Limited English Proficiency and Perioperative Patient-Centered Outcomes: A Systematic Review
Bibliographic record
Abstract
This systematic review assesses whether limited-English proficiency (LEP) increases risk of having poor perioperative care and outcomes. This review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 99 articles were identified in Embase and PubMed and screened by 2 independent reviewers. Ten studies, which included 3 prospective cohort studies, 6 retrospective cohort studies, and 1 cross-sectional study, met inclusion and exclusion criteria. All studies were of high-quality rating according to the Newcastle-Ottawa scale. Subsequently, the Levels of Evidence Rating Scale for Prognostic/Risk Studies and Grade Practice Recommendations from the American Society of Plastic Surgeons were used to assess the quality of evidence of each study and the strength of the body of evidence, respectively. There is strong evidence that professional medical interpreter (PMI) use or having a language-concordant provider for LEP patients improves understanding of the procedural consent. The evidence also highly suggests that LEP patients are at risk of poorer postoperative pain control and poorer understanding of discharge instructions compared with English-speaking patients. Further studies are needed to discern whether consistent PMI use can minimize the disparities in pain control and discharge planning between LEP and English-proficient (EP) patients. There is some evidence that LEP status is not associated with differences in having adequate access to and receiving surgical preoperative evaluation. However, the evidence is weak given the small number of studies available. There are currently no studies on whether LEP status impacts access to preoperative evaluation by an anesthesiology-led team to optimize the patient for surgery. There is some evidence to suggest that LEP patients, especially when PMI services are not used consistently, are at risk for increased length of stay, more complications, and worse clinical outcomes. The available outcomes research is limited by the relative infrequency of complications. Additionally, only 4 studies validated whether LEP patients utilized a PMI. Future studies should use larger sample sizes and ascertain whether LEP patients utilized a PMI, and the effect of PMI use on outcomes.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".