The integration of the Indigenous patient navigator role in British Columbia health systems : a systematic equity action-analysis
Bibliographic record
Abstract
This research analyzes the integration of the Indigenous Patient Navigator (IPN) role within British Columbia's health systems, with a focus on Interior and Northern Health, guided by the Systematic Equity Action-Analysis framework. The study critically analyzes how integrating the IPN role aligns with organizational equity goals and, more broadly, explores how health systems can better advance equity in integrating Indigenous healthcare roles. Additionally, the study brings to light ways for health systems to align the IPN role integration with broader organizational equity objectives. The research employs a theoretical framework that grounds a systematic equity analysis in a philosophy where integrating Indigenous knowledge with critical Western frameworks challenges dominant worldviews and advances equity. This approach deepens the understanding of the research by considering two different worldviews to gain a clearer understanding of equity and how to integrate Indigenous healthcare roles equitably. The study analyzes the role integration of IPN using qualitative document content analysis, situated within an exploratory literature review. It seeks to identify promising practices and barriers to role integration, as well as similarities and differences in integration practices when compared to other special healthcare provider integration processes, such as the Participatory Evidence-based, Patient-focused, Process (PEPPA) and the PEPPA Plus frameworks for the Advanced Practice Nurse (Bryant-Lukosius & Discenco, 2004; Bryant-Lukosius et al., 2016). It aims to systematically explore coherence between stated intentions and the operationalization of role integration, with attention to factors that facilitate or hinder coherence. By examining how Interior and Northern Health operationalize equity goals through IPN role integration, this research generates actionable recommendations to enhance IPN role integration and align the way health systems integrate the IPN role with their equity goals and commitments. Overall, this work contributes to the broader understanding of how health systems can support reconciliation and advance equitable processes and practices that support health initiatives, such as integrating Indigenous healthcare roles that improve health outcomes for Indigenous populations.
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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 | 0.068 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".