DEVELOPMENT, IMPLEMENTATION, AND EVALUATION OF A COMMUNITY- AND HOSPITAL-BASED RESPIRATORY SYNCYTIAL VIRUS PROPHYLAXIS PROGRAM
Bibliographic record
Abstract
PURPOSE: To implement and deliver a respiratory syncytial virus prophylaxis (RSVP) program in response to the Canadian Pediatric Society recommendations. METHODS: A novel program was designed to provide inpatient RSVP for at-risk infants cared for in 1 tertiary care newborn intensive care unit (NICU). This inpatient program was part of a coordinated approach to RSVP, designed and implemented by 3 hospitals. An RSVP program logic model was created and used by a multidisciplinary team to evaluate the in-house program and identify areas of program activity requiring improvement. RESULTS: Following the 2000 to 2001 RSV season, a compliance and outcomes audit was performed in the tertiary center; 193 infants were enrolled in the RSVP program and 162 infants had received RSVP in the NICU [Mean = 1.64 doses]. Telephone follow-up with the parents of discharged infants identified that 159 infants (98%) had successfully completed their full course of RSVP. Using the RSVP program logic model, 5 areas for program improvement were identified including infant recruitment, patient transfer/discharge processes, product procurement, preparation/distribution/administration of doses, and healthcare team communication. CONCLUSIONS: Interdisciplinary collaboration is an important factor in the success of the RSVP program and has supported a consistent model of care for the delivery of RSVP. The program logic model provided a useful structure to systematically review the RSVP program in this organization.
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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 | 0.018 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".