The role of pharmacy technicians in vaccination services: a scoping review
Bibliographic record
Abstract
BACKGROUND: A busy pharmacy workload may limit a pharmacist's ability to meet the needs of vaccine-willing patients and also contribute to missed opportunities to engage with vaccine hesitant individuals. Opportunities for pharmacy technicians to support vaccination services may play a role in addressing increasing patient vaccination needs. PURPOSE: This research aims to review the role of pharmacy technicians in vaccination services that is supported by pharmacy practice research to date. METHODS: In compliance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocols, systematic searches were performed in PubMed, Embase, International Pharmaceutical Abstracts, Scopus, and CINAHL. Articles published through June 2020, in French, English, and Spanish, were screened for eligibility. Two independent reviewers screened titles and abstracts for inclusion. Data extraction of included study methodologies and results was performed by one reviewer and verified by a second reviewer. RESULTS: A total of 656 records were identified through the search of published literature. Full-text screening of 145 records identified 14 articles for inclusion. Most articles evaluated emerging pharmacy technician roles in patient screening (n = 8, 53%) and vaccine administration (n = 5, 36%). Implementation of both emerging roles demonstrated positive patient outcomes (n = 10, 72%). Screening activities were complicated by the complexity of the role, as well as its potential to increase overall time spent on vaccination services. Pharmacists and technicians advocated for accredited vaccine administration training owing to consistent benefits in pharmacy workflow efficiency, pharmacist clinical time, and pharmacy technician job satisfaction. CONCLUSION: This review supports the effective deployment of pharmacy technicians in delivering vaccination services. Despite pharmacy technician vaccine administration roles being highly regulated, professional advocacy by pharmacists and technicians can use the advantageous training, workflow, and patient outcomes benefits presented in this review. Early adopters of professional practice advancements for pharmacy technician vaccine administration may expand vaccination service capacity efficiently and safely, thereby reaching more patients.
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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 | 0.012 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".