Pharmacy-based Immunization in Rural Communities Strategy (PhICS)
Bibliographic record
Abstract
BACKGROUND: Influenza is a major cause of morbidity and mortality in Canada, with up to 7000 influenza-related deaths occurring every year. The elderly and individuals with chronic diseases are at increased risk for influenza-related morbidity and mortality. METHODS: We conducted a 2-year, community cluster-randomized trial targeting elderly people and at-risk groups to assess the effectiveness of pharmacy-based influenza vaccination clinics on influenza vaccination rates. Small rural communities in interior and northern British Columbia were randomly allocated to the intervention or control. In the intervention communities, pharmacy-based influenza vaccination clinics were held and were promoted to eligible patients using personalized invitations from the pharmacists, invitations distributed opportunistically by a pharmacist to eligible patients presenting to pharmacies during the flu season and community-wide promotion using posters and the local media. The main outcome measure was a difference in the mean influenza vaccination rates. The immunization rates were calculated using the number of immunizations given in each community divided by the population size estimated from the census data. RESULTS: Baseline influenza immunization rates in the population ≥65 years of age were the same in the control (n = 10, mean 85.6% [SD 16.6]) and intervention (n = 14, mean 83.8% [SD 16.3]) communities in 2009 (p = 0.79). In 2010, the mean influenza immunization rate was 56.9% (SD 28.0) in the control communities (n = 15) and 80.1% (SD 18.4) in the intervention communities (n = 14) (p = 0.01) for those ≥65 years of age. However, in 2010, for those 2 to 64 years with chronic medical conditions, the immunization rates were lower in the intervention communities (mean 16.3% [SD 7.1]) compared with the control communities (mean 21.2% [SD 5.8]) (p = 0.04). CONCLUSION: Clinics were feasible and well attended and they resulted in increased vaccination rates for elderly residents. In contrast, vaccination rates in the younger population with comorbidities remained low and unchanged.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".