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Record W2316916185 · doi:10.1080/21645515.2015.1127490

Impact of pharmacists as immunizers on influenza vaccination coverage in Nova Scotia, Canada

2016· review· en· W2316916185 on OpenAlexaffabout
Jennifer E. Isenor, Tania A. Alia, Jessica L. Killen, Beverly Billard, Beth Halperin, Kathryn Slayter, Shelly McNeil, Donna MacDougall, Susan K. Bowles

Bibliographic record

VenueHuman Vaccines & Immunotherapeutics · 2016
Typereview
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsGovernment of Nova ScotiaNova Scotia Department of Health and WellnessUniversity of British ColumbiaNova Scotia Health AuthoritySt. Francis Xavier UniversityIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsVaccinationMedicineNova scotiaImmunizationInfluenza vaccineDemographicsPopulationInfluenza seasonFamily medicineEnvironmental healthDemographyImmunologyGeography

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.153
GPT teacher head0.487
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations43
Published2016
Admission routes2
Has abstractyes

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