Mortality, admission rates and outpatient use among frequent users of emergency departments: a systematic review
Bibliographic record
Abstract
OBJECTIVE: This systematic review examines whether frequent emergency department (ED) users experience higher mortality, hospital admissions and outpatient visits than non-frequent ED users. DESIGN: We published an a priori study protocol in PROSPERO. Our search strategy combined terms for 'frequent users' and 'emergency department'. At least two independent reviewers screened, selected, assessed quality and extracted data. Third-party adjudication resolved conflicts. Results were synthesised based on median effect sizes. DATA SOURCES: We searched seven electronic databases with no limits and performed an extensive grey literature search. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: We included observational analytical studies that focused on adult patients, had a comparison group of non-frequent ED users and reported deaths, admissions and/or outpatient outcomes. RESULTS: The search strategy identified 4004 citations; 374 were screened by full text and 31 cohort and cross-sectional studies were included. Authors used many different definitions to describe frequent users; the overall quality of the included studies was moderate. Across seven studies examining mortality, frequent users had a median 2.2-fold increased odds of mortality compared with non-frequent users. Twenty-eight studies assessing hospital admissions found a median increased odds of admissions per visit at 1.16 and of admissions per patient at 2.58. Ten studies reported outpatient visits with a median 2.65-fold increased risk of having at least one outpatient encounter post-ED visit. CONCLUSIONS: Frequent ED users appear to experience higher mortality, hospital admissions and outpatient visits compared with non-frequent users, and may benefit from targeted interventions. Standardised definitions to facilitate comparable research are urgently needed. REVIEW REGISTRATION NUMBER: PROSPERO (CRD42013005855).
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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 | 0.008 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".