Projected health and economic outcomes of extending public funding of pharmacy services to include administration of Pneu23 and Td/Tdap immunizations by pharmacy practitioners in New Brunswick
Bibliographic record
Abstract
Background: Although legislation permits New Brunswick pharmacy professionals to administer a wide range of immunizations, public funding for these services is currently limited to immunizations against influenza and COVID-19 and was recently extended to include pneumococcal immunization (Pneu23) in individuals aged 65 years or older. We used administrative data to project health and economic outcomes associated with the current Pneu23 program and with extension of public funding to include: 1) younger adults aged 19 years or older in the Pneu23 program, and 2) tetanus boosters (Td/Tdap). Methods: Two model scenarios were compared: a Physician-Only model in which physicians remain the only practitioners to administer publicly funded Pneu23 and Td/Tdap, and a Blended model in which this service is also provided by pharmacy professionals. Immunization rates by practitioner type were projected based on physician billing data accessed via the New Brunswick Institute for Research, Data and Training in conjunction with trends observed with influenza immunization by pharmacists. These projections were used along with published data to estimate health and economic outcomes under each model. Results: Public funding of Pneu23 (65+), Pneu23 (19+) and Td/Tdap (19+) administration by pharmacy professionals is projected to yield increased immunization rates and physician time savings compared with the Physician-Only model. Public funding of Pneu23 and Td/Tdap administration by pharmacy professionals in those aged ≥19 years would result in cost savings, owing primarily to productivity losses avoided in the working age population. Discussion: Increased immunization rates, physician time savings and cost savings may be realized if public funding were extended to include administration of Pneu23 in younger adults and Td/Tdap, by pharmacy practitioners.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".