Impact of pharmacists as immunizers on influenza vaccination coverage in Nova Scotia, Canada
Bibliographic record
Abstract
Immunization coverage in Canada has continued to fall below national goals. The addition of pharmacists as immunizers may increase immunization coverage. This study aimed to compare estimated influenza vaccine coverage before and after pharmacists began administering publicly funded influenza immunizations in Nova Scotia, Canada. Vaccination coverage rates and recipient demographics for the influenza vaccination seasons 2010-2011 to 2012-2013 were compared with the 2013-2014 season, the first year pharmacists provided immunizations. In 2013-2014, the vaccination coverage rate for those ≥5 years of age increased 6%, from 36% in 2012-2013 to 42% (p<0.001). Pharmacists administered over 78,000 influenza vaccinations, nearly 9% of the province's population over the age of five. Influenza vaccine coverage rates for those ≥65 increased by 9.8% (p<0.001) in 2013-2014 compared to 2012-2013. Influenza vaccination coverage in Nova Scotia increased in 2013-2014 compared to previous years with a universal influenza program. Various factors may have contributed to the increased coverage, including the addition of pharmacists as immunizers and media coverage of influenza related fatalities. Future research will be necessary to fully determine the impact of pharmacists as immunizers.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".