Practice facilitation for family physicians to contact patients unvaccinated for COVID-19: a randomized trial
Bibliographic record
Abstract
Context: Family physicians have an important role to play in encouraging vaccine confidence among their patients. We evaluated a practice facilitation intervention in partnership with Ontario Health, a provincial government agency, to support family physicians in Ontario with proactive outreach among patients unvaccinated for COVID-19. Objective: To determine whether a multicomponent practice facilitation intervention would increase vaccine rates among patients of family physicians with the largest number of unvaccinated patients. Study Design and Analysis: A 1:1 two-arm, pragmatic, cluster randomized controlled trial (Clinical trial#: NCT05099497). Setting or Dataset: The trial was conducted from November 2021-March 2022 in Ontario, Canada’s most populous province. Data were obtained from the provincial vaccine registry and were linked to routinely used administrative databases. Population Studied: 600 family physicians with the largest number of unvaccinated patients in the province. Intervention/Instrument: Practice facilitators offered physicians support to identify, reach out, and counsel their unvaccinated patients. Outcome Measures: Any vaccine dose during a four-month follow-up interval among rostered patients over 12 years/100. Results: 300 family physicians who cared for a median of 2,399 patients (IQR 2,024-2,747) were randomized to control; the 300 randomized to the intervention cared for a median of 2,394 patients (IQR: 1,907-2,829). Only 29% (n=90) of intervention physicians accepted assistance from a practice facilitator. Among those that received support, 58% (n=51) used technical support to identify unvaccinated patients in their EMRs, 29% (n=26) connected with medical student volunteers to contact patients on their behalf, and 31% (n=27) used automated calling to reach patients. The proportion of adult patients of control physicians with COVID vaccine doses was 82 (IQR: 78-85) at baseline and 83 (IQR: 80-86) after four months. In the intervention group, the proportion of patients with a COVID vaccine dose was 81 (IQR: 76-85) at baseline and 83 (IQR: 79-86) after four months. The relative rate of vaccine uptake of any dose was non-significant (RR= 1.0, CI:0.97-1.02, p=0.824). Conclusion: There was no detectable increase in vaccination uptake among patients who were rostered to family physicians in the intervention group. Low intervention fidelity is a possible explanation for the trial’s null’s results.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 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".