Impact of a New Program of Care for Work-Related Mild Traumatic Brain Injury on Recovery and Return to Work
Bibliographic record
Abstract
BACKGROUND: The Workplace Safety and Insurance Board (WSIB) in Ontario, Canada, launched a new community-based mild traumatic brain injury (mTBI) program of care (POC) in November 2020. The new program included graded exercise therapy and vestibular rehabilitation (where required). The objective of this study was to assess the impact of the new mTBI POC on recovery and return to work among patients who suffered a work-related mTBI. METHODS: We identified WSIB claims that accessed the previous and new mTBI POC over a 4-year timeframe (October 1, 2017, to September 30, 2019, and July 1, 2021, to June 30, 2023). A quasi-experimental pre-post study, propensity score matching design with a difference-in-difference modelling component was applied to approximate estimation of causal effects on loss of earnings (LOE) benefit duration at 3-, 6-, and 12-months and HC costs for patients treated in the previous and new programs. RESULTS: Over the 4-year timeframe, 5625 patients accessed the previous and new mTBI POC. The new program achieved improved 3-, 6-, and 12-month disability durations (incremental percentage difference of -11.7%, -9.3%, and -9.0%, respectively), and shorter durations of disability, reflected by decreased LOE benefit costs (incremental percentage difference of -32.6%) and decreased HC costs (incremental percentage difference of -5.6%). The overall combined savings in LOE and HC costs was 21%. CONCLUSIONS: This analysis indicates that the implementation of this new evidence based mTBI POC resulted in improved outcomes (decreased disability duration and lower health care utilization) on a per patient basis for people with work-related mTBI.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".