Influenza and Emergency Department Utilization by Elders
Bibliographic record
Abstract
OBJECTIVES: Influenza outbreaks have been associated with worsened emergency department (ED) crowding. We sought to examine the mechanism behind this association. METHODS: A retrospective time series analysis was conducted in Toronto from January 1996 to April 1999. Weekly data on laboratory-confirmed influenza and other respiratory virus cases in the community and visits to all city EDs (n = 20) were obtained. In longitudinal analyses, we determined the association between influenza and changes in ED utilization by younger and older patients with specific diagnoses grouped as major influenza related (MIR) and upper respiratory infection (URI). Time trends in psychiatric visits and their relationship to influenza were used as a control group. RESULTS: A mean of 11,075 ED visits occurred weekly (SD = 698; average age, 39.9 years; 51% women). Four influenza seasons occurred, with weekly incident case counts ranging from 0 to 236; there were a total of 81 weeks with zero new cases between seasons. In multivariable analyses, every ten new cases of influenza active in the community was associated with a 1.5% (95% confidence interval = 1.2 to 1.8) and 1.2% (95% confidence interval = 0.6 to 1.8) absolute increase in the proportion of ED patients who were elders with MIR conditions and URIs, respectively. Influenza was not significantly associated with ED utilization by younger patients; other respiratory viruses were not significantly associated with ED utilization for any patient group. CONCLUSIONS: Influenza season is associated with increased ED utilization by patients aged 65 years and older, most of whom have major respiratory illnesses and may require hospital admission. No association was seen between influenza and utilization by younger patients. Efforts to reduce the impact of influenza seasons on EDs should focus on elders.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.005 | 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".