A survey of transfusion practitioners in international society of blood transfusion member countries
Bibliographic record
Abstract
BACKGROUND: Transfusion Practitioner (TP) is a term that describes activities undertaken by a variety of healthcare professionals who play a key role in supporting safe and appropriate blood management/transfusion care for patients. There is significant variation in staff specialty filling the role. To understand which countries have the TP role, and the variations that exist, an international survey was undertaken in 2017. METHODS: A survey was developed by the TP Forum Steering Committee (TPFSC) with input from the International Society of Blood Transfusion (ISBT) Clinical Transfusion Working Party. The survey was distributed by the ISBT Office to all ISBT members and promoted via newsletters and social media. RESULTS/DISCUSSION: Five hundred and eighty-two responses received from 84 different countries. The TP role exists in 67 countries, 10 countries do not have the TP role, one was unaware of the role, and respondents from six other countries did not answer this question. The most prevalent TP activities reported were policy and procedure development, education, participation in Transfusion Committees and audit activities. Eighty-eight respondents indicated they did not have a TP role, with the main barrier being financial, followed by lack of support for the role. Eight respondents indicated they previously had a TP, and this role was no longer in place due to lack of support for the role, cutbacks and other priorities. CONCLUSION: This survey provides insights as to where and how the TP functions and provides the TPFSC with valuable information to develop tools to support further development of the role.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".