Outcomes of Community‐dwelling Seniors Vary by Type of Emergency Department
Bibliographic record
Abstract
OBJECTIVES: The specific objectives were: 1) to compare the characteristics and 6-month outcomes of community-dwelling seniors in Quebec, Canada, who visited three different emergency department (ED) types and 2) to explore whether the differences in outcomes by ED type were seen among subgroups of seniors. METHODS: The three types of ED were most specialized, less community-oriented (n = 12); moderately specialized, less community-oriented (n = 28); and least specialized, more community-oriented (n = 28). Administrative databases were used to create a cohort of 223,120 seniors who visited these 68 EDs during a 14-month period. Using a multilevel approach, the following patient characteristics were compared across ED types: sociodemographic (age, sex, urban vs. rural residence, proximity to ED); medical diagnoses and comorbidity burden; and utilization of hospital and physician services during the 16 months before the index ED visit. Cox regression analysis was used to model the relationships between ED type and two 6-month outcomes, adjusting for patient characteristics: 1) serious outcomes (death, acute or long term-care admission) among all individuals who made an index visit and 2) outpatient ED visits (without hospital admission) among those discharged either from the ED or hospital. Interactions between ED type and patient age, sex, urban-rural residence, and comorbidity burden were explored. RESULTS: Compared to patients treated at the least specialized EDs, those at the most specialized EDs were more often urban-dwelling, resided outside the health service area of the ED, and had the highest disease burden and prior specialist utilization. Those treated at the moderately specialized EDs were intermediate between these two groups. During the 6 months after the ED visit, the rate of serious outcomes was higher and the rate of outpatient ED visits was lower for the most specialized compared to the least specialized EDs, even after adjustment for patient characteristics. The differences in these outcomes by ED type were attenuated among older patients and those with greater comorbidity. CONCLUSIONS: More vulnerable community-dwelling seniors tend to be treated in more specialized EDs, which have worse linkages to community services. Improved linkages between more specialized EDs and the community (physicians, home care, and other services) and increased access to community services may improve outcomes in this population. Seniors treated at more specialized EDs were more likely to experience serious outcomes, but were less likely to make a return outpatient ED visit.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".