38 A proactive outreach approach to prevent primary care patients from falling through the cracks
Bibliographic record
Abstract
Description Primary care providers (PCPs) focus on patients presenting for care, but access limitations may create care gaps for those impacted by social determinants of health. Proactive Care Coordination Assistants (PCCAs) at Edmonton Southside Primary Care Network proactively outreach to patients, ensuring equitable access for 212 participating physicians. As a result of outreach to patients due for care or preventative screening, colorectal, breast, and cervical cancer screening rates increased from 59% to 61%, 51% to 57%, and 53% to 60%, respectively (figure 1). Diabetes screening rates increased from 74% to 88% (figure 2). Over 90% of patients were seen within the recommended timeframe (figure 3). Panel accuracy, measured by the alignment of registered patients with billing data estimates, also improved after the adoption of this model. With high physician participation in this equitable approach high results are promising for spread and scale.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.040 | 0.006 |
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".