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Effects of the August 2003 blackout on the New York City healthcare delivery system: A lesson for disaster preparedness

2005· article· en· W2031356289 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCritical Care Medicine · 2005
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsnot available
Fundersnot available
KeywordsBlackoutMedicineMedical emergencyEmergency medicineEmergency departmentPreparednessEmergency medical servicesSurge CapacityCoronavirus disease 2019 (COVID-19)NursingInternal medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.074
GPT teacher head0.407
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it