Partnerships in specialty care: Exploring rural haemophilia provider resource needs
Bibliographic record
Abstract
Abstract Objective: The purpose of this study was to determine whether rural providers have adequate preparation for safe and effective haemophilia care. Design: This qualitative study proceeded in two phases: focus group (phase I) and telephone (phase II) interviews. Setting: Five Canadian rural hospitals served by one urban haemophilia treatment centre and providing service to at least one haemophilia family. Participants: Phase I: focus groups of rural health professionals (site 1: n = 5; site 2: n = 6), including nursing, medicine and lab technology. Phase II: telephone interviews with nine participants from nursing, medicine, lab technology, social work and physiotherapy across three sites. Main outcome measures: Qualitative content analysis yielded categorical themes for specialty care resource requirements in a rural context. Results: Resource needs reflected five main categories: communication network, subjective knowledge, team roles, objective knowledge and partnerships (C‐STOP). Conclusions: The five C‐STOP categories require resources and alignment of urban specialist, rural provider and family expertise. Specialty clinic efforts promoting self‐care are incomplete without matched resources for rural providers. Key Terms: • Haemophilia (A and B) refers to a deficiency in factor VIII or IX, with associated bleeding of post‐traumatic or spontaneous origin as potentially life or limb threatening 1 • Rural refers to those communities beyond a 30‐min commuting distance 2 to the tertiary‐based haemophilia treatment centre.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".