Effectiveness and Cost-Effectiveness of Automated External Defibrillators in Private Homes
Bibliographic record
Abstract
Importance: Automated external defibrillators (AEDs) have the potential to save lives when used during cardiac arrest. While most cardiac arrests occur at home, there is limited evidence for AED use in private homes. Objective: To determine whether AEDs in private homes are effective and cost-effective. Design, Setting, and Participants: This cohort study used observational data from the Cardiac Arrest Registry to Enhance Survival in the US from January 2017 to December 2024 to determine the effectiveness of AEDs when used for cardiac arrests in private homes. A difference-in-difference approach was used to determine the causal relationship between AED application and survival to hospital discharge. A decision-analytic model was then created to evaluate the cost-effectiveness of purchasing an AED in a private home in the US. Exposure: Application of an AED. Main Outcomes and Measures: Survival to hospital discharge and cost-effectiveness. Results: Of 582 536 included patients, 359 809 (61.8%) were male, and the median (IQR) age was 65 (52-76) years. Survival was better with AED application compared with no AED application in patients with a shockable rhythm (risk ratio, 1.26; 95% CI, 1.01-1.57) but not in those with a nonshockable rhythm (risk ratio, 1.00; 95% CI, 0.68-1.46). Results were consistent in the difference-in-difference analysis. The incremental cost-effectiveness ratio for an AED in a private home was $4 481 659 per quality-adjusted life-year. At a cost-effectiveness threshold of $200 000 per quality-adjusted life-year, AEDs in private homes would be considered cost-effective at a yearly cardiac arrest incidence per person above 1.3% or at an AED cost less than $65 (not including bystander training cost). Conclusions and Relevance: In this study, AEDs in private homes were effective at improving outcomes for patients with cardiac arrest and a shockable rhythm. Given the relative rarity of cardiac arrest at a given home, general purchase of AEDs for individual private homes cannot be considered cost-effective at the current pricing of AEDs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".