Practice- and System-Based Interventions to Reduce COVID-19 Transmission in Primary Care Settings: A Qualitative Study
Bibliographic record
Abstract
Using qualitative interviews with 68 family physicians (FPs) in Canada, we describe practiceand system-based approaches that were used to mitigate COVID-19 exposure in primary care settings across Canada to ensure the continuation of primary care delivery.Participants described how they applied infection prevention and control procedures (risk assessment, hand hygiene, control of environment, administrative control, personal protective equipment) and relied on centralized services that directed patients with COVID-19 to settings outside of primary care, such as testing centres.The multi-layered approach mitigated the risk of COVID-19 exposure while also conserving resources, preserving capacity and supporting supply chains.Résumé À l' aide d' entrevues qualitatives auprès de 68 médecins de famille au Canada, nous décrivons les approches au niveau de la pratique et du système qui ont été utilisées pour atténuer HEALTHCARE POLICY Vol.19 No.2, 2023 [65] Practice-and System-Based Interventions to Reduce COVID-19 Transmission in Primary Carel' exposition à la COVID-19 dans les milieux de soins primaires partout au Canada afin d' assurer la continuité de la prestation des soins primaires.Les participants ont décrit comment ils ont appliqué les procédures de prévention et de contrôle des infections (évaluation des risques, hygiène des mains, contrôle de l' environnement, contrôle administratif, équipement de protection individuelle) et comment ils comptaient sur des services centralisés qui dirigeaient les patients atteints de la COVID-19 vers d' autres établissements que les soins primaires, comme les centres de dépistage.L' approche à plusieurs niveaux a atténué le risque d' exposition à la COVID-19 tout en ménageant les ressources, en préservant les capacités et en soutenant les chaînes d' approvisionnement.
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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 | 0.021 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.017 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".