Did implementation of no-fault auto-insurance in British Columbia, Canada, impact return to work following road trauma? Protocol for a before–after survival analysis
Bibliographic record
Abstract
INTRODUCTION: Road trauma (RT) is a major public health problem that often results in prolonged absenteeism from work. Limited evidence suggests that recovery after RT is associated with automobile insurance compensation schemes. In May 2021, British Columbia, Canada switched from fault-based to no-fault auto-insurance coverage. This manuscript presents the protocol for a planned evaluation of that natural experiment: We will evaluate the impact of changing automobile insurance schemes on return to work following RT. METHODS AND ANALYSIS: The evaluation will use a before-after design to analyse auto-insurance claims (1 April 2019 to 30 April 2024) in order to compare recovery of claimants with non-catastrophic injuries who filed claims under the no-fault insurance scheme to that of those who filed claims under the previous system. Claimants will be followed from date of injury until they return to work or have been followed for 6 months (right-censored). We will perform sensitivity analyses to examine the robustness of our findings. First, we will exclude injuries that occurred during the COVID-19 provincial State of Emergency. Second, we will use propensity score methods rather than conventional covariate adjustment to address potential imbalance between characteristics of claimants pre-change and post-change. Finally, as the implementation effect may have a heterogeneous association with time off work, we will use quantile regression with right-censoring at 6 months to model differences in return to work at the 25th, 50th, 75th and 90th percentiles. ETHICS AND DISSEMINATION: The study uses de-identified data and is approved by the University of British Columbia Clinical Research Ethics Board (H20-03644). This research is funded by the Insurance Corporation of British Columbia (ICBC). Findings will be published in the peer-reviewed literature and summarised in a report prepared for ICBC. We anticipate that our findings will inform policy decisions in other jurisdictions considering switching to no-fault auto-insurance schemes.
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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 | 0.030 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.052 | 0.009 |
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".