Home therapy for inherited bleeding disorders in South Africa: Results of a modified Delphi consensus process
Bibliographic record
Abstract
BACKGROUND: Optimal care of patients with inherited bleeding disorders requires that bleeding episodes are treated early, or still better prevented, through extension of patient care beyond hospital-based treatment to home-based therapy. In South Africa (SA), adoption of home therapy is variable, in part owing to lack of consensus among healthcare providers on what constitutes home therapy, which patients should be candidates for it, how it should be monitored, and what the barriers to home therapy are. OBJECTIVES: To conduct a modified Delphi process in order to establish consensus on home therapy among haemophilia healthcare providers in SA. METHODS: Treaters experienced in haemophilia care were invited to participate in a consensus-seeking process conducted in three rounds. In round 1, provisional statements around home therapy were formulated as questions and collated in a structured list. In rounds 2 and 3, evolving versions of the questionnaire were administered to participants. Consensus was defined as ≥70% agreement among the participants. RESULTS: The panel composition included an equal number of physicians and non-physicians. The participation rate was 100% through all three consensus rounds. The group reached consensus for 92% of the statements. Consensus of 100% was reached on starting home therapy in paediatric patients, requiring all patients on home therapy to sign informed consent and indemnity, and providing round-the-clock support for patients on home therapy. CONCLUSIONS: The home therapy consensus statements in this report have the potential to translate to policy on home therapy and to guide the initiation, practice and evaluation of home therapy programmes in SA.
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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 | 0.117 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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".