Growth in <scp>W</scp>estern <scp>A</scp>ustralian emergency department demand during 2007–2013 is due to people with urgent and complex care needs
Bibliographic record
Abstract
OBJECTIVES: To determine the magnitude and characteristics of the increase in ED demand in Western Australia (WA) from 2007 to 2013. METHODS: We conducted a population-based longitudinal study examining trends in ED demand, stratified by area of residence, age group, sex, Australasian Triage Scale category and discharge disposition. The outcome measures were annual number and rate of ED presentations. We calculated average annual growth, and age-specific and age-standardised rates. We assessed the statistical significance of trends, overall and within each category, using the Mann-Kendall trend test and analysis of variance ANOVA. We also calculated the proportions of growth in ED demand that were attributable to changes in population and utilisation rate. RESULTS: From 2007 to 2013, ED presentations increased by an average 4.6% annually from 739,742 to 945,244. The rate increased 1.4% from 354.1 to 382.6 per 1000 WA population (P = 0.02 for the trend). The main increase occurred in metropolitan WA, age 45+ years, triage category 2 and 3 and admitted cohorts. Approximately three-quarters of this increase was due to population change (growth and ageing) and one-quarter due to increase in utilisation. CONCLUSION: Our study reveals a 4.6% annual increase in ED demand in WA in 2007-2013, mostly because of an increase in people with urgent and complex care needs, and not a shift (demand transfer) from primary care. This indicates that a system-wide integrated approach is required for demand management.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".