Healthcare provider perspectives on inequities in access to care for patients with inherited bleeding disorders
Bibliographic record
Abstract
INTRODUCTION: The ways in which social determinants of health affect patients with inherited bleeding disorders remains unclear. The objective of this study was to understand healthcare provider perspectives regarding access to care and diagnostic delay amongst this patient population. METHODS: A healthcare provider survey comprising 24 questions was developed, tested, and subsequently disseminated online with recruitment to all members of The Association of Hemophilia Clinic Directors of Canada (N = 73), members of the Canadian Association of Nurses in Hemophilia Care (N = 40) and members of the Canadian Physiotherapists in Hemophilia Care (N = 44). RESULTS: There were 70 respondents in total, for a total response rate of 45%. HCPs felt that there were diagnostic delays for patients with mild symptomatology (71%, N = 50), women presenting with abnormal uterine bleeding as their only or primary symptom (59%, N = 41), and patients living in rural Canada (50%, N = 35). Fewer respondents felt that factors such as socioeconomic status (46%, N = 32) or race (21%, N = 15) influenced access to care, particularly as compared to the influence of rural location (77%, N = 54). DISCUSSION: We found that healthcare providers identified patients with mild symptomatology, isolated abnormal uterine bleeding, and residence in rural locations as populations at risk for inequitable access to care. These factors warrant further study, and will be investigated further by our group using our nation-wide patient survey and ongoing in-depth qualitative patient interviews.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".