Including the patient in patient blood management: Development and assessment of an educational animation tool
Bibliographic record
Abstract
BACKGROUND: Patient blood management (PBM) programs are effective at reducing transfusion-associated mortality and morbidity; however, patient engagement within the realm of PBM remains relatively unstudied. Our objectives were to develop a novel educational tool utilizing animation to educate preoperative patients about anemia and to evaluate the effectiveness of this intervention. STUDY DESIGN AND METHODS: We created a patient-facing animation for preoperative surgical patients. The animation addressed characters' health journeys from diagnosis to treatment, addressing the role of PBM. We utilized the concept of patient activation as a means to empower patients, and developed the animation to be as accessible as possible. Post-viewing, patients provided feedback utilizing an electronic survey. RESULTS: A final version of the animation can be found here: https://vimeo.com/495857315. A total of 51 participants viewed our animation, the majority of whom were planned to undergo joint replacement or cardiac surgery. Almost all (94%, N = 4) agreed that taking an active role in their health was the most important factor in determining their ability to function. The video was felt to be easy to understand (96%, N = 49), and 92% (N = 47) agreed that they had a better understanding of anemia and its treatment. After watching the animation, patients felt more certain that they could follow through with their PBM plan (98%, N = 50). DISCUSSION: To the best of our knowledge, there are no other PBM-specific patient education animations. Patients enjoyed learning about PBM though animation, and patient education may lead to better uptake of PBM interventions. We hope that other hospitals will be inspired to pursue this approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".