Response to language barriers with patients from refugee background in general practice in Australia: findings from the OPTIMISE study
Bibliographic record
Abstract
BACKGROUND: Language is a barrier to many patients from refugee backgrounds accessing and receiving quality primary health care. This paper examines the way general practices address these barriers and how this changed following a practice facilitation intervention. METHODS: The OPTIMISE study was a stepped wedge cluster randomised trial set within 31 general practices in three urban regions in Australia with high refugee settlement. It involved a practice facilitation intervention addressing interpreter engagement as one of four core intervention areas. This paper analysed quantitative and qualitative data from the practices and 55 general practitioners from these, collected at baseline and after 6 months during which only those assigned to the early group received the intervention. RESULTS: Many practices (71 %) had at least one GP who spoke a language spoken by recent humanitarian entrants. At baseline, 48 % of practices reported using the government funded Translating and Interpreting Service (TIS). The role of reception staff in assessing and recording the language and interpreter needs of patients was well defined. However, they lacked effective systems to share the information with clinicians. After the intervention, the number of practices using the TIS increased. However, family members and friends continued to be used to interpret with GPs reporting patients preferred this approach. The extra time required to arrange and use interpreting services remained a major barrier. CONCLUSIONS: In this study a whole of practice facilitation intervention resulted in improvements in procedures for and engagement of interpreters. However, there were barriers such as the extra time required, and family members continued to be used. Based on these findings, further effort is needed to reduce the administrative burden and GP's opportunity cost needed to engage interpreters, to provide training for all staff on when and how to work with interpreters and discuss and respond to patient concerns about interpreting services.
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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 | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| 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".