Practices and implementation factors of point-of-care testing for acute upper respiratory tract infections by community pharmacists in Alberta: A cross-sectional survey
Bibliographic record
Abstract
BACKGROUND: Community pharmacists in Alberta have a broad scope of practice and may conduct point-of-care (POC) tests for acute and chronic medical conditions. However, little is known about the provision and pharmacists' experiences in POC testing for respiratory infections. OBJECTIVES: To explore the clinical services offered by community pharmacist to patients with acute upper respiratory tract infections (URTI) by describing the types of POC tests performed and differences in implementation factors and confidence between active and inactive URTI POC testing providers. METHODS: Anonymous, online, cross-sectional survey with email invitations sent to 4035 community pharmacists registered with the Alberta College of Pharmacy in February 2024. The survey collected information on demographics and provision of POC testing services. An adapted version of the Determinants of Implementation Behavior Questionnaire (DIBQ) was used to determine barriers and facilitators. The data were summarized descriptively and compared between groups using univariate statistical tests. RESULTS: A total of 370 responses were included in the final analysis (response rate: 9.2%, 45% < 40 years old, 65% female, 28% rural, 73% have additional prescribing authorization). Most respondents (87%) provide assessments to patients presenting with URTI symptoms. Three quarters (72.7%) provide POC testing, 65% currently provide URTI POC tests, with 59.79% offering strep throat, 26.5% COVID-19 and 5.9% influenza POC tests. Active providers were more likely to agree or strongly agree to 26 out of 30 of the adapted DIBQ items, indicating that these were facilitators of implementation. The largest differences were in having the necessary resources (relative risk: 5.23; 95%CI: 3.34, 8.18), training (RR: 3.89; 95%CI: 2.57, 5.88) and knowing how (RR: 3.16; 95%CI: 2.33, 4.28) to deliver the service. In both groups, areas with low confidence were performing a focused physical assessment, analyzing rapid molecular tests and performing a nasal swab. CONCLUSION: Community pharmacists in our sample commonly provide POC testing for Strep pharyngitis. Our results suggest organizational factors, skills, and knowledge were facilitators of service provision.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".