Blackout 2003: Preparedness and Lessons Learned from the Perspectives of Four Hospitals
Bibliographic record
Abstract
INTRODUCTION: The blackout in North America of August 2003 was one of the worst on record. It affected eight US states and parts of Canada for >24 hours. Additionally, two large US cities, Detroit, Michigan and Cleveland, Ohio, suffered from a loss of water pressure and a subsequent ban on the use of public supplies of potable water that lasted four days. A literature review revealed a paucity of literature that describes blackouts and how they may affect the medical community. METHODS: This paper includes a review of after-action reports from four inner-city, urban hospitals supplemented accounts from the authors' hospital's emergency operations center (EOC). RESULTS: Some of the problems encountered, included: (1)lighting; (2) elevator operations; (3) supplies of water; (4) communication operations; (5) computer failure; (6) lack of adequate supplies of food; (7) mobility to obtain X-ray studies; (8) heating, air condition, and ventilation; (9) staffing; (10) pharmacy; (11) registration of patients; (12) hospital EOC; (13) loss of isolation facilities; (14) inadequate supplies of paper; (15) impaired ability to provide care for non-emergency patients; (16) sanitation; and (17) inadequate emergency power. DISCUSSION: The blackout of 2003 uncovered problems within the US hospital system, ranging from staffing to generator coverage. This report is a review of the effects that the blackout and water ban of 2003 had on hospitals in a large inner-city area. Also discussed are solutions utilized at the time and recommendations for the future. CONCLUSION: The blackout of 2003 was an excellent test of disaster/emergency planning, and produced many valuable lessons to be used in future events.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".