RESEARCH ARTICLE Open Access Direct cost associated with acquired brain injury
Bibliographic record
Abstract
Background: Acquired Brain Injury (ABI) from traumatic and non traumatic causes is a leading cause of disability worldwide yet there is limited research summarizing the health system economic burden associated with ABI. The objective of this study was to determine the direct cost of publicly funded health care services from the initial hospitalization to three years post-injury for individuals with traumatic (TBI) and non-traumatic brain injury (nTBI) in Ontario Canada. Methods: A population-based cohort of patients discharged from acute hospital with an ABI code in any diagnosis position in 2004 through 2007 in Ontario was identified from administrative data. Publicly funded health care utilization was obtained from several Ontario administrative healthcare databases. Patients were stratified according to traumatic and non-traumatic causes of brain injury and whether or not they were discharged to an inpatient rehabilitation center. Health system costs were calculated across a continuum of institutional and community settings for up to three years after initial discharge. The continuum of settings included acute care emergency departments inpatient rehabilitation (IR) complex continuing care home care services and physician visits. All costs were calculated retrospectively assuming the government payer’s perspective. Results: Direct medical costs in an ABI population are substantial with mean cost in the first year post-injury per TBI and nTBI patient being $32132 and $38018 respectively. Among both TBI and nTBI patients those discharged to IR
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.026 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".