Deciding to Attend the Emergency Department: Experiences of Patients With Inflammatory Arthritis
Bibliographic record
Abstract
OBJECTIVE: Patients may use emergency departments (EDs) to meet their health needs when ambulatory care systems are not sufficient. We aim to describe contributing factors to the decision made by persons with inflammatory arthritis (IA) to present to the ED, as well as their experiences of ED care and postdischarge follow-up. METHODS: An embedded mixed-methods approach was taken to contextualize quantitative data with associated free-text responses from an online survey distributed to residents of Alberta with a known IA condition and an ED visit. RESULTS: Eighty-two persons (63% aged 16-55 years, 48% female, 50% urban residents) with rheumatoid arthritis (48%), psoriatic arthritis (12%), spondyloarthritis (6%), or gout (34%) completed the survey. Presenting concerns were arthritis flare (37%), chest pain (15%), injury (12%), and infection (11%). Of all visits, 29% proceeded directly to the ED, 35% attempted accessing ambulatory care first, and 32% arrived for a return visit. In presentations for arthritis flare, patients were aware of the rheumatology service being contacted by the ED provider for advice in just 9% of events. Challenges in healthcare system coordination and system pressures resulted in patients requiring ED attendance to assess their concern. The quality of communication and relationality developed between patients with IA and healthcare providers informed experiences of ED care. CONCLUSION: Modifying rheumatology ambulatory care models could better meet patient needs and ultimately reduce avoidable ED use by patients with IA.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".