Implementation of a telephone callback service for ambulatory oncology patients
Bibliographic record
Abstract
Introduction. A pilot project was established at the Cross Cancer Institute pharmacy to assess the feasibility of implementing a patient callback program to determine which patients would benefit from a callback and the impact a callback service would have on the workload of the pharmacy department. Program description/development/implementation/evaluation. A pharmacy student conducted the pilot project over a 14-week time period. Four categories of patients were selected for inclusion in the pilot. The student approached patients at the time of medication pick-up to receive verbal permission to be included in the callback program. A standardized callback form was utilized to record medication information and any recommendations made. Data were collected on the numbers of patients in each category with questions or concerns as this was felt to be indicative of patients who would most benefit from a callback. The total time spent making the telephone calls was recorded. Over the eight-week period, 530.5 minutes were spent making the telephone calls with the average length of call being 3.27 minutes. Discussion/conclusion. The student researcher proposed that three patient groups would benefit from receiving a callback: new patients or patients on new medications; elderly patients; and patients with specific disease-drug combinations. The project also provided an estimate of pharmacist time required to implement such a service and it was concluded that implementation could occur with minimal disruption to workflow.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".