A systemic review of global emergency department (1974-2012) crowding research
Bibliographic record
Abstract
Objective Emergency department (EDO) is an increasingly international occurrence which affects the quality and access of health care across the globe.We assessed perceptions of EDO by a detailed and comprehensive surveying of current international research literatures.Methods Through PubMed and BMC electronic literatures search engines from 1974 to 2012,1587 papers of original articles,reviews and comments with key words emergency department AND crowding OR overcrowding are selected.Results 52.6％ (835/1587) all selected literatures is original research articles.21.2％ (n =337) of these papers involved the disciplinary construction of emergency medicine,and editorial comment (included viewpoints) holds almost one fifth (302,19.0％).Most common types of study methods in all original researches is single-center cohort study (722/835,86.5％),and none of them was multi-center,randomized control clinical trial.The number of papers on EDO is 8 during 1974 and 1988,and gradually elevated to 325 during 1989 and 2002.Yet the number has climbed up to 1254 dramatically (account for 79％) during 2003 and 2012.Together,USA,Canada and Austria,these three countries generated more than three-quarters of all published literatures (81.0％).So far,the authors in 48 countries and areas gave forth initial contributions in the field of EDO.Conclusions The studies and papers about EDO are steadily increasing in recent years.But the investigation shows the research quality still remain need to improve.This systemic review on EDO studies showed that the standardized measurement of EDO has become the bottleneck of EDO study.It is very important and urgent for ED staff to establish an objective and effective EDO evaluation system. Key words: Emergency department; Overcrowding; Systemic review; Research literature; Geographic distribution; Annual frequency distribution
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 | 0.009 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.045 | 0.036 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".