C OST -E FFECTIVENESS A NALYSIS OF A R URAL /U RBAN F IRST - RESPONDER D EFIBRILLATION P ROGRAM
Bibliographic record
Abstract
OBJECTIVE: To analyze the cost-effectiveness of a proposed first-responder defibrillation program in a small rural area in comparison with a recently initiated first-responder program in an adjoining urban center in southwestern Ontario. The purpose of the analysis was to quantify the expected benefits of the proposed program to determine whether the costs are justified. METHODS: This analysis was conducted on the city of Waterloo (population 80,000 over 25 square miles) and the adjoining rural township of Wellesley (population 8,000 over 105 square miles). The township has volunteer fire department first responders with basic life support (BLS), and basic life support/defibrillation (BLS-D) ambulances as the second tier; whereas the city's full-time fire department has recently adopted a first-responder defibrillation (BLS-D) program backed up by the same BLS-D ambulance service. The most relevant costs identified were the capital costs of the defibrillators, ancillary equipment, and biomedical service for preventive maintenance and routine nonwarranty work. Response intervals and percentage of patients found in ventricular fibrillation were projected and sensitivity analysis was applied. RESULTS: The projected cost per life saved is $6,776 (C) in the urban area and $49,274 (C) in the rural area using an incremental save rate of 6%. Applying sensitivity analysis to the data, the save rate varied from 2% to 10%, resulting in a cost per life saved of $20,328 (C) and $4,066 (C), respectively, in the urban community. For the rural area, the cost per life saved ranged from $147,821 (C) (2%) to $29,564 (C) (10%). Even the worst-case save rate for the urban center [2%; $20,328 (C)] is significantly less than the best-case save rate [10%; $29,564 (C)] for the rural area. CONCLUSIONS: The cost per life saved for a rural first-responder defibrillation program is significantly more expensive than one for an urban center. However, the cost per life saved is still economical compared with common treatments for other life-threatening illnesses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".