Bibliographic record
Abstract
Introduction Telepharmacy has the potential to enhance pharmacy services in oncology care, especially in remote areas. This scoping review explored the range, critical benefits and barriers of using telepharmacy services in oncology care. Methods The scoping review followed the Arksey and O’Malley’s five-stage framework to identify available evidence. PubMed, CINAHL, Embase, PsycINFO, Ovid MEDLINE and Scopus databases were searched for original research published between 2010 and 2020. The five dimensions of the Alberta Quality Matrix for Health were used to analyse reported outcomes. Results Eligible articles ( n = 21) were analysed. Telepharmacy in oncology care was used for follow-up, monitoring and counselling, intravenous chemotherapy and sterile compounding, expanding availability of pharmacy services, and remote education. Telepharmacy obtained high acceptability among cancer patients ( n = 5) and healthcare professionals ( n = 5), and increased accessibility of pharmaceutical services to underserved cancer populations ( n = 2). Commonly cited effectiveness and safety outcomes were improved patient adherence ( n = 5), increased pharmacy services ( n = 3) and early identification of medication-related problems ( n = 5). Telepharmacy improved efficiency in staffing and workload ( n = 3), and increased cost savings ( n = 3). A shortage of resources ( n = 5), technical problems ( n = 4) and prolonged turnaround time ( n = 4), safety concerns ( n = 2) and patient willingness to pay ( n = 1) were identified barriers to implementing telepharmacy in oncology care. Discussion Despite evidence pointing to the advantages and opportunities for expanding oncology pharmacy services through telepharmacy, certain challenges remain. Further research is needed to investigate safety concerns and patient willingness to pay for telepharmacy services.
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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 | 0.010 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.018 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".