Healthcare Costs of Burn Patients From Homes Without Fire Sprinklers
Bibliographic record
Abstract
The treatment of burn injuries requires high-cost services for healthcare and society. Automatic fire sprinklers are a preventive measure that can decrease fire injuries, deaths, property damage, and environmental toxins. This study's aim was to conduct a cost analysis of patients with burn or inhalation injuries caused by residential fires and to compare this with the cost of implementing residential automatic fire sprinklers. We conducted a cohort analysis of adult burn patients admitted to our provincial burn center (1995-2012). Patient demographics and injury characteristics were collected from medical records and clinical and coroner databases. Resource costs included average cost per day at our intensive care and rehabilitation program, transportation, and property loss. During the study period, there were 1557 residential fire-related deaths province-wide and 1139 patients were admitted to our provincial burn center as a result of a flame injury occurring at home. At our burn center, the average cost was CAN$84,678 per patient with a total cost of CAN$96,448,194. All resources totaled CAN$3,605,775,200. This study shows the considerable healthcare costs of burn patients from homes without fire sprinklers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".