Optimizing patient education of oncology medications: A quantitative analysis of the patient perspective
Bibliographic record
Abstract
BACKGROUND: With the ever-increasing complexity of cancer treatments, oncology medication patient education is becoming a progressively important component of cancer care. Despite this, cancer patients frequently report that they receive inadequate information and feel that their education needs have not been met. OBJECTIVE: To explore patients' perspectives of optimal oncology medication education across Nova Scotia. METHODS: This was a descriptive survey of adult medical, hematological and gynaecological oncology outpatients receiving intravenous chemotherapy within the Nova Scotia Health Authority between January 26 and April 30, 2018. RESULTS: One hundred forty-two responses were included; 41% and 47% of respondents reported being satisfied or very satisfied with their oncology medication education, respectively; 30% and 43% of respondents would like the opportunity to receive education or follow-up from a hospital pharmacist, respectively. Respondents with post-secondary education were found to have 2.82 higher odds of wanting to make an appointment for education with a hospital pharmacist. CONCLUSIONS: Patients were generally satisfied with their oncology medication education despite the majority not receiving education from a hospital pharmacist. Patients with a higher level of formal education were more likely to want the opportunity to schedule an appointment for education with and/or receive follow-up from a hospital pharmacist. The oncology medication education participants received in the past appeared to align with their education preferences. Findings from this research can be used to optimize the limited time healthcare professionals have to provide meaningful and effective oncology medication patient education and improve patient-centered 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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".