Preventive care recommendations to promote health equity
Bibliographic record
Abstract
BACKGROUND: Avoidable disparities in health outcomes persist in Canada despite substantial investments in a publicly funded health care system that includes preventive services. Our objective was to provide preventive care recommendations that promote health equity by prioritizing effective interventions for people experiencing disadvantages. METHODS: The guideline was developed by a primary care provider-patient panel, with input from a patient-partner panel with diverse lived experiences. After selecting priority topics, we searched for systematic reviews and recent randomized controlled trials of screening and other relevant studies of screening accuracy and management efficacy. We used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach to develop recommendations and followed the Appraisal of Guidelines for Research and Evaluation (AGREE II) reporting guidance. We managed competing interests using the Guideline International Network principles. The recommendations were externally reviewed by content experts and circulated for endorsement by national stakeholders. RECOMMENDATIONS: We developed 15 screening and other preventive care recommendations and 1 policy recommendation on improving access to primary care. We recommend prioritized outreach for colorectal cancer screening starting at age 45 years and for cardiovascular disease risk assessment, to help address inequities and promote health. Specific interventions that should be rolled out in ways that address inequities include human papillomavirus (HPV) self-testing, HIV self-testing and interferon-γ release assays for tuberculosis infection. Screening for depression, substance use, intimate partner violence and poverty should help connect people experiencing specific disadvantages with proven interventions. We recommend automatic connection to primary care for people experiencing disadvantages. INTERPRETATION: Proven preventive care interventions can address health inequities if people experiencing disadvantages are prioritized. Clinicians, health care organizations and governments should take evidence-based actions and track progress in promoting health equity across Canada.
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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 | 0.050 | 0.213 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.015 | 0.013 |
| Insufficient payload (model declined to judge) | 0.020 | 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".