Cost-utility analysis of offering a novel remunerated community pharmacist consultation service on influenza vaccination for seniors in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Despite the availability of free and accessible influenza vaccine to all Ontarians, uptake has remained suboptimal. Although reasons to not receive the vaccine vary widely, health care provider recommendations remain the most effective strategy to positively influence vaccination decisions. OBJECTIVES: This study aimed to predict the relative quality of life, costs, and cost-effectiveness of introducing a remunerated community pharmacist consultation service on influenza vaccination for Ontarians aged ≥ 65 years. METHODS: A cost-utility analysis was performed from a third-party public payer perspective over 1 year. The delivery of consultation services by community pharmacists on influenza vaccination, billable at CAD $15 was compared with current standard practices (absence of remunerated consultations). Model inputs were derived primarily from existing literature. The impact of parameter uncertainties was assessed through deterministic and probabilistic sensitivity analyses. RESULTS: The provision of influenza vaccine consultation services was predicted to prevent 2407 cases of mild influenza and 3 influenza-related deaths at an additional cost of CAD $2.03 per person over current practices. The incremental costs per quality-adjusted life-year (QALY) gained for the enhanced care strategy compared with standard care was CAD $2087. The interpretation of the base-case result was found to be robust across all sensitivity analyses. The projected additional costs of implementing pharmacist consultations in Ontario was estimated at CAD $1.15 million per year, and the anticipated benefits included a gain of 507 QALY per year. CONCLUSION: Pharmacist-delivered consultation services on influenza vaccination are cost-effective and lead to improved clinical outcomes for Ontario seniors. Introduction of such services offers a promising strategy to address challenges related to poor vaccine uptake in this group.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".