A population-based sex-stratified study to understand how health status preceding traumatic brain injury affects direct medical cost

Abstract

Objective To understand how pre-injury health status present five-years preceding traumatic brain injury (TBI) affects direct medical cost two years post-injury. Methods Patients age �19 years in the emergency department (ED) or acute care for a TBI between April 1, 2007 and March 31, 2014 in Ontario, Canada (N = 55,669) were identified from population-based health administrative data. Forty-three factors of pre-injury health status (i.e., comorbidities and personal, social, and environmental factors) that were internally validated for the TBI population were assessed in this study. The outcome of interest was direct medical cost within two years of discharge. Sex-specific multivariable linear regressions were conducted to understand the associations between direct medical cost within two years of discharge and pre-injury health status.

Social determinants of health associated with psychological distress stratified by lifetime traumatic brain injury status and sex: Cross-sectional evidence from a population sample of adults in Ontario, Canada

“…Income, marital status, and age were significant determinants among males only, while education and rural residence were significant among females only. First, this finding complements the growing literature on sex differences as predictors of and influencing factors in health and health outcomes among individuals with TBI [ 10 – 12 , 21 , 22 , 24 – 27 ] and reiterates the importance of integrating sex and gender considerations in TBI research [ 30 – 33 ]. Second, while we stratified the data by sex, the influence of gender cannot be dismissed.…”

“…The stratification of the sample by sex enabled us to account for the interaction of sex with SDoH and to identify SDoH associated with psychological distress specifically among males and females to inform sex-sensitive interventions. This stratification is particularly important because sex and gender differences in mental health [ 21 – 23 ] and in outcomes post-TBI have been reported in both the general population and in specific sub-populations [ 10 – 12 , 22 , 24 – 27 ]. However, we also acknowledge research studies on TBI and mental health that have reported no sex and/or gender differences; for example, in one study, the reporting of mild depression did not differ between men and women at one year post-TBI [ 28 ].…”

“…However, we also acknowledge research studies on TBI and mental health that have reported no sex and/or gender differences; for example, in one study, the reporting of mild depression did not differ between men and women at one year post-TBI [ 28 ]. Similarly, population-based studies that assessed the impact of pre-existing mental health disorders found that among both males and females, a history of mental health disorders significantly reduced functional outcome and increased direct medical cost post-injury [ 11 , 12 ]. Similarly, pre-injury mental health was significantly associated with excess mortality among both male and female patients who experienced a mild or severe TBI [ 29 ].…”

Sex-specific analysis of traumatic brain injury events: applying computational and data visualization techniques to inform prevention and management

“…We used a previously established cohort of patients discharged from acute care (identified in the Discharge Abstract Database, DAD) and from the ED (identified in the National Ambulatory Care Reporting System, NACRS) between fiscal years 2007/2008 and 2015/2016 with a diagnostic code for TBI (ICD-10-CA codes S02.0, S02.1, S02.3, S02.7, S02.8, S02.9, S04.0, S07.1, and S06) [ 8 , 26 , 27 ]; these patients comprised the TBI cohort in the present study. Data on patient demographics and main and secondary diagnoses, conditions, problems, and injury circumstances were collected for each patient.…”

“…Recently, Folweiler and colleagues (2020) proposed a hybrid machine learning technique to identify phenotypes of patients with TBI during the acute injury phase and reported that when patients were grouped by baseline GCS score, no differences were observed in their clinical profiles or outcomes [17], suggesting that the GCS score may not be foolproof for all TBI severities and that other factors within the human ecosystem, the agent and the environment [24], are essential to consider in TBI prevention strategies [17]. This notion is further supported by recent population-based studies which have revealed that multiple chronic disorders, alcohol and prescribed drug toxicity, and exposures to environmental adversities preceding a TBI event have implications for TBI outcomes and cost of publicly funded healthcare, affecting male and female patients differently [8,[25][26][27]. These differences motivated the present study's design, which aimed to utilize the key concepts of host-agent-environment of the Haddon Matrix [21,22] to analyze the data of patients with a diagnosis of TBI through a sex lens in the event phase.…”