The Components of an Advanced Fellowship Training Program in Pediatric Antimicrobial Stewardship
Bibliographic record
Abstract
Background. Training opportunities which focus on Pediatric Antimicrobial Stewardship (PAS) are limited. To our knowledge no formal advanced fellowship training programs in this area exist in North America. We sought to outline the components of a PAS Advanced Fellowship Training Program. Methods. The training program was developed at a tertiary care children's hospital. We identified key competencies required by an infectious diseases physician taking a leadership role in PAS program development and identified local experts/educational resources that could assist in the attainment of those competencies by the trainee. Results. A 1-year advanced fellowship training program was designed with the following components: research (50%), education (20%), program planning/development (20%), and database management/utilization (10%). Key competencies identified included the following: (1) expertise in the design, implementation and evaluation of research and quality improvement initiatives; (2) ability to use data from pharmacy and hospital relational databases to calculate and analyze antimicrobial utilization metrics within the pediatric and neonatal populations; and (3) experience performing common antimicrobial stewardship program (ASP) activities including prospective audit and feedback reviews, guideline development, and development of educational initiatives for hospital staff. CanMeds objectives were defined as per the framework set by the Royal College of Physicians and Surgeons of Canada. The advanced fellowship training program emphasized the importance of multidisciplinary collaboration in ASPs and to date has involved collaborative projects with pediatric surgeons, hospitalists, residents, community pediatricians, and pediatric/adult pharmacists. Conclusion. The competencies required by a physician taking a leadership role in an ASP were incorporated into the design of a PAS Advanced Fellowship Training Program. This program could serve as a prototype for a formally recognized educational initiative at other institutions. Disclosures. All authors: No reported disclosures.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".