Effect of widespread restrictions on the use of hospital services during an outbreak of severe acute respiratory syndrome
Bibliographic record
Abstract
BACKGROUND: Restrictions on the nonurgent use of hospital services were imposed in March 2003 to control an outbreak of severe acute respiratory syndrome (SARS) in Toronto, Ont. We describe the impact of these restrictions on health care utilization and suggest lessons for future epidemics. METHODS: We performed a retrospective population-based study of the Greater Toronto Area (hereafter referred to as Toronto) and unaffected comparison regions (Ottawa and London, Ont.) before, during and after the SARS outbreak (April 2001-March 2004). We determined the adjusted rates of hospital admissions, emergency department and outpatient visits, diagnostic testing and drug prescribing. RESULTS: During the early and late SARS restriction periods, the rate of overall and medical admissions decreased by 10%-12% in Toronto; there was no change in the comparison regions. The rate of elective surgery in Toronto fell by 22% and 15% during the early and late restriction periods respectively and by 8% in the comparison regions. The admission rates for urgent surgery remained unchanged in all regions; those for some acute serious medical conditions decreased by 15%-21%. The rates of elective cardiac procedures declined by up to 66% in Toronto and by 71% in the comparison regions; the rates of urgent and semi-urgent procedures declined little or increased. High-acuity visits to emergency departments fell by 37% in Toronto, and inter-hospital patient transfers fell by 44% in the circum-Toronto area. Drug prescribing and primary care visits were unchanged in all regions. INTERPRETATION: The restrictions achieved modest reductions in overall hospital admissions and substantial reductions in the use of elective services. Brief reductions occurred in admissions for some acute serious conditions, high-acuity visits to emergency departments and inter-hospital patient transfers suggesting that access to care for some potentially seriously ill patients was affected.
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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 | 0.003 | 0.003 |
| 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 | 0.001 |
| 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".