Patient monitoring programs in oncology pharmacy practice: A survey of oncology pharmacists in Atlantic Canada
Bibliographic record
Abstract
BACKGROUND: There has been a dramatic increase in new drug approvals in oncology, consisting of both small molecule inhibitors and monoclonal antibodies. However, Health Canada approval for many of the new agents was based on single randomized trials consisting of only a few hundred patients. As more patients get treated with these newer agents, there is the potential for new and discrete toxicities. Pharmacists are in an ideal position to identify, monitor, manage, and even preempt future events, given their close proximity to the patient. However, the extent of pharmacists' involvement in formal patient programs is unknown. To address this knowledge gap, a survey of oncology pharmacists practicing in Atlantic Canada was conducted. METHODS: A structured mailing strategy was adopted as recommended by Dillman (1978). Standardized data collection forms were electronically mailed to 60 oncology pharmacists. Survey items consisted of respondent demographic information, practice setting, the existence of a formal patient monitoring program managed, and if patients are contacted by telephone following the completion of their anticancer cycle. RESULTS: Overall, 31 completed surveys were received, for an overall response rate of 50%. Respondents had a median age of 42 and a median of 18 years' (range 1 to 25) professional experience as a pharmacist. Only 18 of the 31 (58%) respondents indicated that there was a formal monitoring and call back program managed by pharmacy available at their institution. For those without such programs, the main reasons were due to staffing issues and lack of adequately trained clinical personnel. Overall, 100% of respondents would favor the development of a formal monitoring program in hospitals with a high volume of anticancer drug prescribing. CONCLUSIONS: Even though the number of new anticancer drugs being introduced into clinical pharmacy practice is increasing, formal patient monitoring and patient call back programs are not universal in Atlantic Canada hospitals.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".