Effects of the August 2003 blackout on the New York City healthcare delivery system: A lesson for disaster preparedness
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Bibliographic record
Abstract
BACKGROUND: On August 14, 2003, the United States and Canada suffered the largest power failure in history. We report the effects of this blackout on New York City's healthcare system by examining the following: 1) citywide 911 emergency medical service (EMS) calls and ambulance responses; and 2) emergency department (ED) visits and hospital admissions to one of New York City's largest hospitals. METHODS: Citywide EMS calls and ambulance responses were categorized by 911 call type. Montefiore Medical Center (MMC) ED visits and hospital admissions were categorized by diagnosis and physician-reviewed for relationship to the blackout. Comparisons were made to the week pre- and postblackout. RESULTS: Citywide EMS calls numbered 5,299 on August 14, 2003, and 5,021 on August 15, 2003, a 58% increase (p < .001). During the blackout, there were increases in "respiratory" (189%; p < .001), "cardiac" (68%; p = .016), and "other" (40%; p < .001) EMS call categories, but when expressed as a percent of daily totals, "cardiac" was no longer significant. The MMC-ED reflected this surge with only "respiratory" visits significantly increased (expressed as percent of daily total visits; p < .001). Respiratory device failure (mechanical ventilators, positive pressure breathing assist devices, nebulizers, and oxygen compressors) was responsible for the greatest burden (65 MMC-ED visits, with 37 admissions) as compared with 0 pre- and postblackout. CONCLUSIONS: The blackout dramatically increased EMS and hospital activity, with unexpected increases resulting from respiratory device failures in community-based patients. Our findings suggest that current capacity to respond to public health emergencies could be easily overwhelmed by widespread/prolonged power failure(s). Disaster preparedness planning would be greatly enhanced if fully operational, backup power systems were mandated, not only for acute care facilities, but also for community-based patients dependent on electrically powered lifesaving devices.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it