Patients’ and health care providers’ perspectives on quality of hemophilia care in the Netherlands: a questionnaire and interview study
Bibliographic record
Abstract
Background: Hemophilia care has improved greatly because of advances in treatment options and comprehensive care. In-depth insight into the perspectives of persons with hemophilia and health care providers on their care may provide targets for further improvements. Objectives: To assess satisfaction of the hemophilia population with their care, to explore factors determining care satisfaction, and to identify areas for potential health care improvements, including digital health tools. Methods: First, to assess care satisfaction and factors determining satisfaction and health care improvements, data from a nationwide, cross-sectional questionnaire among 867 adult and pediatric Dutch persons with hemophilia A or B were analyzed. This included the Hemophilia Patient Satisfaction Scale questionnaire, Canadian Hemophilia Outcomes Kids' Life Assessment Tool satisfaction questions, a visual analog scale satisfaction score, and open questions. Second, to further explore factors determining satisfaction and health care improvements, semistructured interviews were conducted with 19 persons with hemophilia or their parents and 18 health care providers. Results: High care satisfaction was found, with an overall median Hemophilia Patient Satisfaction Scale score of 12 (IQR, 6-21). Participants in the interviews reported that patient-professional interactions, availability of care, and coordination of care were major factors determining satisfaction. Suggested health care improvements included improved information provision and coordination of care, especially shared care with professionals not working within comprehensive care centers. Participants suggested that digital health tools could aid in this. Conclusion: Satisfaction with hemophilia care is high among persons with hemophilia in the Netherlands, although several potential improvements have been identified. Accentuating these is especially relevant in the current era of treatment innovations, in which we might focus less on other aspects of 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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".