Evaluation of a patient self-medication program in allogeneic hematopoietic stem cell transplantation
Bibliographic record
Abstract
Introduction Patients admitted for allogeneic hematopoietic stem cell transplantation (allo-HSCT) are discharged with multiple new medications. At our institution, a new patient Self Medication Program (SMP) was implemented on the allo-HSCT units. An SMP allows patients to practice self-administration of medications in a controlled environment before discharge. We assessed the impact of the SMP on patient medication knowledge, self-efficacy, adherence, and safety. Patient and staff satisfaction with the SMP was also explored. Methods Participants in the SMP group received medication counseling by a pharmacist and self-managed their medications with nursing supervision until discharge. Participants in the pre-SMP group received medication counseling by a pharmacist at discharge. All participants completed a Medication Knowledge and Self-Efficacy Questionnaire before discharge and at follow-up. Safety endpoints were assessed for SMP participants. Results Twenty-six patients in the pre-SMP group and 25 patients in the SMP group completed both questionnaires. Median knowledge scores in the pre-SMP group versus the SMP group were 8.5/10 versus 10/10 at discharge ( p = 0.0023) and 9/10 versus 10/10 at follow-up ( p = 0.047). Median self-efficacy scores were 38/39 in the pre-SMP group versus 39/39 in the SMP group at both discharge and follow-up ( p discharge = 0.11, p follow-up = 0.10). The SMP was associated with at least 1 medication event in 7 participants, but no medication incidents. Patient and staff surveys showed a positive perceived value of the SMP. Conclusion Our results demonstrate that the SMP is associated with durable, improved medication knowledge, a trend towards improved self-efficacy, and largely positive perceptions among both staff and patient participants.
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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 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".