Bibliographic record
Abstract
Abstract Objective To describe the associations between the socioeconomic status of emergency department (ED) users and age, sex, and acuity of medical conditions to better understand users’ common characteristics, and to better meet primary and ambulatory health care needs. Design A retrospective, observational, population-based analysis. A rigorous proxy of socioeconomic status was applied using census-based methods to calculate a relative deprivation index. Setting Ontario. Participants All Ontario ED visits for the fiscal year April 1, 2008, to March 31, 2009, from the National Ambulatory Care Reporting System data set. Main outcome measures Emergency department visits were ranked into deprivation quintiles, and associations between deprivation and age, sex, acuity at triage, and association with a primary care physician were investigated. Results More than 25% of ED visits in Ontario were from the most deprived population; almost half of those (12.3%) were for conditions of low acuity. Age profiles indicated that a large contribution to low-acuity ED visits was made by young adults (aged 20 to 30 years) from the most deprived population. For the highest-volume ED in Ontario, 94 of the 499 ED visits per day were for low-acuity patients from the most deprived population. Most of the highest volume EDs in Ontario (more than 200 ED visits per day) follow this trend. Conclusion Overall input into EDs might be reduced by providing accessible and appropriate primary health care resources in catchment areas of EDs with high rates of low-acuity ED visits, particularly for young adults from the most deprived segment of the population.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.081 | 0.038 |
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 source (direct Gemma or distilled Codex), 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".