Factors associated with recurrent emergency department visits among people living with dementia: A retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Research on factors associated with recurrent emergency department (ED) visits and their implications for improving dementia care is lacking. The objective of this study was to examine associations between the individual characteristics of older adults living with dementia and recurrent ED visits. METHODS: We used health administrative databases to conduct a population-based retrospective cohort study among older adults with dementia in Ontario, Canada. We included community-dwelling adults 66 years and older who visited the ED between April 1, 2010, and March 31, 2019 and were discharged home. We recorded all ED visits within one year after the baseline visit. We used recurrent event Cox regression to examine associations between repeat ED visits and individual clinical, demographic, and health service use characteristics. We fit conditional inference trees to identify the most important factors and define subgroups of varying risk. RESULTS: Our cohort included 175,863 older adults with dementia. ED use in the year prior to baseline had the strongest association with recurrent visits (3+ vs.0 adjusted hazard ratio (aHR): 1.92 (1.89, 1.94), 2vs.0 aHR: 1.45 (1.43, 1.47), 1vs.0 aHR: 1.23 (1.21, 1.24)). The conditional inference tree utilized history of ED visits and comorbidity count to define 12 subgroups with ED revisit rates ranging from 0.79 to 7.27 per year. Older adults in higher risk groups were more likely to live in rural and low-income areas and had higher use of anticonvulsants, antipsychotics, and benzodiazepines. CONCLUSIONS: History of ED visits may be a useful measure to identify older adults with dementia who would benefit from additional interventions and supports. A substantial proportion of older adults with dementia have a pattern of recurrent visits and may benefit from dementia-friendly and geriatric-focused EDs. Collaborative medication review in the ED and closer follow-up and engagement with community supports could improve patient care and experience.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".