The influence of patient–clinician ethnocultural and language concordance on continuity and quality of care: a cross-sectional analysis
Bibliographic record
Abstract
<h3>Background:</h3> Concordance refers to shared characteristics between a clinician and patient, such as ethnicity or language. The purpose of this study was to examine whether patient–clinician concordance is associated with patient-reported continuity of care (relational, informational and management) and patient-reported impacts of care (quality and empowerment). <h3>Methods:</h3> This is a secondary analysis of cross-sectional patient surveys that were administered across British Columbia, Manitoba and Quebec using random digit dialling. Participants were adults who spoke English, French, Mandarin, Cantonese or Punjabi and who had visited a primary care clinician in the previous 12 months (<i>n</i> = 3156). Patients self-identified as being of European, Chinese, South Asian and Indigenous descent. Outcome measures included patients’ perceptions of continuity, quality and empowerment. Adjusted logistic regression models and odds ratio were generated. <h3>Results:</h3> More than 64% of non-Indigenous respondents reported ethnocultural concordance. Ethnocultural concordance was associated with higher odds of relational and management continuity. This same pattern held when there was both ethnocultural and language concordance. No association was found between language concordance and any outcome measure. Chinese participants reported lower quality (odds ratio [OR] 0.24, 95% confidence interval [CI] 0.12–0.48), as did South Asian participants (OR 0.17, 95% CI 0.09–0.31) than did participants of European descent. <h3>Interpretation:</h3> Higher relational and management continuity is more likely with the presence of patient–clinician ethnocultural and language concordance. Lower continuity and quality reported by Chinese and South Asian particpants could indicate important health care disparities.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".