Professional over-the-phone interpretation to improve the quality of primary care for migrants: a feasibility study
Bibliographic record
Abstract
Background: In Canada, health disparities exist between limited language (English/French) proficient (LLP) patients and English/French proficient patients, principally in the areas of quality and access to care. The use of professional interpreters (PIs) during medical encounters with LLP patients has been shown to significantly reduce these language-based inequalities, yet PIs are rarely engaged. Little work has been done to shed light on the feasibility of using language service technologies, such as telephone interpretation, especially in primary care. This is worthy of investigation in Montreal where clinicians have limited or no access to language support services. Objective: To investigate the feasibility of over-the-phone interpretation (OPI) service use in primary care clinics by measuring healthcare professionals’ service usage and their perception of the factors that are likely to impact service usage.Participants: All (117) healthcare professionals (including staff physicians, residents, nurses, and nurse practitioners) from two Montreal primary care clinics were invited to participate.Methods: For this prospective cohort study, all primary healthcare professionals at two Montreal primary care clinics were given unlimited, on-demand access to OPI services for three months. Participants completed two self-administered surveys before and after the study. This was supplemented with service usage data (routinely collected by the service provider) and participants’ reports on their number of LLP patient encounters during the study. Key results: OPI service usage at the two primary care clinics differed; while OPI usage was consistent at clinic 2, it decreased significantly at clinic 1. As expected, a significant gap exists between the number of LLP patient visits and the frequency of OPI usage. At both clinics, participants had positive attitudes towards and opinions of the OPI service but, for various reasons, many had difficulty integrating the service into their daily routine.Conclusion: Based on the patterns of service usage at each clinic, and an evaluation of the factors that are likely to impact service usage, OPI service has the potential to be used in Montreal primary care clinics, but is not necessarily feasible under the given circumstance. Uptake of OPI services would improve by providing more in-depth training for healthcare professionals in OPI use, systematically identifying LLP patients, and by providing OPI services in both of Canada’s official languages.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".