FUNDING OPPORTUNITY: Secondary analysis of existing databases in traumatic brain injury to explore
outcomes relevant to medical rehabilitation (R21); RFA-HD-16-001
PI: COLANTONIO A
PROJECT SUMMARY: Comorbidity is prevalent after traumatic brain injury (TBI) and across
the spectrum of injury severity. It can be present at the time of injury, arise early after injury, or
during hospitalization or inpatient rehabilitation. Long-term follow-up studies of individuals who
had endured a TBI report that patients have numerous co-existing disorders. Nevertheless, our
comprehension of the when (i.e., pre- or post-injury presentation), how (i.e., how the conditions
affect the injured individual and their subsequent demand for health care services) and which
(i.e., which comorbid conditions cause the greatest burden), with respect to excessive use of
resources, functional outcomes, and all-cause mortality, remain unanswered. Larger population-
based studies are necessary to address these research gaps. The proposed retrospective cohort
study will utilize linked data of all patients with TBI diagnostic codes, derived from emergency
departments (National Ambulatory Care Reporting System), acute care (Discharge Abstract
Database), inpatient rehabilitation (National Rehabilitation System), community services and
long-term care (Home Care Database), continuing care (Continuing Care Reporting System), and
prescription data (Ontario Health Insurance Plan Claims Database) over a 10 year period. At
least 35,000 acute care cases over a 10 year period form the basis of the longitudinal analysis.
These data have undergone quality assessments and linkage by the Institute for Clinical
Evaluation Sciences, a non-profit independent organization that carries out research to improve
the effectiveness of health care services in Ontario, Canada. We hypothesize that acutely derived
variables (i.e., age, intracranial injury, injury mechanism, injury severity, length of stay) –
currently the focus of most research efforts in TBI and comorbidity – are not by themselves
sufficient to accurately predict resource consumption, all-cause mortality, and functional
outcomes in individuals with TBI, stratified by age and sex. We further hypothesize that an
expanded set of factors and factor clusters including patient demographic, certain clinical (i.e.,
comorbid) disorders and social indices, will provide greater accuracy in predicting resource
consumption, all-cause mortality and functional outcomes of TBI, and these clusters will be
subject to change over time. This study of comorbidity in patients with TBI may lead to
uncovering challenging multifaceted problems (i.e., frailty and patient complexity) that are
currently not well defined but generally considered to be closely related to the presence of
multiple comorbid disorders.
October 2015
