Development of a pharmacist-coordinated system of chemotherapy protocols in an integrated healthcare delivery organization
Bibliographic record
Abstract
Objectives. To develop and coordinate protocols for chemotherapy regimens in a large integrated healthcare organization; to disseminate protocols in a timely fashion; to maintain protocols for continuous quality improvement; and to promote utilization of protocol-based chemotherapy. Methods. Two interdisciplinary groups reviewed the acceptability, accessibility, and appropriateness of the existing protocols, and proposed recommendations to be implemented by the Systemic Therapy Program of the agency. Results. A standard protocol format and a pharmacist-coordinated protocol system were developed. Protocols were relocated from the Intranet to the network computer directory and Internet website for increased accessibility. To date, 172 protocols are available on the network directory and the website, with 87% (150/172) reviewed by pharmacists and physicians of an interdisciplinary review panel. Preliminary analysis shows increased healthcare professionals’ satisfaction and a protocol use in 77% of patients treated. Conclusion. A pharmacist-coordinated chemotherapy protocol system improves protocol dissemination, protocol compliance, and chemo-therapy delivery and safety. The project enhances the pharmacist profile and credibility within the organization.
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 | 0.028 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".