Uptake and outcomes of VaxCheck, an adult life-course vaccination service: A study among community pharmacists
Bibliographic record
Abstract
Vaccination rates among Canadian adults remain suboptimal. Community pharmacists have increasingly adopted an active role in vaccination and are trusted by the public to provide vaccination-related advice and care. The aim of this prospective descriptive study was to develop and test a novel clinical service, VaxCheck, to support proactive life-course vaccination assessments by community pharmacists. From October 2022-May 2023, 123 VaxCheck consultations were performed at 9 community pharmacies within the Wholehealth Pharmacy Partners banner in Ontario, Canada. Patient age averaged 60 years and 35.8 % had at least one chronic disease risk factor, 17.7 % had lifestyle-related risk factor(s), and 15.4 % were immunocompromised. 95.1 % of VaxCheck consultations resulted in at least one vaccine recommendation, averaging three vaccines per patient. Most frequently recommended vaccines were those against pneumococcal disease, tetanus/diphtheria, herpes zoster, COVID-19, and influenza, with acceptance rates highest for those available without a prescription and at no charge at the pharmacy. Patient feedback was positive with 85 % of respondents agreeing or strongly agreeing that they would recommend the service to others. Vaccine administration at the time of the consultation occurred with only 5.9 % of recommended vaccines, frequently impacted by limitations to scope of practice related to pharmacist ability to prescribe and/or administer the vaccine and lack of pharmacy access to publicly funded vaccine supply for those meeting eligibility criteria. Community pharmacists performing a VaxCheck consultation can proactively identify indicated vaccines for patients. Expansion in scope of practice and access to publicly funded vaccine is recommended to further support vaccine uptake.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".