A review of patient safety communication in multicultural and multilingual healthcare settings with special attention to the U.S. and Canada
Bibliographic record
Abstract
Abstract Purpose The present work aims to raise awareness of the issue of patient safety communication in multicultural and multilingual healthcare settings and to present strategies on how to overcome emerging cultural and language barriers and enable healthcare providers to reduce the risk of miscommunication, prevent inequalities and disparities, and provide their patients with safe and quality care. It also strives to present the policies and measures the United States and Canada have implemented and the strategies U.S. experts have developed to advance effective communication between provider and patient. Methods The literature review was conducted on academic works and publications by health associations, institutes of health, and government departments in topics such as adverse events in health care and strategies to reduce cross-cultural miscommunications and on guides for hospitals. Results/Discussion Cultural diversity in a patient population, language barriers, and a lack of effective communication can impose an increased threat on an individual's health. In order to radically decrease the incidence of adverse events, policies and systems on how to manage multinational and multilingual medical environments should be created at a national level. Cultural competence is also key to delivering care that meets patients' social and cultural needs; furthermore, developing a language access plan and providing language assistance (interpretation, translation) for those in need can greatly contribute to providing quality care. Conclusions Clear communication is key to quality care and patient safety in multicultural and multilingual healthcare environments, but to significantly reduce the incidence of adverse events, policies and systems should be created at a national level.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".