Language Preference, Surgical Wait Time, and Outcomes Among Older Adults With Hip Fracture
Bibliographic record
Abstract
Importance: Patients with a non-English language preference served within English-dominant health care settings are at increased risk of adverse events that may be associated with communication barriers and inequitable access to care. Objective: To investigate the association of non-English language preference with surgical wait time and postoperative outcomes in older patients undergoing hip fracture repair. Design, Setting, and Participants: This population-based, retrospective cohort study was conducted using linked databases to measure surgical wait time and postoperative outcomes among older adults (aged ≥66 years) in Ontario, Canada, who underwent hip fracture surgery between January 1, 2017, and December 31, 2022. Propensity-based overlap weighting accounting for baseline patient characteristics was used to compare primary and secondary outcomes. Exposure: Non-English language preference. Main Outcomes and Measures: The primary outcome was surgical delay beyond 24 hours. Secondary outcomes included time to surgery, surgical delay beyond 48 hours, postoperative medical complications, length of stay, discharge destination, 30-day mortality, and 30-day hospital readmission. Results: Among 35 238 patients who underwent hip fracture surgery, 28 815 individuals (81.8%) were English speakers (mean [SD] age, 84.4 [8.0] years; 19 965 female [69.3%]) and 6423 individuals (18.2%) were non-English speakers (mean [SD] age, 85.5 [7.0] years; 4556 female [70.9%]). The median (IQR) wait time for surgery was similar for English (24 [16-41] hours) and non-English (25 [16-42] hours) speakers. There was no significant difference in surgical delay beyond 24 hours between English-speaking and non-English-speaking patients (3321 patients [51.7%] vs 14 499 patients [50.3%]; adjusted relative risk [aRR], 1.00; 95% CI, 0.98-1.03). Compared with English speakers, patients with a non-English language preference had increased risk of delirium (4207 patients [14.6%] vs 1209 patients [18.8%]; aRR, 1.10; 95% CI, 1.03-1.17), myocardial infarction (150 patients [0.5%] vs 43 patients [0.7%]; aRR, 1.52; 95% CI, 1.04-2.22), longer length of stay (median [IQR], 10 [6-17] vs 11 [7-20] days; aRR per 1-day increase, 1.11; 95% CI, 1.06-1.15), and more frequent discharge to a nursing home (1814 of 26 673 patients surviving to discharge [6.8%] vs 413 of 5903 patients surviving to discharge [7.0%]; aRR, 1.13; 95% CI, 1.01-1.27). Conclusions and Relevance: In this study of older adults with hip fracture, non-English language preference was associated with increased risk of delirium, myocardial infarction, longer length of stay, and discharge to a nursing home. These findings suggest inequities in hip fracture care for patients with a non-English language preference.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".