The economic burden of burned patients for hospitalization in Canada
Bibliographic record
Abstract
BACKGROUND: Burn injuries pose a significant burden on both patients and healthcare systems. Yet, costs arising from the consumption of resources by these patients are rarely examined in Canada. OBJECTIVE: The objective of this study was to assess real-world costs resulting from the initial hospitalization of patients admitted to a major burn unit in Quebec, Canada. METHODS: A cost study based on a retrospective cohort was undertaken using in-hospital economic data matched to hospital chart data. Our cohort included all burn-injured patients admitted between April 1, 2017, and March 31, 2021, to the hospital's major burn unit during their initial hospitalization. Descriptive statistics were tabulated for sociodemographic and economic data. Costing data were analyzed unstratified and stratified according to burn severity (i.e., ≥ 20% of total body surface area [TBSA] vs. < 20%). Costs were presented in CAD 2021. RESULTS: Our cohort included 362 patients, including 65 (18%) with TBSA ≥ 20%. The average initial hospitalization cost was $32,360 ($22,783 for < 20% TBSA and $76,121 for ≥ 20% TBSA). CONCLUSION: Findings reveal that the total cost of the initial hospitalization, from a public hospital perspective, was $11,714,348. Our study underlines the substantial burden associated with burns and highlights the need for long-term cost evaluations.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".