brain injury (ABI), which includes traumatic brain injury (TBI) as well as other causes of brain injury, is a health condition that affects millions annually. The present study uses data from the 2014 North Carolina Behavioral Risk Factor Surveillance System to examine the relationship between ACEs and ABI. The study sample included 3454 participants who completed questions on both ABI and ACEs. Multivariable logistic regression models were used to determine the relationship between ACEs and ABI as well as ACEs and TBI. Sexual abuse, emotional abuse, physical abuse, household mental illness and household substance abuse were significantly associated with ABI after adjusting for age, race/ethnicity, gender and employment. Compared with those reporting no ACEs, individuals reporting three ACEs had 2.55 times the odds of having experienced an ABI; individuals reporting four or more ACEs had 3.51 times the odds of having experienced an ABI. Examining TBI separately, those who experienced sexual abuse, physical abuse, household mental illness and had incarcerated household members in childhood had greater odds of reported TBI, after adjusting for age, race/ethnicity, gender and income. Respondents reporting three ACEs (AOR=4.16, 95% CI (1.47 to 11.76)) and four or more ACEs (AOR=3.39, 95% CI (1.45 to 7.90)) had significantly greater odds of reporting TBI than respondents with zero ACEs. Prevention of early adversity may reduce the incidence of ABI; however, additional research is required to elucidate the potential pathways from ACEs to ABI, and vice versa.

Using the public health model to address unintentional injuries and TBI: A perspective from the Centers for Disease Control and Prevention (CDC).

Traumatic brain injury (TBI) can have long term effects on mental and physical health, and can disrupt vocational, educational, and social functioning. TBIs can range from mild to severe and their effects can last many years after the initial injury. CDC seeks to reduce the burden of TBI from unintentional injuries through a focus on primary prevention, improved recognition and management, and intervening to improve health outcomes after TBI. CDC uses a 4-stage public health model to guide TBI prevention, moving from 1) surveillance of TBI, 2) identification of risk and protective factors for TBI, 3) development and testing of evidence-based interventions, to 4) bringing effective intervention to scale through widespread adoption. CDC's unintentional injury prevention activities focus on the prevention of sports-related concussions, motor vehicle crashes, and older adult falls. For concussion prevention, CDC developed Heads Up - an awareness initiative focusing on ways to prevent a concussion in sports, and identifying how to recognize and manage potential concussions. In motor vehicle injury prevention, CDC has developed a tool (MV PICCS) to calculate the expected number of injuries prevented and lives saved using various evidence-based motor vehicle crash prevention strategies. To help prevent TBI related to older adult falls, CDC has developed STEADI, an initiative to help primary care providers identify their patients' falls risk and provide effective interventions. In the future, CDC is focused on advancing our understanding of the public health burden of TBI through improved surveillance in order to produce more comprehensive estimates of the public health burden of TBI.

Racial, ethnic, and sex differences in the associations between violence and self-reported health among US high school students.

BACKGROUND: Involvement in interpersonal violence or suicidal behaviors can have a significant impact on an adolescent's physical health. Similarly, previous research has suggested that lived experiences, more than the presence or absence of physical ailments, can significantly influence self-assessed health status among adolescents. The purpose of this study was to examine the cross-sectional associations between involvement in violence and poor or fair self-reported health among US high school students. METHODS: Data were obtained from the 2005 national Youth Risk Behavior Survey (n = 13,953). Logistic regression analyses were conducted to determine the associations between violence-related measures and self-reported health while controlling for demographic characteristics and potential confounders. Analyses are presented for students overall and stratified by sex and race/ethnicity. RESULTS: Overall, 7.2% of students reported fair or poor self-rated health. Having been in a physical fight, having been injured in a physical fight, having attempted suicide, and having not gone to school because of safety concerns were significantly associated with fair or poor self-rated health after controlling for demographic characteristics and other potential confounders. Differences associated with race/ethnicity and sex are identified. CONCLUSIONS: Four of the 5 violence-related measures included in these analyses were significantly associated with fair or poor self-rated health. Future studies should consider the impact of involvement in violent behaviors and perceptions of both physical and mental well-being.