Evidence demonstrating the pharmacist's direct impact on clinical outcomes in pediatric patients: An opinion of the pediatrics practice and research network of the American College of Clinical Pharmacy
Bibliographic record
Abstract
Abstract The pharmacist's role in pediatric care is critical for the provision of safe medication use secondary to differences in physical development, frequent off label use of medications, need for dose calculations, and the lack of standard dosage forms. Many regulatory agencies, health care organizations, and professional societies support the pharmacist as a member of the interdisciplinary team. However, specific details showcasing how pharmacists impact the care of pediatric patients in a quantifiable and meaningful way have not been well described. The purpose of this article is to provide a review of evidence demonstrating measurable clinical outcomes directly resulting from pharmacist participation in pediatric patient care. This report is an opinion paper of The American College of Clinical Pharmacy (ACCP) Pediatrics Practice and Research Network and has been endorsed by the Pediatric Pharmacy Association (PPA). This article represents the opinion of the Pediatrics Practice and Research Network of ACCP. It does not necessarily represent an official ACCP commentary, guideline, or statement of policy or position.
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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 | 0.041 | 0.216 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".