North End Community Health Centre in Halifax, NS: Relationship-based care goes beyond collaborative care to address patient needs.
Bibliographic record
Abstract
OBJECTIVE: To identify and describe features of relationship-based care that contribute to a successful collaborative model of primary care delivery. DESIGN: Focused institutional ethnography using a critical medical anthropology approach. SETTING: The North End Community Health Centre (NECHC) in downtown Halifax, NS. PARTICIPANTS: Twenty health care providers employed or previously employed at the NECHC. METHODS: Qualitative data collection included participant observation, recorded and transcribed semistructured interviews, informal discussions, and policy document analysis. Data collection continued until saturation was reached, between December 2014 and October 2016. Data were member checked, coded, and triangulated with evidence from policy documents and informal conversations to establish credibility. MAIN FINDINGS: The NECHC offers high-quality care to the community, welcoming marginalized, vulnerable populations. The NECHC's recognized success is grounded in unique relationships among providers, patients, and the community. Four key themes contributing to relationship-based care in the clinic's operation emerged: an activist provider identity, cultural safety, provider-patient relationships, and provider-provider relationships. Inadequate provincial funding mechanisms limit the work and development of the clinic. CONCLUSION: Collaborative care is advanced by health authorities to improve quality of care and reduce health care costs. This model is still poorly understood in Nova Scotia. The findings, which draw on focused ethnographic fieldwork and analysis of the NECHC, suggest that the NECHC is a pragmatic real-world model of collaborative health care. The success of its approach relies on a deliberative democratic realization of reflexive practice through relationship-based care.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".