Qualitative Pilot Study: Challenges for Primary Healthcare Providers Caring for Refugees in Northeast Ohio
Bibliographic record
Abstract
BACKGROUND: Refugees resettling into the United States are faced with complex barriers to accessing basic health care. Qualitative research is needed from the primary health care providers' (PHCP) experience caring for refugees. Examination of PHCPs' experience adds to a holistic understanding of the healthcare needs of refugees and points to specific health system interventions to improve care. Consideration for Patient-Centered Medical Homes (PMCH) within refugee communities is advanced. Objective: Gather experiences through narratives from PHCPs to understand challenges and barriers in meeting the health care needs of refugees and suggest solutions. Design: Qualitative, descriptive framework. Open-ended, semi-structured interviews. PARTICIPANTS: In-depth interviews (n=seven) with current licensed PHCPs (four physicians and three family nurse practitioners) working in clinic practice settings throughout Northeast Ohio, providing care to four or more refugee families per week. Approach: Interviews were recorded and transcribed. Transcripts were coded and analyzed utilizing thematic analysis to identify themes. KEY RESULTS: Three themes related to challenges faced by PHCPs: 1) coordination and comprehensive care, 2) accessibility of services, 3) provision of patient-centered care. Conclusions: The challenges PHCPs describe in delivering healthcare to refugee families were physical access to resources and care coordination. Support was found for inclusion of PCMH within refugee communities.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".