Utilization and Cost of Health Services in Individuals With Traumatic Brain Injury
Bibliographic record
Abstract
Traumatic Brain Injury (TBI) has gained attention in the past decade as a "signature injury" in the conflicts in Iraq and Afghanistan. TBI is a major burden for both the military and civilian population in the US and worldwide. It is a leading cause of death and disability in the US and a major health services resource burden. We seek to answer two questions. What is the evidence regarding the association of TBI with health services utilization and costs in the US and worldwide? What is the evidence regarding racial/ethnic, gender, geographic, socio-economic and other disparities in health services utilization and cost in the US and worldwide? To attain this goal we searched several databases using key words to perform a systematic review of the literature since 2000. We found 36 articles to be eligible for inclusion in the review. The evidence demonstrates a wide variation in health services utilization and costs depending on population of study and severity of TBI. The evidence also supports the existence of racial/ethnic, gender, insurance, geographic disparities in the US as well as other unique disparities worldwide.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".